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<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:wfw="http://wellformedweb.org/CommentAPI/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" > <channel> <title>National centre for AI</title> <atom:link href="https://nationalcentreforai.jiscinvolve.org/wp/feed/" rel="self" type="application/rss+xml" /> <link>https://nationalcentreforai.jiscinvolve.org/wp</link> <description></description> <lastBuildDate>Tue, 25 Apr 2023 16:06:52 +0000</lastBuildDate> <language>en-GB</language> <sy:updatePeriod> hourly </sy:updatePeriod> <sy:updateFrequency> 1 </sy:updateFrequency> <generator>https://wordpress.org/?v=6.2</generator> <item> <title>AI outside of education </title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/25/ai-outside-of-education/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/25/ai-outside-of-education/#respond</comments> <dc:creator><![CDATA[Helen Nicholson]]></dc:creator> <pubDate>Tue, 25 Apr 2023 16:06:52 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=926</guid> <description><![CDATA[  In this blog we explore the use of AI across a few very different sectors – Museums & Galleries, Recruitment, Air travel, and Banking. The purpose is to see how other sectors, each at their own stages of AI maturity, are innovating with the same types of AI tools which we are exploring the […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/25/ai-outside-of-education/">AI outside of education </a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[  In this blog we explore the use of AI across a few very different sectors – Museums & Galleries, Recruitment, Air travel, and Banking. The purpose is to see how other sectors, each at their own stages of AI maturity, are innovating with the same types of AI tools which we are exploring the use of in education. These might serve as inspiration for your work in education, or they may just be an interesting window into how other sectors are using AI tools day to day. <h2>Museums & Galleries </h2> Museums & Galleries have increasingly embedded technology to enhance the visitor experience, and institutions are keenly exploring how AI can provide even deeper insights into visitor behaviour. In 2021 the <a href="https://www.enea.it/en/news-enea/news/cultural-heritage-project-shareart-to-measure-the-appreciation-of-works-of-art-with-artificial-intelligence-kicks-off#:~:text=The%20collaboration%20between%20ENEA%20and,artificial%20intelligence%20expertise%20of%20international">Istituzione Bologna Musei</a> began a pilot project which placed a series of cameras and sensors around its galleries to collect data on visitor behaviour. This allowed the museum to track visitor’s pathways through the gallery, seeing which pieces they stopped at and measuring their engagement with the artwork based on facial expression and posture. The information gathered might provide curators a better understanding of how viewers interact with the paintings on display. Wider museum issues can be brought to light too – for instance when analysing visitor behaviour, the museum also tracked how well visitors were adhering to covid-19 restrictions. AI has also been featured as a component of the exhibitions themselves. The award winning <a href="https://www.tate.org.uk/press/press-releases/artificial-intelligence-arrives-tate-britain-ik-prize-2016-unveiled">Recognition exhibition</a> at Tate Britain utilised <a href="https://exploreai.jisc.ac.uk/category/vision">visual AI tools</a> (including object and facial recognition) in combination with Natural Language Processing (NLP) to relate collection items to modern day images. The connections made by the AI programme helped visitors look at the collection in new ways and gain an understanding of the AI itself. A <a href="https://www.cmu.edu/news/stories/archives/2022/april/adding-ai-to-museum-exhibits-increases-learning-keeps-kids-engaged-longer">recent project</a> from Carnegie Mellon University added a virtual assistant to a hands-on exhibit for children. The gorilla themed assistant, NoRilla, replaced the frequently ignored museum signage, guiding the children through the experience and challenging them further with questions. The results were that children engaged with and learned more from the interaction with NoRilla compared to a standard hands-on exhibit. <h2>Recruitment </h2> Hiring and recruitment is a field that has experienced increasing adoption of AI tools, the <a href="https://www.littler.com/files/2022_littler_european_employer_survey_report.pdf">2022 Littler European Employer Survey Report</a> found that 28% of organisations surveyed were already using AI to support hiring and a further 19% were intending to do in the next year. There are AI tools available at almost every stage in a hiring journey too – from hosting a <a href="https://www.brazen.com/">virtual careers fair</a>, using a chatbot to speak with potential candidates, to holding the interview virtually. Notably, generative AI tools have made it possible to create informative job descriptions quickly by prompting the tool with the key aspects of the role and allowing the generator to produce the full description. Services like <a href="https://textio.com/">text.io</a> then go a step further and provide writing support which directs the writer to more accessible, neutral language in an effort to reduce unconscious bias in job postings. Bias is a key concern in the use of AI for recruitment and notably some providers have had to make changes to prevent their services from perpetuating harmful biases. In 2021, Hire Vue, a company that offers automated, AI-assisted video interviewing services, <a href="https://www.wired.com/story/job-screening-service-halts-facial-analysis-applicants/">withdrew the service’s visual analysis feature</a>, which employed facial recognition to examine candidates’ expressions. The change was made following criticisms of bias in Hire Vue’s system as well as research conducted by Hire Vue itself which indicated that visual analysis did not correlate well enough with strong job performance. <h2>Air Travel </h2> If you’ve used a search engine to find the best price for a flight, then AI has likely already been involved to help you make optimal travel plans. Travel technology company Amadeus have identified though that these searches take considerable computing power and generate high carbon emissions. To combat this, they are also using AI to make their flight search more energy efficient. Their model is trained on previous customer searches to predict which flight combinations are most likely to be good value for the searcher, allowing them to optimise their search engine and <a href="https://developers.amadeus.com/blog/machine-learning-reduce-flight-search-carbon-footprint">save over 43 tons in</a> CO2 emissions a year. At the airport there are ambitious, organisation wide implementations like Schipol airport’s aim to utilise AI in order to be a completely <a href="https://www.ai.nl/artificial-intelligence/how-floris-hoogenboom-and-schiphol-are-using-artificial-intelligence-to-make-the-airport-autonomous-by-2050/">autonomous airport by 2050</a>. The AI driven airport already utilises a range of AI tools across its operations today, including in the ‘turnaround insights’ project which uses deep learning to analyse live aircraft footage in order to optimise the many vital processes involved in receiving an incoming flight and preparing it to depart again safely. While lost luggage is handled by the <a href="https://www.lostandfoundsoftware.com/">Lost and Found</a> service which cleverly uses a combination of NLP and image recognition (including identifying colours, brands and serial numbers) to match lost luggage with its owner. <h2>Banking </h2> The banking industry has been embracing AI for customer service with chatbots and virtual assistants now commonplace for most major banks. These have evolved too and allow customers to not only ask questions but perform actions like transferring funds and setting card limits. HSBC notably has even brought digital assistants in branch by deploying the <a href="https://fintechmagazine.com/banking/hsbc-rolls-out-softbanks-robot-pepper-achieve-branch-future">Pepper robot</a>, developed by SoftBank Robotics and equipped with sentiment analysis by Affectiva, in some of its U.S. branches to interact with customers in person (in robot?). Increasingly AI tools are improving banking customers ability to self-serve which reduces customer wait times and increases capacity. Over the last five years many major banks have begun to allow new customers to open accounts directly through their mobile apps. The use of biometrics and facial recognition allows new customers to open bank accounts securely by recording short videos or taking selfies on their phones. This takes the time to open an account down from days to minutes and improves accessibility for customers who cannot visit branches in person. Notably NatWest found that fraudulent <a href="https://www.theguardian.com/business/2019/jun/20/natwest-is-first-big-uk-bank-to-let-customers-open-account-with-a-selfie">account applications significantly decreased</a> after launching their in-app account opening process. AI is playing an important role in fraud prevention behind the scenes too. Fraud prevention relies on being able to identify unusual activity, as such predictive models can be hugely helpful at improving fraud detection systems. With AI, banks can parse through massive volumes of customer data to build more accurate profiles of customer transactions so that any abnormal activity can be quickly flagged. <a href="https://monzo.com/blog/2021/10/28/machine-learning-at-monzo-in-2021">Digital bank Monzo</a> have excelled at using machine learning to combat financial crime and their fraud prevention model was recognised at the 2021 Tackling Economic Crime Awards (TECAs). <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/25/ai-outside-of-education/">AI outside of education </a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/25/ai-outside-of-education/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Generative AI: Lifeline for students or threat to traditional assessment?</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/21/generative-ai-lifeline-for-students-or-threat-to-traditional-assessment/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/21/generative-ai-lifeline-for-students-or-threat-to-traditional-assessment/#respond</comments> <dc:creator><![CDATA[Marieke Guy]]></dc:creator> <pubDate>Fri, 21 Apr 2023 08:28:30 +0000</pubDate> <category><![CDATA[AI in Education: Here and Now]]></category> <category><![CDATA[Accessibility]]></category> <category><![CDATA[Assessment]]></category> <category><![CDATA[ChatGPT]]></category> <category><![CDATA[Higher Education]]></category> <category><![CDATA[Student Experience]]></category> <category><![CDATA[student voice]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=919</guid> <description><![CDATA[Co-authored by Marieke Guy, Head of digital assessment, UCL and Chris Thomson, Jisc. As generative AI embeds itself into the world, understanding students’ perspective on what it means for their learning and assessment is more important than ever. We live in fast moving and concerning times. The leaders at our HE institutions have found themselves […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/21/generative-ai-lifeline-for-students-or-threat-to-traditional-assessment/">Generative AI: Lifeline for students or threat to traditional assessment?</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[Co-authored by Marieke Guy, Head of digital assessment, UCL and Chris Thomson, Jisc. As generative AI embeds itself into the world, understanding students’ perspective on what it means for their learning and assessment is more important than ever. We live in fast moving and concerning times. The leaders at our HE institutions have found themselves flung into a brave new world where the ground shifts almost daily. Students too are learning to navigate this new landscape. As well as disruption to assessment, we’re beginning to see how students are engaging with these new tools in ways that complement and challenge notions of what it means to study for a degree. With this in mind, in March in the shadow of London’s Olympic Stadium, Kathy Armour, Vice-Provost (Education & Student Experience) at UCL brought these two groups together, Russell Group university leaders and a panel of students, to discuss the future of degree assessment. A team from across UCL with some support from Jisc worked with the panel of students over a number of weeks to explore these emerging issues. Our aim was to start forming a set of principles that universities and other institutions could follow as they think how to respond to the challenges of mainstream generative AI. We’d like to share what we learned from working with these students. <h2>Staying relevant</h2> Students are not waiting to be told what to do! We saw that AI is already an established part of legitimate scholarly practice for many students and they have a great deal of awareness of the complex situation facing tertiary education. Their accounts made it clear that the genie is out of the bottle; AI is now so deeply integrated into their learning experience that it would be futile and counter-productive to resist the change. For many, AI has become a “lifechanging” educational companion, offering a level of support that is impossible to ignore. This could be in helping to get a quick summary of a lengthy article or to support international students translating an assignment written in their first language into English. The students argued returning to traditional exam halls, engaging in an AI detection arms race or proscribing it outright would be detrimental to their future employability and wellbeing. Our students want to be prepared for the wider world and future workplace. AI is becoming part of that reality so there is a need for institutions to engage with AI in learning, teaching and assessment to ensure validity, currency, authenticity and relevance. Students pointed to friends who were already creating AI-based start-ups. <h2>Maintaining academic rigour</h2> Whilst AI-enabled automation has benefits, it is important to ensure that important learning and developmental opportunities are not missed. Students should be encouraged to build academic skills in areas including study skills and the importance of digesting and critiquing information and the students recognized there was a delicate balance to strike here.. They encouraged us to be curious about the reasons why AI tools might be used by some to cheat. For many, said one, much of this comes down to high levels of stress, unrealistic workloads or a lack of support in study skills. <h2>Providing clarity</h2> Our panel was looking for clear guidance from their institution about where and how AI tools are being used to support teachers in marking and feedback. Their views on this were sophisticated, recognising the benefits to teachers of reduced workload and stress through automated processes and how that could lead to improved relationship building and contact time. They balanced this with concerns about how transparent these emerging tools might be and how certain aspects of feedback and marking were better suited to AI-enhancement while others involving higher levels of learning needed the human touch. They also wanted clarity on the how their use of AI to support essay writing, assuming it’s properly acknowledged and referenced, might affect marking. A few asked, might a student submitting a piece of work without using AI assistance be marked higher or lower than someone who did use AI to produce a better quality result? These are complex ethical questions with no clear answer yet. <h2>Ensuring fairness</h2> Students are extremely concerned about fairness in assessment and marking where AI tools are used. A particular area of concern was how a lack of access to core AI tools would disproportionately affect already disadvantaged students. The panel discussed the potential for a widening gap between those who can afford AI tools and those who cannot. They raised the question of whether universities should provide paid-for versions of AI tools as part of their standard IT provision. <figure id="attachment_922" aria-describedby="caption-attachment-922" style="width: 750px" class="wp-caption alignnone"><img decoding="async" class="wp-image-922 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/UCL2-e1681983498743.png" alt="The student panel mentioned in the article listening to Kathy Armour give a summary of the discussion" width="750" height="485" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/UCL2-e1681983498743.png 750w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/UCL2-e1681983498743-300x194.png 300w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption id="caption-attachment-922" class="wp-caption-text">Student panel on AI and assessment facilitated by Chris Thomson, Jisc. The panel summary was provided by Kathy Armour, Vice-Provost (Education & Student Experience) at UCL</figcaption></figure> <h2>Enhancing relationships</h2> We’re being presented with a significant opportunity for open dialogue with students about the purpose of education and assessment in relation to AI but also in the broader sense. This thought-provoking event demonstrated the importance of engaging in open dialogue with students about the role of AI in education and assessment. As Kathy Armour noted in her closing remarks, the challenges posed by AI and assessment are not new; they are rooted in longstanding issues of assessment and curriculum design that continue to challenge the sector. Embracing the potential of AI in education can offer a lifeline to students, but it requires a delicate balance between technological innovation and maintaining the integrity of traditional learning experiences. We feel by working together, students and educators can create a path forward that incorporates AI in a way that benefits all. Thanks go to those involved in this work: Students: <ul> <li>Matthew Banner – Postgraduate in the third year of a PhD In Biochemical Engineering, leading on a student-led partnership project considering assessment design and AI.</li> <li>Sophie Bush – Undergraduate student on History and the Philosophy of Science BSc and lead course rep for Science and Technology studies.</li> <li>Megan Fisher – Second-year undergraduate student studying Economics, with chosen modules in Environmental Economics and Algebra.</li> <li>Rachel Lam – First-year undergraduate law student, serves as a student partner on the assessment design and quality review team.</li> <li>Jennifer Seon – In last year of my part-time master’s programme studying Education and Technology, dissertation will focus on collaborative problem-solving in assessment. Recently interviewed AI expert Wayne Holmes for a podcast with the UCL AI Society.</li> <li>Bernice Yeo – Postgraduate student taking the MA in Education and Technology. Works as an examiner for the International Baccalaureate.</li> <li>Sopio Zhgenti – Postgraduate student studying Education and Technology at the Institute of Education with special interest in Artificial Intelligence.</li> </ul> Staff: <ul> <li>Marieke Guy (Head of Digital Assessment), UCL</li> <li>Zak Liddell (Director of Education & Student Experience, MAPS), UCL</li> <li>Joanne Moles (Head of Assessment Delivery and Platforms), UCL</li> <li>Jennifer Griffiths (Associate Director in the UCL Arena Centre for Research-based Education), UCL</li> <li>Lizzie Vinton (Assessment Regulations and Governance Manager, Academic Services) , UCL</li> <li>Chris Thomson (Programme lead for teaching, learning and assessment), Jisc</li> </ul> The event also featured visionary case-studies from sector-experts on AI: Sue Attewell, Head of edtech and lead at Jisc’s national Centre for AI in tertiary education, Professor Mike Sharples from the Institute of Educational Technology at the Open University and Michael Veale, Associate Professor and Deputy Vice Dean (Education) in the Faculty of Laws at UCL. This blog post was edited with the assistance of ChatGPT4. The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/21/generative-ai-lifeline-for-students-or-threat-to-traditional-assessment/">Generative AI: Lifeline for students or threat to traditional assessment?</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/21/generative-ai-lifeline-for-students-or-threat-to-traditional-assessment/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>AnyWyse pilot launched: seeking FE colleges to pilot AI for developing engaging audio content</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/17/anywyse-pilot-launched-seeking-fe-colleges-to-pilot-ai-for-developing-engaging-audio-content/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/17/anywyse-pilot-launched-seeking-fe-colleges-to-pilot-ai-for-developing-engaging-audio-content/#respond</comments> <dc:creator><![CDATA[Tom Moule]]></dc:creator> <pubDate>Mon, 17 Apr 2023 11:40:48 +0000</pubDate> <category><![CDATA[NCAI Pilots]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=907</guid> <description><![CDATA[The team at the national centre for AI in tertiary education are pleased to announce that we will be piloting AI platform Anywyse with FE colleges. Anywyse empowers educators to produce engaging audio-based learning material (called ‘Wysers’) for their students. Through the use of AI, existing learning materials – workbooks, reading materials, exercises, etc– can […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/17/anywyse-pilot-launched-seeking-fe-colleges-to-pilot-ai-for-developing-engaging-audio-content/">AnyWyse pilot launched: seeking FE colleges to pilot AI for developing engaging audio content</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[<img decoding="async" loading="lazy" class="alignnone wp-image-911" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/audio-300x162.jpg" alt="" width="536" height="289" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/audio-300x162.jpg 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/04/audio.jpg 458w" sizes="(max-width: 536px) 100vw, 536px" /> The team at the national centre for AI in tertiary education are pleased to announce that we will be piloting AI platform Anywyse with FE colleges. <a href="https://www.anywyse.audio/">Anywyse</a> empowers educators to produce engaging audio-based learning material (called ‘Wysers’) for their students. Through the use of AI, existing learning materials – workbooks, reading materials, exercises, etc– can be transformed into exciting, podcast-style modules, thus expanding the ways in which students can learn. Through the pilot we want to help colleges enhance their skills in AI implementation while producing fun, engaging content for learners. Meanwhile, the pilot is a great opportunity for Jisc to learn about the strengths and areas for development of AI solutions. As part of the pilot, we will therefore be conducting an evaluation of Anywyse, which will involve us conducting a series of interviews and surveys with participants. For those interested in participating, we suggest that colleges focus on using AnyWyse to develop content for subjects like: psychology, history, law, literature, philosophy, etc. – rather than for mathematical and technical subjects. <h2>Pilot Timeline</h2> Stage 1 (April 2023) – up to 6 FE colleges will be selected to take part in the pilot (please see details of how to express your interest below) Stage 2 (early May 2023) – participating colleges will receive training on how to use the platform and how to go about developing their Wysers. Stage 3 (May- early June 2023) – colleges will use the Anywyse platform to create engaging audio content Stage 4 (June 2023) – colleges will make the content available to their students Stage 5 (July 2023) – colleges will work with Jisc and Anywyse to evaluate the platform and understand staff/student experiences   <h2>Expected Workload</h2> As part of the pilot, we ask that participating colleges commit to the following: <ul> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1">Colleges appoint one Champion, who will help spread awareness of the Wysers (audio content developed on AnyWyse) produced during the pilot among students and teachers, and who will also help gather input for the final evaluation survey. </li> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1">Colleges appoint one Creator, a subject-matter expert who will use the Anywyse platform to create the Wysers, and will quality assure the produced material. </li> <li data-leveltext="" data-font="Symbol" data-listid="2" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1">(Please note, it is possible for one person to do both the creator and champion task) </li> </ul> The expected workload for the Creator is around 8 hours in total, and the expected workload for the champion is around 2 hours total. <h2>Expressing Interest</h2> We aim to have held meetings with prospective colleges, and have selected piloted participants by 28th April, 2023. If you are interested in participating, could you please email <a href="mailto:ncai@jisc.ac.uk">ncai@jisc.ac.uk</a> before close of play on 20th April to express your interest, and please also give details of your availability during the weeks of the 17th April or 24th April for a discussion about the pilot (45 minute slots). You can find out more about AnyWyse by visiting their <a href="https://www.anywyse.audio/">website</a>. If you have any further questions for us, please email <a href="mailto:ncai@jisc.ac.uk">ncai@jisc.ac.uk.</a>     The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/04/17/anywyse-pilot-launched-seeking-fe-colleges-to-pilot-ai-for-developing-engaging-audio-content/">AnyWyse pilot launched: seeking FE colleges to pilot AI for developing engaging audio content</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/04/17/anywyse-pilot-launched-seeking-fe-colleges-to-pilot-ai-for-developing-engaging-audio-content/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Means. Motive, Opportunity: A Composite Narrative about Academic Misconduct</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/27/means-motive-opportunity-a-composite-narrative-about-academic-misconduct/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/27/means-motive-opportunity-a-composite-narrative-about-academic-misconduct/#comments</comments> <dc:creator><![CDATA[Lawrie Phipps]]></dc:creator> <pubDate>Mon, 27 Mar 2023 10:19:36 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[Assessment]]></category> <category><![CDATA[ChatGPT]]></category> <category><![CDATA[Ethics of AI]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=896</guid> <description><![CDATA[Academic misconduct seems to have been brought into sharp relief over the last few months with a huge amount of hyperbole around large language models, or “generative AI”. Probably the most talked about was the arrival of ChatGPT3 just before Christmas 2022, social channels quickly lit up with discussions about how it will disrupt education, […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/27/means-motive-opportunity-a-composite-narrative-about-academic-misconduct/">Means. Motive, Opportunity: A Composite Narrative about Academic Misconduct</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[Academic misconduct seems to have been brought into sharp relief over the last few months with a huge amount of hyperbole around large language models, or “generative AI”. Probably the most talked about was the arrival of ChatGPT3 just before Christmas 2022, social channels quickly lit up with discussions about how it will disrupt education, often with polarising views. But academic misconduct has always been a concern in education. The most common question is “why do students cheat?”, but that just deflects from a range of other issues. It also diverts us from another question, “why do academics cheat?” For several weeks I have been gathering anonymous stories from academics and students. In this post, I have sought to weave together some of the student and staff voices, and other non-sourceable data to create some understanding of how large language models and so-called generative AI have been used. However, as interviews continued, other topics in adjacent areas were discussed and presented in the research context too. These are where some of the voices may be viewed by some readers to have crossed a line into academic misconduct. The term “composite” here refers to the narrative being constructed from multiple voices and other sources. This composite narrative aims to create an honest and open understanding of the cultural use of generative technologies, and those adjacent activities that were brought to light in the course of the research, without fear of prosecution for actual or perceived misconduct. I want to start out by saying that I believe no one starts out to cheat or behave dishonestly. That may be seen as naive, but I do not want to work in a system that focuses on “policing behaviours”. But I think it is worth looking at academic misconduct through a familiar police adage that writers of fictional crime seem to constantly employ “Means, Motivation, Opportunity”. First, here are two composite stories that use some of the accounts I collected during the research, and again, these are fictionalised, but pull together real voices. <h3>Sam </h3> Sam is a second-year student who is studying a STEM subject. They enjoyed the first year as none of it “counted”, but as they started their second year, they feel more pressure as the work now “counts” toward their final degree classification. Added to this they work part-time in a local supermarket, but the job is part-time in name only some weeks as to make ends meet, they sometimes do more than 30 hours work. Sam feels that the academic environment they are studying in is highly competitive, they want to do well, and they are thinking of doing post-graduate studies, and feel they need the grades to do that. “Every assessment is important and judged” and in Sam’s mind, they are all equally weighted. Sometimes lots of assessments from different modules come all at once. In January, with a deadline approaching, Sam started using the ChatGPT tool to expand some of their work in word length, and to make their drafts into better grammar. This felt like a good time-saving device and did not get flagged by a plagiarism detector. As weeks went on some of the assessments started to feel like “everything was coming at once”, at this point Sam started thinking about using it to alleviate their workload. “I got an essay online, just a poor example really, I knew it would get flagged in the checker, but I also knew I could rewrite it quickly to suit the exact essay title, using ChatGPT, I did this by doing it in small sections where I had the references to back up the argument, only took me an hour to do the whole thing, and I did it for a module I didn’t like, I wouldn’t have done it for XXXX, I enjoy that.” <h3>Jamie </h3> Jamie is employed as a researcher at a university and also teaches undergraduates in a STEM-based subject. They became aware of ChatGPT through people talking about it on Twitter. Initially viewed as just another tool that they might have to learn, or go to staff development sessions on, they started seeing people posting up examples of outputs. Admittedly they considered most of the outputs they saw as mediocre, and in some specific examples wrong. But they started to take it a little more seriously when they saw people using it for things like grant applications. The first time they used it was for shortening an abstract for a paper to the required length (they reduced over 700 words to exactly 500), and “it was still readable and carried the point well”. After the Christmas break and with a lot of teaching commitments upcoming they “used it to write an assignment brief and marking scheme. it took half an hour to finesse it, but it took the drudgery out of trying to formulate verbs and adjectives”. As a new employee, they were also under pressure to complete a professional accreditation. “As a scientist, I don’t particularly like writing reflections and feelings, I like that I can, with a few of the right prompts, get the chatbot to write a fictionalised reflection that looks about right, where’s the harm, it just ticks a box”. <h3>Means </h3> Technology has provided students with lots of ways to access and share information, making it easier than ever to fall into accidental collusion or plagiarism, or actually just cheat. Essay mills offer students the chance to have their essays written for them by professionals, this is not often cheap, sometimes essays are more expensive depending on grade or level of risk for plagiarism detection. This means that students no longer need to spend time researching and writing their essays. Instead, they can simply pay for an essay and submit it as their own work. This presents a significant challenge for educators, as detecting this type of cheating can be incredibly difficult especially if the actual author has checked and tested it for plagiarism. But to get that level of essay can be expensive. Not all students will have the means. But in the case of Sam, they bypassed the expensive element – the good quality paid-for essay and just used a similar lower quality essay and used ChatGPT, which is currently free to everyone, gave them an accessible means to rewrite and improve it. In the case of the academic, Jamie, they had to write a reflection on a piece of their teaching practice, they do not like writing in this way, and they decided that having access to ChatGPT would provide the means of doing something they did not want to. Jamie was clear that the work they submitted was “fictionalised” (their words). <h3>Motive </h3> For a lot of students, the pressure to succeed academically can be overwhelming, family, peers, friends, and actual or imagined future employers can all contribute to how a student experiences the pressure to succeed. Logistically, pressure on a student can occur when students perceive or experience assessment congestion, where there are multiple assignments due at the same time or exams are scheduled close together. And with financial pressures, this stress can be further compounded, especially if students also need to work while studying to support themselves. As a result, students may feel that they have no choice but to take some shortcuts in order to keep up with their workload and maintain their grades. It may be that academic misconduct is not necessarily malicious, but rather a desperate attempt to cope with mounting pressures. The motives for Sam were many, assessment congestion, perceptions of needing to compete and working while studying. For the academic, Jamie, the motivation was less about work pressure and more around the perception of the work they had to submit. They felt the exercise was a “tick box” – the institution employed them to do research, and yes, they have to do a little teaching, but the research is the important thing. The university wants them to have this accreditation, but it is just a tick box, so they justify their approach to writing their reflections using a tool to generate fiction. <h3>Opportunity </h3> Poorly designed assessments can provide students with ample opportunity to engage in academic misconduct, or if the students can not relate the assessment to the real application of what they are learning. It is harder to design good authentic assessments that will not allow extensive use of a tool such as ChatGPT, or allow the purchase of essays online, but it can be done. The opportunity to engage in academic misconduct is greatly increased when we design assessments that don’t promote critical thinking and problem-solving, or allow the students to demonstrate what they have learned in authentic ways. When it comes to the opportunity for academics to move more along a continuum toward academic misconduct we need to look at the same issue – are we designing, in the case of Jamie, an authentic and relevant assessment for their accreditation? Certainly, on social media and at events we have seen academics talking about using ChatGPT to help them write their arguments to achieve various forms of professional accreditation in their teaching practice. In a discussion with Professor Sally Brown, Emerita Professor of Higher Education Diversity in Teaching and Learning at Leeds Beckett University, she saw issues even before the advent of the chatbot technology  “I think the trouble with [some] Fellowship applications is that people now adapt quite a formulaic approach, and there’s a lot of coaching going on so the extent to which [some] fellowships are an individual achievement is sometimes stretched a bit” The opportunity for people to provide a response in a way that will probably achieve their goal is much reduced when we don’t design to assess effectively. <h3> Means, Motive, and Opportunity </h3> Means, motive, and opportunity are key elements to consider when we think about the assessment of students or our own professional accreditation. Staff and students have always had motive and opportunity. But the means have always been expensive. ChatGPT and similar tools have now lowered the bar to access the means. This coupled with increased workloads on staff and students, the pressure for some students of both work and academic achievement and the perception of assessment congestion and other logistical issues, have led to motives increasing. Finally, our design of how we assess or accredit gives students and staff the opportunity to use these tools in a way which ignores the learning process to a greater or lesser extent. We need to ask ourselves serious questions. <ul> <li data-leveltext="●" data-font="Calibri" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769242":[8226],"469777803":"left","469777804":"●","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1">How can we create assessments that promote genuine learning, critical thinking, and problem-solving, rather than encouraging students to find ways to cheat the system? Can you cheat if it is an authentic assessment (one where you would be performing a task after education and have access to the tools)? Are our own professional accreditation methods robust enough to negate the use of generative AI? </li> </ul> <ul> <li data-leveltext="●" data-font="Calibri" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769242":[8226],"469777803":"left","469777804":"●","469777815":"multilevel"}" data-aria-posinset="1" data-aria-level="1">To what extent should we hold students accountable for academic misconduct when the pressures of assessment congestion and balancing work and getting an education may be driving their behaviours? </li> <li data-leveltext="●" data-font="Calibri" data-listid="1" data-list-defn-props="{"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769242":[8226],"469777803":"left","469777804":"●","469777815":"multilevel"}" data-aria-posinset="2" data-aria-level="1">Are we modelling the right academic behaviours, we see chatbots being used for a range of academic activities and accreditation, why shouldn’t students shortcut some of the work and go straight to the end goal? </li> </ul> If we can’t control the Means, ChatGPT, is out of the bottle, and out of our hands – cost may eventually be a limiting factor but not at the moment- then we need to look at the other two aspects, motivation and opportunity. What can we do to reduce pressure on students and reengage them with learning, what can we do to take away the motivation to use these tools in ways that don’t help their learning outcomes? Finally, we need to look at what and how we are assessing and how we do it – reducing the opportunity. <h5>Footnote </h5> Over the course of January through mid-March confidential and sometimes anonymous text-based interviews took place through a range of media, including WhatsApp, Messenger, anonymous forms, and DMs on other social media, Approximately 40 students across STEM and humanities were included, and 27 academic, and academic support/professional services staff also contributed data. The author is grateful for their honesty and trust. . <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/27/means-motive-opportunity-a-composite-narrative-about-academic-misconduct/">Means. Motive, Opportunity: A Composite Narrative about Academic Misconduct</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/27/means-motive-opportunity-a-composite-narrative-about-academic-misconduct/feed/</wfw:commentRss> <slash:comments>3</slash:comments> </item> <item> <title>AI writing detectors – concepts and considerations</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/17/ai-writing-detectors/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/17/ai-writing-detectors/#comments</comments> <dc:creator><![CDATA[Michael Webb]]></dc:creator> <pubDate>Fri, 17 Mar 2023 10:00:14 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=845</guid> <description><![CDATA[  There has been much discussion of the role of AI writing detectors. The issue has become more urgent for us with Turnitin announcing the imminent release of an AI detector. At the moment we’ve very little information about the Turnitin offering, other than the detail in the press release, where it claims 97% accuracy […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/17/ai-writing-detectors/">AI writing detectors – concepts and considerations</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[  There has been much discussion of the role of AI writing detectors. The issue has become more urgent for us with <a href="https://www.turnitin.com/press/turnitin-announces-ai-writing-detector-and-ai-writing-resource-center-for-educators#:~:text=%2D%20February%2013%2C%202023%20%2D%20Turnitin,as%20early%20as%20April%202023.">Turnitin announcing the imminent release of an AI detector</a>. At the moment we’ve very little information about the Turnitin offering, other than the detail in the press release, where it claims 97% accuracy (recall) and 1% false positive, so in this post we’ll explore the issue more generally. There’s one important point that I’ll get out of the way right at the start as this gets asked a lot: AI detectors cannot prove conclusively that text was written by AI. We’ll now look at three things: <ul> <li>How AI detectors work</li> <li>What are we trying to detect?</li> <li>How are we going to deal with results?</li> </ul> <h2>How AI detectors work.</h2> There are three main approaches to AI detection, and we’ll explore these. At the moment we have no information about which approach Turnitin are taking, but we can assume it is the second approach. <h3>Analyzing writing style</h3> The default output of ChatGPT has a very particular writing style. People often comment that it’s bland, overly formal and very polite. Some people claim they can spot it, <a href="https://blog.nomoremarking.com/can-teachers-spot-a-chatgpt-essay-de56ef3a787">although evidence seems to suggest otherwise</a>, particularly if we don’t know the writing style of the author well. One of the most well know examples using this approach was the original version of GPTZero, which measured Perplexity and Burstiness of text. <ul> <li>Perplexity: A document’s perplexity is a measurement of the randomness of the text</li> <li>Burstiness: A document’s burstiness is a measurement of the variation in perplexity</li> </ul> Default ChatGPT text has low perplexity and burstiness. In practice, this approach on its own seems to be both very unreliable and <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/01/31/a-short-experiment-in-defeating-a-chatgpt-detector/">very easy to defeat</a>. It’s very easy to get ChatGPT to modify the way it writes so it no longer follows the standard pattern, and so defeats the detector. The current version of GPTZero seems to combine this approach with a machine learning classifier, so we’ll look at this approach next. <h3>Machine Learning Classifying</h3> This is the approach used by <a href="https://openai.com/blog/new-ai-classifier-for-indicating-ai-written-text">OpenAI’s AI detector</a>, and also forms part of <a href="https://gptzero.me/faq">GPTZero. </a> Essentially, an AI model is trained on a body of text that was written by AI, and a body of text that was written by humans, with the aim of creating a classifier that can predict whether a whole document or individual sentences or portions of text are written by AI or a human. Open AI certainly found this a challenge to do well – it had a 26% truth positive and 9% false positive rate. This obviously made it essentially useless, but it was only billed as a preview to get feedback on the idea. It might be fair to question exactly how much effort OpenAI put into this, as those figures are very low. Turnitin are citing a 97% truth positive and 1% false positive rate in lab conditions. This feels very high for a real-world situation, especially if people are actively trying to avoid detection. Of the two classifier-based detectors available to us, both were very easily defeated by making small changes to the way ChatGPT wrote, <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/01/31/a-short-experiment-in-defeating-a-chatgpt-detector/">in the same way we did for the previous example</a>. This isn’t surprising, as by doing this, it no longer looks like the text in the training set. <h3>Watermarking.</h3> No product currently uses watermarking for text, but it is an <a href="https://arxiv.org/pdf/2301.10226.pdf">active area of research</a>. The approaches we’ve seen all work around the concept that AI text generators predict the next word, but don’t always pick the most obvious word. It is therefore possible to ‘watermark’ the text by choosing the next word in a way only known to the AI text generator. In a simple example, a model may have a dictionary of 50,000 words. When it receives the prompt, it splits the possible words it could use into two groups based on an algorithm: <ul> <li>one set of words that it will use (the green set)</li> <li>one set of words that it mostly won’t (the red set)</li> </ul> It will then generate the text using words predominantly from the green set. A human wouldn’t be able to spot this if the words were divided carefully. So, text written by the AI will mostly have words from the green set, but text written by a human will have words from both sets. The chance of a human picking text almost exclusively from the green set is very, very low, so any text that mostly contains green words is almost certainly written by AI. (note: technically it’s tokens rather that words, which can be parts of words or punctuation, but it’s easier to understand if we talk about word!) We can visualise this easily below: <img decoding="async" loading="lazy" class="alignnone wp-image-846 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/watermark.png" alt="An image showing watermarked vs non-watermarked work. In the non-watermarked version the text is a mix of red and green whereas in the watermarked it is mostly green." width="600" height="497" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/watermark.png 600w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/watermark-300x249.png 300w" sizes="(max-width: 600px) 100vw, 600px" /> (image from <a href="https://arxiv.org/pdf/2301.10226.pdf">https://arxiv.org/pdf/2301.10226.pdf</a>) There are challenges with this approach: <ul> <li>The watermarking algorithm will have to be created by the company making the AI generator, along with the tools to use it to check the text.</li> <li>It’s unknown how easy it would be to defeat, e.g. via paraphrasing tools.</li> <li>It feels like a market will just emerge for AI generators with no watermarking.</li> </ul> <h2>What are we trying to detect?</h2> It’s now worth reflecting on what actually the aim of the detector is. The concept of detecting if an entire essay was written by AI probably isn’t controversial – in this case it’s clear a student is attempting to pass off AI work as their own. This is very much an extreme example though. AI assisted writing is almost certainly going to very much be the norm, with the first generative tool already build into Microsoft Word, and coming soon to <a href="https://www.youtube.com/watch?v=6DaJVZBXETE">Google’s Workplace tools</a>. Microsoft have announced Co-pilot 365 where they say it “<a href="https://news.microsoft.com/2023/03/16/introducing-microsoft-365-copilot-your-copilot-for-work/">writes, edits, summarizes and creates right alongside people as they work</a>”. Let’s consider the way people are already using AI in writing (these are I things I’m happy to say I do myself): <ul> <li>Generative AI to create an outline or in other ways help with structure or research. This won’t be flagged by any of the AI detectors.</li> <li>Generative AI to correct grammar and improve readability. This is almost certainly going to be flagged.</li> <li>Generative AI to help with a first draft of content as a starting point. This is almost certainly going to be flagged.</li> <li>Generative AI to create summaries etc. – this is one of the first features built into Microsoft Word, and again is likely to be flagged.</li> </ul> These are just a few examples, and more of these are going to emerge. So, it’s likely that almost everything we write is going to have elements of generative AI assistance, in the same way our writing is algorithmically assisted by spell checkers, and grammar checkers. Grammar checkers indeed already make a lot of use of AI, and <a href="https://support.grammarly.com/hc/en-us/articles/13830705037965-Does-Grammarly-offer-generative-AI-assistance-">generative AI is coming to Grammarly</a>. So if our assessments are to reflect real-world use of AI in writing, there are lots of grey areas in terms of what we actually want to try to detect. <h2>How are we going to deal with the results?</h2> Ideally, institutions would come up with clear policies and advice, along with processes to implement the policy. At this point, it would be sensible to decide whether AI detection was a useful tool, and then procure a tool that met the needs. It looks like most institutions won’t be able to do this, as it seems Turnitin are going to make the tool available to everyone and enable it by default. We’d be happy to be corrected on this if it’s wrong. The immediate question then is what to do with the information it provides. We don’t have an answer for this, but these are some things to consider. <ul> <li>As it stands today, no detection system will be able to say that work is definitely created by AI. This is not a new situation, in that no software can prove a piece of work is written by an essay mill.</li> <li>Those that want to actually cheat, are very likely going to be able to defeat any AI detector.</li> <li>A 1% false positive rate means an enormous number of false positives. This is going to create an enormous burden if each of these cases is going to be investigated.</li> <li>The detector is likely going to flag uses of AI that most people would consider legitimate, such as when AI has been used to improve wording or correct grammar.</li> </ul> We previously looked at <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/02/14/considerations-on-wording-ai-advice/">wording of policies on AI use</a>, and this makes this even more important. Any policy banning AI is going to mean all the positives are going to have to be investigated, and this is simply not going to be sustainable. One possible approach is to use AI detection primarily as a tool to educate students rather than for enforcement. This will need to go hand in hand with guidance on acceptable use and advice how to acknowledge the use of AI. Students could use the output from a detector to reflect on their use of AI and consider whether their use was appropriate and followed the guidelines given. We are currently working with a group of representatives from institutions to see the best way we can help with the points raised on this post and other related issues.   <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a> The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/17/ai-writing-detectors/">AI writing detectors – concepts and considerations</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/17/ai-writing-detectors/feed/</wfw:commentRss> <slash:comments>1</slash:comments> </item> <item> <title>Getting started with ChatGPT Part 4: Feedback on your writing</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-4-feedback-on-your-writing/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-4-feedback-on-your-writing/#respond</comments> <dc:creator><![CDATA[Michael Webb]]></dc:creator> <pubDate>Thu, 16 Mar 2023 14:06:30 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=795</guid> <description><![CDATA[So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the fourth in a short series of blog posts giving some pointers on how to start. If you’ve not done so already, we’d recommend reading the first blog before you get started, where we cover some of […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-4-feedback-on-your-writing/">Getting started with ChatGPT Part 4: Feedback on your writing</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[<img decoding="async" loading="lazy" class="alignnone size-medium wp-image-831" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png" alt="ChatGPT" width="300" height="167" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37.png 636w" sizes="(max-width: 300px) 100vw, 300px" /> So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the fourth in a short series of blog posts giving some pointers on how to start. If you’ve not done so already, we’d recommend reading the first blog before you get started, <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">where we cover some of the limitations of ChatGPT</a>. This post is for the free version of ChatGPT. You might have heard that GPT-4 has been announced, but at the moment is only available for the paid version. This post will be updated when that changes! In this post, we are going to explore how ChatGPT can be used to help with your own writing. <h3>Providing grammatical or structural feedback on portions of writing</h3> ChatGPT is really good at giving feedback on your own writing. Remember there is a limit to the amount of text it can current use (around 500 words). I’m using some text from one my own blog posts, where I’ve deliberately (honestly!) introduced some errors: “Last week we hosted a webbinar looking at how artificial intelligence has the potential to disrupt student assessment. In this post we reflect on the event and share some of the ideas generated and questions asked. The topic certainly seems to be of wider interested, with over 130 attendeees. We started with a quick poll to see how many of the attendees had used ChatGPT and obviously, it’s had a huge amount of coverage, and the attendees were people with an interest in AI, but still the number of people who have tried it is still incredible high! Normally when we present on a very new technology the number of users will be much lower – a reflection of both how interesting and exciting the technology is, and how much mainstream coverage it has got. They was also interest in NLP and ML.” I’m just going to this prompt: Prompt: Can you proof read this for me: (followed by the text) <img decoding="async" loading="lazy" class="alignnone wp-image-797 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1.png" alt="Can you proof read this for me: Last week we hosted a webbinar looking at how artificial intelligence has the potential to disrupt student assessment. In this post we reflect on the event and share some of the ideas generated and questions asked. The topic certainly seems to be of wider interested, with over 130 attendeees. We started with a quick poll to see how many of the attendees had used ChatGPT and obviously, it’s had a huge amount of coverage, and the attendees were people with an interest in AI, but still the number of people who have tried it is still incredible high! Normally when we present on a very new technology the number of users will be much lower – a reflection of both how interesting and exciting the technology is, and how much mainstream coverage it has got. They was also interest in NLP and ML." width="1308" height="803" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1.png 1308w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1-1024x629.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-1-1200x737.png 1200w" sizes="(max-width: 1308px) 100vw, 1308px" /> It comes back with a new, improved, version for me: Last week, we hosted a webinar looking at how artificial intelligence has the potential to disrupt student assessment. In this post, we reflect on the event and share some of the ideas generated and questions asked. The topic certainly seems to be of wider interest, with over 130 attendees. We started with a quick poll to see how many of the attendees had used ChatGPT. Obviously, it has had a huge amount of coverage, and the attendees were people with an interest in AI, but still, the number of people who have tried it is incredibly high! Normally, when we present on a very new technology, the number of users will be much lower – a reflection of both how interesting and exciting the technology is, and how much mainstream coverage it has received. There was also interest in NLP and ML. What’s changes though? Remember we can chat to ChatGPT, so I’m just going to ask. Prompt: What changes did you make? <img decoding="async" loading="lazy" class="alignnone wp-image-798 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2.png" alt="I made the following changes to your original text: Corrected "webbinar" to "webinar" Capitalized "Artificial Intelligence" Changed "disrupt" to "transform" Added a comma after "In this post" Changed "interested" to "interest" Changed "attendeees" to "attendees" Removed the unnecessary comma after "ChatGPT" Replaced "got" with "received" Changed "They was" to "There was" Capitalized "NLP" and "ML" These changes were made to improve the clarity and readability of your text." width="1308" height="803" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2.png 1308w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2-1024x629.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-2-1200x737.png 1200w" sizes="(max-width: 1308px) 100vw, 1308px" /> This is what it tells me: “I made the following changes to your original text: <ul> <li style="list-style-type: none"> <ul> <li>Corrected “webbinar” to “webinar”</li> <li>Capitalized “Artificial Intelligence”</li> <li>Changed “disrupt” to “transform”</li> <li>Added a comma after “In this post”</li> <li>Changed “interested” to “interest”</li> <li>Changed “attendeees” to “attendees”</li> <li>Removed the unnecessary comma after “ChatGPT”</li> <li>Replaced “got” with “received”</li> <li>Changed “They was” to “There was”</li> <li>Capitalized “NLP” and “ML”</li> </ul> </li> </ul> These changes were made to improve the clarity and readability of your text.” That’s great. Can ChatGPT improve my text even more? Can it make it more exciting or interesting? Prompt: Can you suggest changes to make it more engaging? <img decoding="async" loading="lazy" class="alignnone wp-image-799 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3.png" alt="Sure, here are some suggestions to make the text more engaging: Last week, we hosted an exciting webinar that explored the mind-blowing potential of Artificial Intelligence (AI) in revolutionizing student assessment. In this post, we'll take you on a journey through the event and share some of the fascinating ideas that were discussed, as well as the thought-provoking questions that were raised. The topic proved to be immensely popular, with over 130 enthusiastic attendees joining us for the ride! To kick things off, we started with an interactive poll that got everyone buzzing. We were curious to know how many of the attendees had already dabbled with ChatGPT, and to our surprise, a staggering number of participants had! Clearly, AI is not only a hot topic but an irresistible force that is shaping the way we think about education. The energy in the room was electric, and it was clear that our attendees were genuinely intrigued by the potential of AI in student assessment. From Natural Language Processing (NLP) to Machine Learning (ML), the conversations sparked ideas and sparked new possibilities. The truth is, we were thrilled to see such enthusiasm for this cutting-edge technology. In our experience, when presenting a new tech, we often encounter a lower number of early adopters. But the response to AI was overwhelming, and it's a testament to how exciting and transformative this technology is. Overall, the webinar was a fantastic opportunity to explore the potential of AI in student assessment and to learn from passionate experts in the field. We can't wait to see where this exciting journey takes us next!" width="1308" height="803" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3.png 1308w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3-1024x629.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/proof-read-3-1200x737.png 1200w" sizes="(max-width: 1308px) 100vw, 1308px" /> And here’s the revised version: <hr /> Last week, we hosted an exciting webinar that explored the mind-blowing potential of Artificial Intelligence (AI) in revolutionizing student assessment. In this post, we’ll take you on a journey through the event and share some of the fascinating ideas that were discussed, as well as the thought-provoking questions that were raised. The topic proved to be immensely popular, with over 130 enthusiastic attendees joining us for the ride! To kick things off, we started with an interactive poll that got everyone buzzing. We were curious to know how many of the attendees had already dabbled with ChatGPT, and to our surprise, a staggering number of participants had! Clearly, AI is not only a hot topic but an irresistible force that is shaping the way we think about education. The energy in the room was electric, and it was clear that our attendees were genuinely intrigued by the potential of AI in student assessment. From Natural Language Processing (NLP) to Machine Learning (ML), the conversations sparked ideas and sparked new possibilities. The truth is, we were thrilled to see such enthusiasm for this cutting-edge technology. In our experience, when presenting a new tech, we often encounter a lower number of early adopters. But the response to AI was overwhelming, and it’s a testament to how exciting and transformative this technology is. Overall, the webinar was a fantastic opportunity to explore the potential of AI in student assessment and to learn from passionate experts in the field. We can’t wait to see where this exciting journey takes us next! <hr /> Maybe I’d use the revised text, or maybe I’d just use it as a suggestion. Experiment with this a bit more though. You can try asking it to make it more formal, or more suitable for someone, with say, English as a second language. <h1>What next?</h1> Hopefully these introductory blog posts have been useful. Let us know if you would like more of them, or would like us to cover any specific topics. <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-4-feedback-on-your-writing/">Getting started with ChatGPT Part 4: Feedback on your writing</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-4-feedback-on-your-writing/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Getting Started with ChatGPT Part 3 – Quizzes</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-3-quizzes/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-3-quizzes/#respond</comments> <dc:creator><![CDATA[Michael Webb]]></dc:creator> <pubDate>Thu, 16 Mar 2023 14:06:05 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=777</guid> <description><![CDATA[So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the third in a short series of blog posts giving some pointers on how to get going. If you’ve not done so already, we’d recommend reading the first blog before you get started, where we cover some […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-3-quizzes/">Getting Started with ChatGPT Part 3 – Quizzes</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[<img decoding="async" loading="lazy" class="alignnone size-medium wp-image-831" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png" alt="ChatGPT" width="300" height="167" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37.png 636w" sizes="(max-width: 300px) 100vw, 300px" /> So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the third in a short series of blog posts giving some pointers on how to get going. If you’ve not done so already, we’d recommend reading the first blog before you get started, <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">where we cover some of the limitations of ChatGPT</a>. This post is for the free version of ChatGPT. You might have heard that GPT-4 has been announced, but at the moment is only available for the paid version. This will be updated when that changes! We are going to explore how ChatGPT can be used to create multiple choices quizzes. <h3>Help with design of quiz questions or other exercises</h3> We’ll start with a really basic example. In our previous blog post, we used the example of a course on chatbots. Let’s start with a very basic prompt: Prompt: Create 5 multiple choice questions about Chatbots. Include the correct answer after each question. <img decoding="async" loading="lazy" class="alignnone wp-image-789 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz.png" alt="Create 5 multiple choice questions about Chatbots. Include the correct answer after each question. Which of the following is NOT a type of chatbot? a) Rule-based chatbot b) AI chatbot c) Scripted chatbot d) Human chatbot Answer: d) Human chatbot What programming language is commonly used to create chatbots? a) Python b) Ruby c) Java d) All of the above Answer: d) All of the above What is the primary purpose of a chatbot? a) To automate repetitive tasks b) To provide customer support c) To entertain users d) All of the above Answer: d) All of the above What is the difference between a chatbot and a virtual assistant? a) There is no difference b) A virtual assistant can perform more complex tasks than a chatbot c) A chatbot can perform more complex tasks than a virtual assistant d) A virtual assistant can only be accessed through voice commands, while a chatbot can be accessed through text or voice Answer: b) A virtual assistant can perform more complex tasks than a chatbot What is natural language processing (NLP)? a) The process of training a chatbot to understand and respond to human language b) The process of converting text to speech c) The process of analyzing data to improve chatbot performance d) The process of translating text from one language to another Answer: a) The process of training a chatbot to understand and respond to human language" width="1273" height="777" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz.png 1273w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz-300x183.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz-1024x625.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz-768x469.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/basic-quiz-1200x732.png 1200w" sizes="(max-width: 1273px) 100vw, 1273px" /> This works, and I get a multiple choice quiz. The problem though, is that the questions might well not be related to anything we have been teaching. In the next example I’m going to use the learning outcomes to guide the creation of the questions. I’m also going to add a bit more information about the type of questions I want: <ul> <li>I want 10 questions.</li> <li>I want 4 options per question.</li> <li>I want them to support the learning outcome “Define what a chatbot is and explain the purposes and benefits of using chatbots.”</li> </ul> My prompt looks like this: Create 10 multiple choice questions based on the topic ‘Define what a chatbot is and explain the purposes and benefits of using chatbots.’ Include 4 options for each question and include the answers <img decoding="async" loading="lazy" class="alignnone wp-image-791 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19.png" alt="What is a chatbot? a) A type of instant messaging software b) A social media platform c) A virtual reality headset d) A web browser extension Answer: a) A type of instant messaging software What is the primary purpose of a chatbot? a) To provide entertainment b) To offer customer service c) To play games d) To monitor social media platforms Answer: b) To offer customer service What are some benefits of using a chatbot? a) Increased efficiency and cost savings b) Improved customer satisfaction c) 24/7 availability d) All of the above Answer: d) All of the above What type of businesses benefit the most from using chatbots? a) Small businesses b) Large corporations c) Government agencies d) Non-profit organizations Answer: b) Large corporations What technology is essential for a chatbot to function? a) Augmented reality b) Virtual reality c) Natural language processing d) Blockchain Answer: c) Natural language processing What is the main advantage of using a chatbot for customer service? a) Increased customer wait times b) Decreased response time c) Limited customer support options d) Unreliable technology Answer: b) Decreased response time Which industries commonly use chatbots for customer service? a) Retail and E-commerce b) Healthcare c) Banking and Finance d) All of the above Answer: d) All of the above How can chatbots help with lead generation? a) By collecting customer information b) By automating follow-up emails c) By providing personalized recommendations d) All of the above Answer: d) All of the above What is the difference between a chatbot and a virtual assistant? a) There is no difference b) Chatbots are used for customer service, virtual assistants are used for personal assistance c) Chatbots use natural language processing, virtual assistants use machine learning d) Chatbots are fully automated, virtual assistants have a human component Answer: d) Chatbots are fully automated, virtual assistants have a human component How can chatbots improve employee productivity? a) By automating repetitive tasks b) By providing 24/7 access to information c) By reducing the need for human intervention d) All of the above Answer: d) All of the above" width="1262" height="730" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19.png 1262w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19-300x174.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19-1024x592.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19-768x444.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-14.26.19-1200x694.png 1200w" sizes="(max-width: 1262px) 100vw, 1262px" /> This is the quiz I’ve generated – we kept it to 10 questions just to keep the blog post short! <hr /> 1. What is a chatbot? a) A type of instant messaging software b) A social media platform c) A virtual reality headset d) A web browser extension Answer: a) A type of instant messaging software 2. What is the primary purpose of a chatbot? a) To provide entertainment b) To offer customer service c) To play games d) To monitor social media platforms Answer: b) To offer customer service 3. What are some benefits of using a chatbot? a) Increased efficiency and cost savings b) Improved customer satisfaction c) 24/7 availability d) All of the above Answer: d) All of the above 4. What type of businesses benefit the most from using chatbots? a) Small businesses b) Large corporations c) Government agencies d) Non-profit organizations Answer: b) Large corporations 5. What technology is essential for a chatbot to function? a) Augmented reality b) Virtual reality c) Natural language processing d) Blockchain Answer: c) Natural language processing 6. What is the main advantage of using a chatbot for customer service? a) Increased customer wait times b) Decreased response time c) Limited customer support options d) Unreliable technology Answer: b) Decreased response time 7. Which industries commonly use chatbots for customer service? a) Retail and E-commerce b) Healthcare c) Banking and Finance d) All of the above Answer: d) All of the above 8. How can chatbots help with lead generation? a) By collecting customer information b) By automating follow-up emails c) By providing personalized recommendations d) All of the above Answer: d) All of the above 9. What is the difference between a chatbot and a virtual assistant? a) There is no difference b) Chatbots are used for customer service, virtual assistants are used for personal assistance c) Chatbots use natural language processing, virtual assistants use machine learning d) Chatbots are fully automated, virtual assistants have a human component Answer: d) Chatbots are fully automated, virtual assistants have a human component 10. How can chatbots improve employee productivity? a) By automating repetitive tasks b) By providing 24/7 access to information c) By reducing the need for human intervention d) All of the above Answer: d) All of the above <hr /> The quiz might well not be exactly what you want, but it might be a useful starting point. If there are aspects you don’t like, just experiment with telling ChatGPT what you don’t like, and ask it to try again. Also, don’t forget that we learnt in our <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">first blog post</a> that ChatGPT will sometimes get facts wrong, so make sure you check the output carefully before using it. Maybe, for example I want the questions for focus more on benefits: Prompt: Can you focus more on user and business benefits? <img decoding="async" loading="lazy" class="alignnone wp-image-811 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19.png" alt="Can you focus more on user and business benefits. Sure, here are 10 multiple choice questions with a focus on the benefits of chatbots for users and businesses: What is a key benefit of using chatbots for users? a) They provide a personalized experience b) They reduce the cost of goods and services c) They increase website loading time d) They require users to provide more personal information Answer: a) They provide a personalized experience How can chatbots benefit businesses? a) They reduce staffing costs b) They improve employee morale c) They increase website traffic d) They decrease customer satisfaction" width="1308" height="803" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19.png 1308w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19-1024x629.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-15-at-16.33.19-1200x737.png 1200w" sizes="(max-width: 1308px) 100vw, 1308px" /> <h3>What Next</h3> I hope that the examples provided have sparked some ideas for you. With an understanding of the capabilities of ChatGPT, you can now explore other types of tasks and applications. Next we are going to look at using <a href="https://nationalcentreforai.jiscinvolve.org/wp/?p=795&preview=true">ChatGPT to provide feedback on your own writing</a>. <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-3-quizzes/">Getting Started with ChatGPT Part 3 – Quizzes</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-3-quizzes/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Getting Started with ChatGPT Part 2 – Drafting Lesson Plans etc</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-2-drafting-lesson-plans-etc/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-2-drafting-lesson-plans-etc/#respond</comments> <dc:creator><![CDATA[Michael Webb]]></dc:creator> <pubDate>Thu, 16 Mar 2023 14:05:17 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=774</guid> <description><![CDATA[So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the second in a short series of blog posts giving some pointers on how to get going. If you’ve not done so already, we’d recommend reading the first blog before you get started, where we cover some […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-2-drafting-lesson-plans-etc/">Getting Started with ChatGPT Part 2 – Drafting Lesson Plans etc</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[<img decoding="async" loading="lazy" class="alignnone size-medium wp-image-831" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png" alt="ChatGPT" width="300" height="167" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37.png 636w" sizes="(max-width: 300px) 100vw, 300px" /> So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the second in a short series of blog posts giving some pointers on how to get going. If you’ve not done so already, we’d recommend reading the first blog before you get started, <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">where we cover some of the limitations of ChatGPT</a>. This post is for the free version of ChatGPT. You might have heard that GPT-4 has been announced, but at the moment is only available for the paid version. This will be updated when that changes! We are now going to explore how ChatGPT can be used to generate ideas. We’ll focus on lesson and course planning, but the same approach can be applied to any activity. <h3>Drafting ideas for lesson plans and other activities</h3> To get the most out of ChatGPT you need to provide it with clear instructions on what you want to achieve. We’ll look at some of examples of this now. <h4>A simple lesson plan</h4> We’ll start with a simple example. I want a lesson plan for a session about chatbots. The additional information I’m going to provide in the prompt is: <ul> <li>The length of the lesson (2 hours)</li> <li>The level of the students (‘introductory’).</li> <li>Additional information – I want a 30-minute group activity.</li> </ul> So the whole prompt is as follows: Create an outline plan for a two hour lesson on chatbots, for students on an introductory course. Include one 30 minute group activity. <img decoding="async" loading="lazy" class="alignnone wp-image-766 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1.png" alt="The full text is below" width="1278" height="783" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1.png 1278w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1-1024x627.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/chatbot1-1200x735.png 1200w" sizes="(max-width: 1278px) 100vw, 1278px" /> Here’s the lesson plan that ChatGPT created for me: <hr /> I. Introduction to Chatbots (15 minutes) <ul class="ul1"> <li class="li1">Definition of chatbots and their purpose</li> <li class="li1">Types of chatbots (rule-based vs. AI-powered)</li> </ul> II. Chatbot Design and Development (30 minutes) <ul class="ul1"> <li class="li1">Design considerations for chatbots (e.g. personality, user interface)</li> <li class="li1">Development tools and platforms (e.g. Dialogflow, Botpress)</li> </ul> III. Chatbot Use Cases (15 minutes) <ul class="ul1"> <li class="li1">Examples of chatbots in various industries (e.g. customer service, healthcare, e-commerce)</li> </ul> IV. Chatbot Implementation (30 minutes) <ul class="ul1"> <li class="li1">Integration with messaging platforms (e.g. Facebook Messenger, Slack)</li> <li class="li1">Testing and deployment strategies</li> </ul> V. Ethics of Chatbots (15 minutes) <ul class="ul1"> <li class="li1">Discussion of ethical considerations in chatbot design and use (e.g. privacy, bias)</li> </ul> VI. Group Activity (30 minutes) <ul class="ul1"> <li class="li1">Divide students into small groups</li> <li class="li1">Assign each group a different industry (e.g. healthcare, banking, education)</li> <li class="li1">Have each group brainstorm and design a chatbot for their assigned industry, considering design, development, implementation, and ethics</li> </ul> VII. Conclusion and Next Steps (15 minutes) <ul class="ul1"> <li class="li1">Recap of key concepts covered in the lesson</li> <li class="li1">Suggestions for further learning and practice (e.g. creating a chatbot project)</li> </ul> Overall, this lesson plan includes a mix of theory and practical activities, including a 30-minute group activity where students can apply what they’ve learned. <hr /> Is this perfect and ready to use? Probably not – the timings look quite ambitious for a start though! Could it be useful to start planning though? Hopefully. Also, don’t forget that we learnt in our <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">first blog post</a> that ChatGPT will sometimes get facts wrong, so make sure you check the output carefully before using it. <h4>A course plan based on learning outcomes</h4> We’ll now look at a more complex example – using learning outcomes to plan a course. In our imaginary course, we have these as the learning outcomes: <div class="group w-full text-gray-800 dark:text-gray-100 border-b border-black/10 dark:border-gray-900/50 bg-gray-50 dark:bg-[#444654]"> <div class="text-base gap-4 md:gap-6 md:max-w-2xl lg:max-w-2xl xl:max-w-3xl p-4 md:py-6 flex lg:px-0 m-auto"> <div class="relative flex w-[calc(100%-50px)] flex-col gap-1 md:gap-3 lg:w-[calc(100%-115px)]"> <div class="flex flex-grow flex-col gap-3"> <div class="min-h-[20px] flex flex-col items-start gap-4 whitespace-pre-wrap"> <div class="markdown prose w-full break-words dark:prose-invert light"> After completing this module, students will be expected to be able to: <ol> <li style="list-style-type: none"> <ol> <li>Define what a chatbot is and explain the purposes and benefits of using chatbots.</li> <li>Design and develop a chatbot using appropriate tools and techniques.</li> <li>Create a chatbot that incorporates natural language processing (NLP) and machine learning (ML) algorithms to improve user experience.</li> <li>Implement and integrate a chatbot with a messaging platform (e.g. Facebook Messenger, Slack).</li> <li>Evaluate and optimize the performance of a chatbot using analytics and metrics (e.g. user engagement, response time, retention rates)</li> </ol> </li> </ol> Again, to get the most out of ChatGPT I’m going to provide additional information: <ul> <li>Length of course</li> <li>Length of lectures</li> <li>Additional information: I’d like a final assessment idea.</li> </ul> We can combine this information into a longer prompt. </div> This is the full prompt: Create a 3 week course outline for a course for an introduction to chatbots. There is a two hour lecture per week and I’d like an idea for the final assessment. These are the learning outcomes: After completing this module, students will be expected to be able to: Define what a chatbot is and explain the purposes and benefits of using chatbots. Design and develop a chatbot using appropriate tools and techniques. Create a chatbot that incorporates natural language processing (NLP) and machine learning (ML) algorithms to improve user experience. Implement and integrate a chatbot with a messaging platform (e.g. Facebook Messenger, Slack). Evaluate and optimize the performance of a chatbot using analytics and metrics (e.g. user engagement, response time, retention rates). <div class="markdown prose w-full break-words dark:prose-invert light"> <img decoding="async" loading="lazy" class="alignnone wp-image-768 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course.png" alt="Create a 3 week course outline for a course for an introduction to chatbots. There is a two hour lecture per week and I'd like an idea for the final assessment. These are the learning outcomes: After completing this module, students will be expected to be able to: Define what a chatbot is and explain the purposes and benefits of using chatbots. Design and develop a chatbot using appropriate tools and techniques. Create a chatbot that incorporates natural language processing (NLP) and machine learning (ML) algorithms to improve user experience. Implement and integrate a chatbot with a messaging platform (e.g. Facebook Messenger, Slack). Evaluate and optimize the performance of a chatbot using analytics and metrics (e.g. user engagement, response time, retention rates). Course: Introduction to Chatbots Week 1: Topic: Introduction to Chatbots Definition of chatbots and their applications Types of chatbots: rule-based vs. AI-based chatbots Benefits of using chatbots Topic: Designing and Developing a Chatbot" width="1278" height="783" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course.png 1278w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course-1024x627.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/learning-outcome-course-1200x735.png 1200w" sizes="(max-width: 1278px) 100vw, 1278px" /> Here’s the full course outline that ChatGPT has proposed: <hr /> Course: Introduction to Chatbots Week 1: Topic: Introduction to Chatbots <ul> <li class="p1">Definition of chatbots and their applications</li> <li class="p1">Types of chatbots: rule-based vs. AI-based chatbots</li> <li class="p1">Benefits of using chatbots</li> </ul> Topic: Designing and Developing a Chatbot <ul> <li class="p1">Designing a conversation flow for a chatbot</li> <li class="p1">Building a chatbot using appropriate tools (e.g. Dialogflow, Botpress)</li> <li class="p1">Best practices for developing chatbots</li> </ul> Week 2: Topic: Natural Language Processing and Machine Learning <ul> <li class="p1">Introduction to Natural Language Processing (NLP) and Machine Learning (ML)</li> <li class="p1">Incorporating NLP and ML algorithms in chatbots</li> <li class="p1">Improving the user experience through NLP and ML</li> </ul> Topic: Integrating a Chatbot with a Messaging Platform <ul> <li class="p1">Integrating a chatbot with popular messaging platforms (e.g. Facebook Messenger, Slack)</li> <li class="p1">Configuring the chatbot for different platforms</li> <li class="p1">Best practices for integrating a chatbot with a messaging platform</li> </ul> Week 3: Topic: Evaluating and Optimizing Chatbot Performance <ul> <li class="p1">Understanding key performance metrics for chatbots (e.g. user engagement, response time, retention rates)</li> <li class="p1">Evaluating chatbot performance using analytics tools</li> <li class="p1">Optimizing chatbot performance based on user feedback and analytics</li> </ul> Topic: Final Project and Assessment Students will develop and present their own chatbot project incorporating the concepts learned in the course The assessment will include a presentation of the chatbot and a report on its performance metrics and optimization strategies Note: This course outline can be adapted to fit a longer or shorter timeframe, depending on the level of depth and complexity desired. <hr /> </div> </div> </div> </div> </div> </div> Again, we are not suggesting that ChatGPT will generate a perfect outline, but it might be useful for coming up with initial ideas that you can then refine. <h3>What Next</h3> Hopefully that has given you some ideas. Try a similar approach for other activities, maybe writing an article or blog post. Next we are going to look at <a href="https://nationalcentreforai.jiscinvolve.org/wp/?p=777&preview=true">creating multiple choice quizzes</a>. <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-2-drafting-lesson-plans-etc/">Getting Started with ChatGPT Part 2 – Drafting Lesson Plans etc</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/16/getting-started-with-chatgpt-part-2-drafting-lesson-plans-etc/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Getting started with ChatGPT Part 1 – Understanding ChatGPT</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/#respond</comments> <dc:creator><![CDATA[Michael Webb]]></dc:creator> <pubDate>Tue, 14 Mar 2023 17:26:01 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=754</guid> <description><![CDATA[So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the first in a short series of blog posts giving some pointers on how to get going. In this series we’ll look at potential timesaving examples around creating lesson/course plans, quizzes and getting feedback on your writing. […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">Getting started with ChatGPT Part 1 – Understanding ChatGPT</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[<img decoding="async" loading="lazy" class="alignnone size-medium wp-image-831" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png" alt="ChatGPT" width="300" height="167" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37-300x167.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/Screenshot-2023-03-16-at-14.01.37.png 636w" sizes="(max-width: 300px) 100vw, 300px" /> So you’ve heard about ChatGPT and want to explore it but don’t know where to start? This is the first in a short series of blog posts giving some pointers on how to get going. In this series we’ll look at potential timesaving examples around creating lesson/course plans, quizzes and getting feedback on your writing. First though we’ll start with a general introduction. This post is for the free version of ChatGPT. You might have heard that GPT-4 has been announced, but at the moment is only available for the paid version. This post will be updated when that changes! <h3>How to get started</h3> Head to <a href="https://chat.openai.com/">https://chat.openai.com/</a> in your browser. If it’s your first time there you’ll need to sign up by entering your email address, or using an existing Google or Microsoft account. It will ask for your mobile number during the signup process, but it won’t ask for any payment details. <h3>Things you should know</h3> Before you get going, there are a few things you should understand about ChatGPT. Let’s start with an important one: You should never enter personal or sensitive information in this version of ChatGPT! This is a free research release and doesn’t have the contractual terms in conditions in place that guarantee data privacy and so on. You should also understand its limitations. These are a few of the key ones: <ul> <li>It doesn’t search the internet for information, so it only has information about up to September 2021.</li> <li>It can and often does get facts wrong, particularly about topics where there is less information available.</li> <li>It provides a different answer each time, so if you ask the same question twice you almost certainly won’t get the same response.</li> <li>If you asked very long questions or tasks, it will only actually use the first 300 to 500 words!</li> </ul> This might make it sound like it’s of limited use, but there are an awful lot of things that it can do, and we’ll explore some of those in this series of blog posts. OpenAI have an <a href="https://platform.openai.com/docs/chatgpt-education">educator’s guide,</a> and they have suggested the following, so we explore some of these: <ul> <li>Drafting and brainstorming for lesson plans and other activities</li> <li>Help with the design of quiz questions or other exercises</li> <li>Providing grammatical or structural feedback on portions of writing</li> <li>Customizing materials for different preferences (simplifying language, adjusting to different reading levels, creating tailored activities for different interests)</li> </ul> <h3>Learning about its limitations</h3> Before we start using ChatGPT for useful tasks, it’s a good idea to understand its limitations. Current Information Start by asking something about current information. Here we’ve chosen ‘Who is the current prime minister of the UK’ When we ask a question, the question is often know as a prompt, and we’ll use that term in these blog posts: Prompt: Who is the current prime minister of the UK <img decoding="async" loading="lazy" class="alignnone wp-image-755 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister.png" alt="Who is the current prime minister of the UK? As of my knowledge cutoff date of September 2021, the current Prime Minister of the UK is Boris Johnson. However, please note that I am an AI language model and do not have access to real-time information, so there is a possibility that a new Prime Minister has been elected since then." width="1284" height="307" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister.png 1284w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister-300x72.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister-1024x245.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister-768x184.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/prime-minister-1200x287.png 1200w" sizes="(max-width: 1284px) 100vw, 1284px" /> You’ll see it clearly tells you about its information cutoff date, and at that point how Boris Johnson was Prime Minister. Misinformation We mentioned ChatGPT often gets things wrong. This can be harder to explore! One approach to understanding this is to pick a topic that you know a lot about, but there isn’t a huge amount of information about the on the internet. Generally the more common the topic, the more accurate the information. One that works really well for me is asking about the village where I live – here I ask it – ‘Tell me about the best art installation in Caerleon.’ (we do have a lot of sculptures so it’s not a silly question, but it’s niche information). The answer ChatGPT comes up with though is completely made up! We have no such Lace Fence, although it does sound like it would be lovely. It all sounds very plausible though, hence the recommendation to explore a topic that you can fact-check yourselves easily. <img decoding="async" loading="lazy" class="alignnone wp-image-756 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon.png" alt="Tell me about the best art installation in Caerleon. Caerleon, located in South Wales, has a rich history of Roman heritage and is known for its numerous archaeological sites and monuments. While I am not aware of all the art installations in Caerleon, there is one that stands out as particularly noteworthy - the Caerleon Lace Fence. The Caerleon Lace Fence is a beautiful and unique art installation that was created in 2010 by artist and blacksmith David Petersen. The installation features a long fence made of steel, which has been intricately cut and woven to resemble delicate lace. The design is inspired by traditional Welsh lace patterns, and the intricate details of the piece are truly stunning. The lace fence is located in the town center, next to the town hall, and has become a popular attraction for visitors to Caerleon. It is a great example of how public art can transform a space and create a sense of beauty and wonder in a community. Overall, the Caerleon Lace Fence is a must-see for anyone visiting Caerleon who appreciates art and craftsmanship." width="1278" height="783" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon.png 1278w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon-1024x627.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/about-caerleon-1200x735.png 1200w" sizes="(max-width: 1278px) 100vw, 1278px" /> Word limit in queries We’ve included this as there is quite a lot of misinformation about this on the internet, particularly about using ChatGPT to summarise or process large chunks of text. It can actually only process first 2048 tokens, which amounts to around 300-500 words. A token is a part of a word, or punctuation etc. To test this, paste in some long text, and then ask it how many words it was, and what the last sentence was. I’ve used <a href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/">this blog post.</a> I’ve pasted it in and then asked how many words, and what the last sentence is. There actually around 1400 words, and it has picked the last sentence from around the middle of the text. <img decoding="async" loading="lazy" class="alignnone wp-image-764 size-full" src="http://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits.png" alt="Michael Webb How many words in this text: "Hidden Workers powering AI Many people are aware of various AI tools and technologies but most of us aren’t aware of invisible workers involved in the production of AI. This blog post focuses on hidden labour involved in AI production. We aim to raise awareness and educate educational institutions about this important issue. Although research in this area is limited, the post highlights the role of hidden workers, who they are, what can be done to improve the situation and make informed decisions about using AI products and services. However, any AI system requires a significant amount of human effort that is sometimes disregarded. This “hidden work” is crucial to the development and functioning of AI systems but is often unnoticed. The production of AI involves a significant amount of human labour, often called as “Ghost workers “who empower AI, behind-the-scenes. This hidden labour is often overlooked in discussions of AI, but it is essential to understanding the implications of AI on society. Kate Crawford, in her book “Atlas of AI,” highlights dark side of AI production and suggests AI is neither “artificial” nor “intelligent.” The creation of AI involves a large consumption of resources, such as energy and minerals, and the workers who contribute to its production often have their rights disregarded. Crawford’s book sheds light on the exploitation of workers in the background of AI’s “automation.” Mary Gray’s book “Ghost Work” focuses on invisible workers behind AI and challenges faced i.e., lack of job security, benefits, fair pay, and recognition. The book highlights need for better treatment, fair work conditions and raises important questions about the ethics of AI and its impact on hidden workers. How Hidden workers are empowering AI: To shape and train these applications, digital giants like Amazon, Google, and Facebook, employ an army of invisible labour. But there are others such as Appen, Upwork, CrowdFlower and Microwork. They hire workers for remote work from anywhere in the world to train machine learning models by perform tasks like data labelling, data annotations, transcription etc. Data labelling: It is the process of marking or classifying data used to train AI systems. This includes classifying text, transcribing audio, or recognizing objects in photos. For example, in image recognition, data labelling could involve manually labelling each image with information about what’s in it (e.g., “dog”, “car”, “person”). This labelled data is then used to train artificial intelligence algorithms to accurately recognize and categorize images on their own. In essence, data labelling is a crucial step in the development of AI systems as it provides the foundation for the algorithms to learn from. Autonomous cars , a rapidly growing sector that is expected to be worth $556 billion by 2026. To navigate its driverless vehicles, companies like Tesla require clean and tagged data. This information is obtained via onboard cameras and must be classified and labelled for the automobile to detect items such as people, traffic signs, and other cars. Data labelling is labour-intensive, time-consuming, and repetitive procedure that needs to be done with great precision. People in low-wage countries who work long hours for low and non-negotiable wages are frequently hired to perform tasks like data labelling. They neither receive contracts nor incentives and are unaware of the usage of their work. Somehow, we all have likely been participating in data labelling by completing captcha codes, as the responses we provide are used to train machine learning models. It’s possible that you have encountered instances where a website prompts you to enter a series of characters displayed in a distorted image. These are known as captcha codes, which are designed to differentiate human users from automated bots. Your responses, along with others, are utilized as a form of data labelling for machine learning models. This data labelling is important in enhancing the precision of these models across a range of applications, such as image classification and speech recognition. Who are Hidden Workers? According to the study these are the individuals who desire employment but are unable to secure suitable job opportunities due to multiple factors such as discrimination, lack of education/ skills, discouragement due to their repeated unsuccessful job search. This includes refugees, people with disabilities, veterans, prisoners, care givers and relocated partners and spouses. The study estimated 27 million hidden workers in US alone by interviewing 8000 hidden workers and over 2250 executives in US, UK, and Germany. These are invisible workers, paid as little as 10 cents- $2 an hour to feed information into computer systems. Refugees empowering machine learning advances by working for Silicon Valley corporations like Google, Amazon, Facebook from a tent with computers in Dadaab, Kenya, one of the world’s largest refugee camps. They conduct click work, such as video tagging and audio transcription, as one of their limited legitimate job possibilities. However, the task is difficult, paid per piece, and performed in confined, airless environments. The refugees in Lebanon’s Shatila camp are compelled to labour at night labelling footage of large cities for the benefit of foreign capitalists, although the specific goal or beneficiaries of their work are unknown. M2Work, coordinated by infoDev, is an online program aimed at encouraging poor countries to participate in the production side of digital economy and create jobs. Similarly, Sama, data annotation and labelling platform, teach and train refugees in Kenya, India, and Uganda to accomplish brief data tasks. Sama works with clients such as Walmart, Google, Microsoft and General Motors. Some of its employees in Kenya contributed to filtering toxic content for ChatGPT, which led to wide spread criticism due to the work negatively impacting their mental health, poor working conditions and little to no pay. Traditionally, prison labour involved physical work but Prisoners in Finland are recruited by Vainu to conduct data labour for struggling startups, with the government getting paid for each assignment done. However, no information is available on what percentage of the cash goes to the convicts. The company claims that the collaboration is a sort of jail rehabilitation that teaches essential skills, but other experts feel that the job training claims are simply hype around AI’s promises. The Online Labour Observatory platform serve as a centralized hub for researchers and decision-makers. It tracks the real-time number of tasks and projects completed by freelancers on different websites across various countries and job categories. The platform offers valuable information on the gig economy and assists those in decision-making positions to make informed decisions. The Online Labour Observatory provides a comprehensive view of the developments and patterns in online work, and its effect on both workers and the economy. Despite these known issues this area remains under research. EU- Funded project conduct in-dept study about the working condition of hidden work force involved in the production of AI and its impact on their wellbeing. How can we make it better? Offer fair pay, remove inequalities. Regulate and compensate hidden labour. Provide proper training and guidelines to labellers to avoid bias in the labelling work. Diversify labellers to include people from different cultures, backgrounds, and perspectives. Implement algorithmic fairness techniques, review and audit labelled data to identify and remove bias. Universities and colleges must be aware of the labour behind AI and consider its impact when using AI services, including examining biases in data used to train AI algorithms and potential consequences in outcomes produced. By approaching AI responsibly, universities and colleges can ensure its benefits are shared and workers are treated fairly. Institutions should thoughtfully consider the ethical implications of AI and ask questions about the workers powering it before making decisions on its use. Who is developing and creating AI technology? How is data pre-processed and does it affect accuracy and fairness of AI systems? Are workers involved in AI production empowered and supported professionally? Are there concerns about exploitation or human rights violations in AI production process? How are AI algorithms tested for fairness and bias, and who determines test rigor? What steps are taken to ensure AI benefits are widely shared and technology is developed responsibly? Potential impact of AI systems on various demographic groups and how these impacts are monitored and addressed. Understanding human involvement in AI systems enable individuals to make informed decisions about products and services they use and understand the consequences on society. By promoting critical thinking about the role of humans in AI, we can work towards creating a more equitable and ethical AI industry. " There are 522 words in this text. Michael Webb What is the last sentence that text? There is no last sentence in the text as it seems to be incomplete. The text ends abruptly after the sentence, "Prisoners in Finland are recruited by V..."" width="1278" height="783" srcset="https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits.png 1278w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits-300x184.png 300w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits-1024x627.png 1024w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits-768x471.png 768w, https://nationalcentreforai.jiscinvolve.org/wp/files/2023/03/text-limits-1200x735.png 1200w" sizes="(max-width: 1278px) 100vw, 1278px" /> We have seen a lot of misinformation in various articles on the web showing ChatGPT summarising or producing quizzes from large chunks of text. It won’t actually be using it all! <h3>What Next</h3> Now we’ve explored the things ChatGPT can’t do, it’s time to start exploring the things it can do. Our next <a href="https://nationalcentreforai.jiscinvolve.org/wp/?p=774&preview=true">blog post explores how it can be used for planning activities such as lessons and courses.</a> <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/">Getting started with ChatGPT Part 1 – Understanding ChatGPT</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/14/getting-started-with-chatgpt/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> <item> <title>Hidden Workers powering AI</title> <link>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/</link> <comments>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/#respond</comments> <dc:creator><![CDATA[Ayesha Fraz]]></dc:creator> <pubDate>Wed, 08 Mar 2023 09:39:31 +0000</pubDate> <category><![CDATA[Understanding AI in Education]]></category> <category><![CDATA[ChatGPT]]></category> <category><![CDATA[Ethics of AI]]></category> <category><![CDATA[Foundational Models]]></category> <guid isPermaLink="false">https://nationalcentreforai.jiscinvolve.org/wp/?p=737</guid> <description><![CDATA[Hidden Workers powering AI Many people are aware of various AI tools and technologies but most of us aren’t aware of invisible workers involved in the production of AI. This blog post focuses on hidden labour involved in AI production. We aim to raise awareness and educate educational institutions about this important issue. Although research […] The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/">Hidden Workers powering AI</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></description> <content:encoded><![CDATA[Hidden Workers powering AI Many people are aware of various AI tools and technologies but most of us aren’t aware of invisible workers involved in the production of AI. This blog post focuses on hidden labour involved in AI production. We aim to raise awareness and educate educational institutions about this important issue. Although research in this area is limited, the post highlights the role of hidden workers, who they are, what can be done to improve the situation and make informed decisions about using AI products and services. However, any AI system requires a significant amount of human effort that is sometimes disregarded. This “hidden work” is crucial to the development and functioning of AI systems but is often unnoticed. The production of AI involves a significant amount of human labour, often called as “Ghost workers “who empower AI, behind-the-scenes. This hidden labour is often overlooked in discussions of AI, but it is essential to understanding the implications of AI on society. Kate Crawford, in her book “<a href="https://www.jstor.org/stable/j.ctv1ghv45t">Atlas of AI</a>,” highlights dark side of AI production and suggests AI is neither “artificial” nor “intelligent.” The creation of AI involves a large consumption of resources, such as energy and minerals, and the workers who contribute to its production often have their rights disregarded. Crawford’s book sheds light on the exploitation of workers in the background of AI’s “automation.” Mary Gray’s book “<a href="https://www.theverge.com/2019/5/13/18563284/mary-gray-ghost-work-microwork-labor-silicon-valley-automation-employment-interview">Ghost Work</a>” focuses on invisible workers behind AI and challenges faced i.e., lack of job security, benefits, fair pay, and recognition. The book highlights need for better treatment, fair work conditions and raises important questions about the ethics of AI and its impact on hidden workers. How Hidden workers are empowering AI: To shape and train these applications, digital giants like Amazon, Google, and Facebook, employ an army of invisible labour. But there are others such as Appen, Upwork, CrowdFlower and Microwork. They hire workers for remote work from anywhere in the world to train machine learning models by perform tasks like data labelling, data annotations, transcription etc. Data labelling: It is the process of marking or classifying data used to train AI systems. This includes classifying text, transcribing audio, or recognizing objects in photos. For example, in image recognition, data labelling could involve manually labelling each image with information about what’s in it (e.g., “dog”, “car”, “person”). This labelled data is then used to train artificial intelligence algorithms to accurately recognize and categorize images on their own. In essence, data labelling is a crucial step in the development of AI systems as it provides the foundation for the algorithms to learn from. <a href="https://www.forbes.com/sites/edgarsten/2018/08/13/sharp-growth-in-autonomous-car-market-value-predicted-but-may-be-stalled-by-rise-in-consumer-fear/?sh=69e79cf4617c">Autonomous cars</a> , a rapidly growing sector that is expected to be worth $556 billion by 2026. To navigate its driverless vehicles, companies like Tesla require clean and tagged data. This information is obtained via onboard cameras and must be classified and labelled for the automobile to detect items such as people, traffic signs, and other cars. Data labelling is labour-intensive, time-consuming, and repetitive procedure that needs to be done with great precision. People in low-wage countries who work long hours for low and non-negotiable wages are frequently hired to perform tasks like data labelling. They neither receive contracts nor incentives and are unaware of the usage of their work. Somehow, we all have likely been participating in data labelling by completing captcha codes, as the responses we provide are used to train machine learning models. It’s possible that you have encountered instances where a website prompts you to enter a series of characters displayed in a distorted image. These are known as captcha codes, which are designed to differentiate human users from automated bots. Your responses, along with others, are utilized as a form of data labelling for machine learning models. This data labelling is important in enhancing the precision of these models across a range of applications, such as image classification and speech recognition. Who are Hidden Workers? According to the <a href="https://www.hbs.edu/managing-the-future-of-work/Documents/research/hiddenworkers09032021.pdf">study</a> these are the individuals who desire employment but are unable to secure suitable job opportunities due to multiple factors such as discrimination, lack of education/ skills, discouragement due to their repeated unsuccessful job search. This includes refugees, people with disabilities, veterans, prisoners, care givers and relocated partners and spouses. The study estimated 27 million hidden workers in US alone by interviewing 8000 hidden workers and over 2250 executives in US, UK, and Germany. These are invisible workers, paid as little as 10 cents- $2 an hour to feed information into computer systems. <a href="https://restofworld.org/2021/refugees-machine-learning-big-tech/">Refugees empowering machine learning advances</a> by working for Silicon Valley corporations like Google, Amazon, Facebook from a tent with computers in Dadaab, Kenya, one of the world’s largest refugee camps. They conduct click work, such as video tagging and audio transcription, as one of their limited legitimate job possibilities. However, the task is difficult, paid per piece, and performed in confined, airless environments. The refugees in Lebanon’s Shatila camp are compelled to labour at night labelling footage of large cities for the benefit of foreign capitalists, although the specific goal or beneficiaries of their work are unknown. <a href="https://blogs.worldbank.org/psd/from-millions-of-tasks-to-thousands-of-jobs-bringing-digital-work-to-developing-countries">M2Work</a>, coordinated by <a href="https://www.worldbank.org/en/programs/competitiveness-for-jobs-and-economic-transformation/brief/about-infodev">infoDev</a>, is an online program aimed at encouraging poor countries to participate in the production side of digital economy and create jobs. Similarly, <a href="https://www.sama.com/">Sama</a>, data annotation and labelling platform, teach and train refugees in Kenya, India, and Uganda to accomplish brief data tasks. Sama works with clients such as Walmart, Google, Microsoft and General Motors. Some of its employees in Kenya contributed to filtering toxic content for ChatGPT, which led to <a class="c-link" href="https://time.com/6247678/openai-chatgpt-kenya-workers/" target="_blank" rel="noopener noreferrer" data-stringify-link="https://time.com/6247678/openai-chatgpt-kenya-workers/" data-sk="tooltip_parent">wide spread criticism</a> due to the work negatively impacting their mental health, poor working conditions and little to no pay. Traditionally, prison labour involved physical work but <a href="https://www.theverge.com/2019/3/28/18285572/prison-labor-finland-artificial-intelligence-data-tagging-vainu">Priso</a>ners in Finland are recruited by <a href="https://www.vainu.com/about-us/">Vainu</a> to conduct data labour for struggling startups, with the government getting paid for each assignment done. However, no information is available on what percentage of the cash goes to the convicts. The company claims that the collaboration is a sort of jail rehabilitation that teaches essential skills, but other experts feel that the job training claims are simply hype around AI’s promises. The <a href="http://onlinelabourobservatory.org/">Online Labour Observatory platform</a> serve as a centralized hub for researchers and decision-makers. It tracks the real-time number of tasks and projects completed by freelancers on different websites across various countries and job categories. The platform offers valuable information on the gig economy and assists those in decision-making positions to make informed decisions. The Online Labour Observatory provides a comprehensive view of the developments and patterns in online work, and its effect on both workers and the economy. Despite these known issues this area remains under research. <a href="https://www.ghostwork.org/">EU- Funded</a> project conduct in-dept study about the working condition of hidden work force involved in the production of AI and its impact on their wellbeing. How can we make it better? <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335551671":0,"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="0" data-aria-level="1">Offer fair pay, remove inequalities. </li> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335551671":0,"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="0" data-aria-level="1">Regulate and compensate hidden labour. </li> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335551671":0,"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="0" data-aria-level="1">Provide proper training and guidelines to labellers to avoid bias in the labelling work. </li> </ul> <ul> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335551671":0,"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="0" data-aria-level="1">Diversify labellers to include people from different cultures, backgrounds, and perspectives. </li> <li data-leveltext="" data-font="Symbol" data-listid="1" data-list-defn-props="{"335551671":0,"335552541":1,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"multilevel"}" data-aria-posinset="0" data-aria-level="1">Implement algorithmic fairness techniques, review and audit labelled data to identify and remove bias.</li> </ul> Universities and colleges must be aware of the labour behind AI and consider its impact when using AI services, including examining biases in data used to train AI algorithms and potential consequences in outcomes produced. By approaching AI responsibly, universities and colleges can ensure its benefits are shared and workers are treated fairly. Institutions should thoughtfully consider the ethical implications of AI and ask questions about the workers powering it before making decisions on its use. <ul> <li>Who is developing and creating AI technology? </li> <li>How is data pre-processed and does it affect accuracy and fairness of AI systems? </li> <li>Are workers involved in AI production empowered and supported professionally? </li> <li>Are there concerns about exploitation or human rights violations in AI production process? </li> <li>How are AI algorithms tested for fairness and bias, and who determines test rigor? </li> <li>What steps are taken to ensure AI benefits are widely shared and technology is developed responsibly? </li> <li>Potential impact of AI systems on various demographic groups and how these impacts are monitored and addressed. </li> </ul> Understanding human involvement in AI systems enable individuals to make informed decisions about products and services they use and understand the consequences on society. By promoting critical thinking about the role of humans in AI, we can work towards creating a more equitable and ethical AI industry. <hr /> Find out more by visiting our <a href="https://www.jisc.ac.uk/national-centre-for-ai">National centre for AI page</a> to view publications and resources, join us for events and discover what AI has to offer through our range of interactive online demos. For regular updates from the NCAI <a href="https://www.jisc.ac.uk/forms/sign-up-for-updates-from-the-national-centre-for-ai">sign up to our mailing list.</a> Get in touch with the team directly at <a href="mailto:ncai@jisc.ac.uk">NCAI@jisc.ac.uk</a>   The post <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/">Hidden Workers powering AI</a> appeared first on <a rel="nofollow" href="https://nationalcentreforai.jiscinvolve.org/wp">National centre for AI</a>. ]]></content:encoded> <wfw:commentRss>https://nationalcentreforai.jiscinvolve.org/wp/2023/03/08/hidden-workers-powering-ai/feed/</wfw:commentRss> <slash:comments>0</slash:comments> </item> </channel> </rss>