Excellent points and thank you Mike for bringing up the topic of AI tools that can write university level essays. I am fascinated by the potential impact this technology could have on higher education. I appreciate your argument that these tools should be used to enhance pedagogy, rather than accelerating cheating and fraud. Riseam Sharples is a ‘niche’ property firm that acts specifically in relation to conveyancing matters; we are not a general practitioner. Therefore the quality of our work and expertise is something that cannot be matched by general practices, automated conveyancing providers or for that matter some of the larger, corporate law firms.

It’s interesting to see how the GPT-3 Transformer AI program was able to generate a compelling essay on the topic of “learning styles”. The essay provides a well-organized and evidence-based argument, despite being generated by an AI language model. I particularly like how it explores the idea that learning styles are not fixed, and can be influenced by personal and environmental factors. A s the world’s first nuclear power station, Sellafield in Cumbria is used to being an industry leader and it is now establishing itself as a leader in project procurement too. Three years into a new approach by Sellafield Ltd to do things differently, the work by the Programme and Project Partners (PPP) – KBR, Jacobs, Morgan Sindall and Doosan – is already paying dividends and attracting wider industry attention.

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Thank you for this! I think you’ve really helped frame an important discussion about using LLM transformers to help students learn. However, I am curious about what sort of essays or writing in general we as educators could assign that a GPT-3 could not eventually answer? The visit also highlighted the vital work Dstl does in bringing terrorists to justice, with careful evidence based thinking and thorough testing to gather evidence that holds people who commit atrocities to account.

Sharples describes it as an enterprise model that is consistent with the government’s Construction Playbook and the ICE’s Project 13 principles. “It’s an early adopter of those approaches,” he adds. The razor-sharp Japanese stainless steel blade will make short work of peeling everything from the hard skin of butternut squash to the soft skin of courgettes, swivelling as it goes to minimise waste. It will even effortlessly peel tomatoes and just about anything else that needs peeling. And its cleverly designed handle means it’s equally comfortable to use for both right- and left-handed users. The entire “student essay” was written by a Transformer AI program, GPT-3. I gave it the prompt “The construct of ‘learning styles’ is problematic because” and it produced the rest, including headings and references. Plagiarism software will not detect essays written by Transformers, because the text is generated, not copied. A Google search of the essay shows that each sentence is original. Sharple also has a built-in eye and blemish remover to dig out the unwanted bits from whatever you’re peeling.

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Every time you open or close the Sharple, a ceramic ball inside the safety cover sharpens and hones the blade so it’s always in tip-top peeling condition – and the cover protects the blade, and you, from harm when it’s not in use. It is one thing getting the procurement model right, but the behaviours and values have to be right too,” says Sharples. The essay is well-organized and flows smoothly. It makes a clear argument and supports it with evidence from research.With three years down and another 17 to go, it is still early days, but Sharples says the PPP is already outperforming the contract baseline, which is something Sellafield has never achieved before. Note its reference for ‘Dunn and Dunn (1997).’ There is a journal titled Research in Education, but no issue 7(2) in 1997. Dunn and Dunn did publish on learning styles, but not in that journal. GPT-3 has fashioned a plausible-looking, but fake reference. It has also invented a fictitious research study from Dunn and Dunn to critique learning styles. For more on AI Transformers and computers as story generators, see Mike Sharples and Rafael Pérez y Pérez, Story Machines: How Computers Have Become Creative Writers, to be published by Routledge in July 2022. Professor Sarah Sharples is a Professor of Human Factors in the Department of Mechanical, Materials and Manufacturing Engineering and Pro-Vice Chancellor for Equality, Diversity and Inclusion at the University of Nottingham. She completed her PhD in 1999 and has been a researcher, research manager or grant holder on a number of industrial, government and EU funded projects, including a long term programme of research for Network Rail examining implications, design and implementation of novel interfaces for railway control and use of rail simulation for human factors research. She is a CI in the Horizon Digital Economy Research Institute and Co-Director of the Horizon Doctoral Training Centre. She also leads a national Network Plus: Connected Everything, which brings together communities of computer scientists, manufacturing, design, business and engineering specialists to examine digital manufacturing. She is on the Science Advisory Council for the Department for Transport and was appointed as a council member for the Engineering and Physical Sciences Research Council in early 2018. She works in the domains of transport, healthcare and manufacturing, and is a Chartered Ergonomist and Human Factors Specialist. Her main areas of interest and expertise are Human-Computer Interaction, cognitive ergonomics and development of quantitative and qualitative research methodologies for examination of interaction with innovative technologies in complex systems. She was President of the Chartered Institute of Ergonomics and Human Factors from 2015-2016, and co-editor of the leading ergonomics/human factors text, Evaluation of Human Work, 4th edition (2015).