Staying Human in the Age of AI. With Peter Davidson

Staying Human in the Age of AI. With Peter Davidson

I'm joined by Peter Davidson from Zayed University to discuss the 2023 article by David Brooks [https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html]: [https://www.nytimes.com/2023/02/02/opinion/ai-human-education.html] In the Age of AI, Major in Being Human, which claims: "AI will force us humans to double down on those talents and skills that only humans possess. The most important thing about Al may be that it shows us what it can't do, and so reveals who we are and what we have to offer." What might these ‘human’ skills and attributes be that we will need in the age of AI? In this podcast we will try to identify these human skills and attributes (what might be termed ‘capacities’) that have become more essential to us as humans, as AI becomes embedded in teaching and learning, and in the workplace. It is these human capacities, Peter argues, that will become increasingly important for our us and our students as the impact of AI grows. See the full list of Essential Human Skills [https://drive.google.com/file/d/1wxkigiThOQ-zYc8fl2bdmw1UQYetbtJL/view?usp=drive_link]. Guest bio Peter Davidson teaches Business Communication and Technical Communication at Zayed University in Dubai, having previously taught in New Zealand, Japan, the UK, and Turkey. He is currently interested in exploring how Generative AI is impacting language teaching and assessment practices, and how it can be leveraged to improve the educational experiences of students. Peter is presenting at the upcoming BALEAP PIM [https://www.baleap.org/events/upcoming-events/profile/online-pim-eap-and-the-academy-in-the-age-of-genai-implications-for-practices-and-practitioners] at Leeds on June 19th. Further Reading The framing of autonomy, mastery and purpose that's referred to in the discussion was popularised by Daniel Pink in his 2012 book Drive: the surprising truth about what motivates us. This draws on the work of Richard Ryan and Edward Deci, and Self-Determination Theory. Anderson, D.J., Rainie, L, & Anderson, J. (2026). Human Wisdom for the Age of AI: A Field Guide to Cultivating Essential Skills. Elon University and AAC&U. Anderson, J. & Rainie, L. (2025). Being Human in 2035: How Are We Changing in the Age of AI? Imagining the Digital Future Center. Gerlich, M. A. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign. https://curriculumredesign.org/wp-content/uploads/AIED-Book-Excerpt-CCR.pdf Pink, D. H. (2012). Drive: the surprising truth about what motivates us. Edinburgh: Canongate. Postman, N., & Weingartner, C. (1969). Teaching as a Subversive Activity. New York: Delacorte Press. Raman, A. (2024). Investing in Human Skills in the Age of AI. LinkedinLearning, California, USA. Ryan, R and Deci, E. (2000). Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychological Association. 55 (1). Available at: DOI: 10.1037110003-066X.55.1.68

Lead us not into temptation: notes from the StudentXGenAI Project. With Stephen Gow

Last year HEPI reported 95% of students were using gen AI, but recent research from Stephen Gow and Sam Illingworth casts doubt on this figure. Today I’m joined by Stephen to talk through some of the key finding of his Leverhume Trust funded study that draws data from over 7,000 participants. What do students really think about gen AI in higher education, and how should this shape the way we treat it in the curriculum? Guest Bio Dr Stephen Gow was the Leverhulme Research Fellow at the Department of Learning and Teaching Enhancement (DLTE) at Edinburgh Napier University. During this role he led the Student Experiences on Generative AI Project (StudentXGenAI [https://www.studentxgenai.co.uk/]), this project carried out the StudentXGenAI Survey with a response rate of over 7000 students at UK institutions and interviews with students across the UK in addition to integrating GenAI into the research process. He is an expert on academic integrity, assessment and GenAI, and the Chair of the Northern Academic Integrity Forum. He is now associate staff with Department of Education, University of York and available for consultation and research projects related to GenAI in education. He can be contacted at stephen.gow@york.ac.uk [stephen.gow@york.ac.uk] or via Linkedin: Stephen Gow | LinkedIn [https://www.linkedin.com/in/stephen-gow-77556a73/]  Further reading Chung, J., Henderson, M., Slade, C., Liang, Y., Pepperell, N., Corbin, T., Walton, J., Yu, AS., Bearman, M., Buckingham Shum, S., Fawns, T., McCluskey, T., McLean, J., Oberg, G., Seligmann, A., Shibani, A., Bakharia, A., Lim, LA., Matthews, KE. (2026). The use and usefulness of GenAI in higher education: Student experience and perspectives. Computers and Education Open, Available at: doi:  10.1016/j.caeo.2026.100347 [https://doi.org/10.1016/j.caeo.2026.100347]. Gow S, Illingworth S (2026), "Dynamic tensions: an AI-assisted critical scoping review of university students' qualitative experiences of GenAI". Artificial Intelligence in Education, Vol. 2 No. 1 pp. 67–89, Available at: doi: 10.1108/AIIE-06-2025-0151 [https://doi.org/10.1108/AIIE-06-2025-0151]  Gow, S. and Illingworth, S. (2026) “It is a temptation to get it to do the work…” – student experiences of GenAI in UK universities. 09 Apr 2026. Advance HE. [Online]. Available at: https://www.advance-he.ac.uk/news-and-views/it-temptation-get-it-do-work-student-experiences-genai-uk-universities [https://www.advance-he.ac.uk/news-and-views/it-temptation-get-it-do-work-student-experiences-genai-uk-universities] [Accessed 20 April 2026]. The Castlereagh Statement is available at: https://castlereagh.ai/ Timecodes 00:00 Welcome and guest intro 01:12 Duolingo streak talk 06:20 Tech backlash and attention 10:46 Generative AI literacy risks 19:23 Introducing StudentXGenAI 22:31 Survey design and access 24:54 Who uses GenAI and why 27:23 Productivity versus learning 31:42 Massification and student pressures 34:26 Research goals and policy impact 34:48 Survey design choices 35:52 UK vs Australia findings 36:47 Why usage rates differ 38:15 Regulation and risk 39:07 Learning tool doubts 41:11 Assessment scales explained 45:42 Trust and honesty data 49:44 Fairness and incentives 56:55 Exams after COVID 01:03:59 Data privacy and costs 01:07:31 Future research

Has machine translation killed conversation? With James Lamont and Jiaoyue Chen

Language students using machine translation has certainly raised lots of questions for those of us teaching English for Academic Purposes over the past few years. But most of the conversation has been around its impact on written compositions. A new study by Lamont and Cirocki looks at how and why it's changing the way international students interact verbally with each other and their teachers.  We're joined today by James Lamont, the lead author of the study, to dig into the data and talk about the implications for the language classroom. What steps do teachers need to take to enable learning to actually take place? Speaker bios Jiaoyue Chen is an Academic Practice Adviser at the University of York, where she supports colleagues’ professional journey through the PGCAP programme, York Professional and Academic Development scheme recognition, and the York SoTL network. With a background in Applied Linguistics, she worked as a Lecturer in English Language and Education at Huazhong University of Science and Technology in China. She still returns to this area of research with great interest, but also seeks to disentangle the nuanced relationship between SoTL and formal pedagogical research to better support student learning.  James Lamont is an Associate Lecturer at the University of York in the Department of Education and the School of Business and Society, where he supports student skills development. His research interests are student use of technology and developing working relationships across student cohorts.  Further reading Lamont, J., & Cirocki, A. (2025). Talking to algorithms, not students: Students’ and lecturers’ perceptions of machine translation in academic discussion. The JALT CALL Journal, 21(3), 103256. https://doi.org/10.29140/jaltcall.v21n3.103256 [https://doi.org/10.29140/jaltcall.v21n3.103256]  Timecodes 00:00 Intro to MT in the classroom 01:19 James Lamont and Jiaoyue Chen 03:08 Talking to algorithms  04:58 Groves and Mund’s previous work on MT 04:58 Real time translation in class 07:36 Language acquisition concerns 12:19 Tasks versus learning goals 16:15 The impact of MT on non-language learning 20:42 Overreliance and false confidence 26:00 Accuracy culture and dependency 29:48 Policy gaps and overreliance 31:04 Setting classroom expectations 32:57 Phone boundaries and culture 34:15 Structured tech use phases 35:23 Proficiency gaps and support 38:06 Accents, idioms and listening load 43:24 Anxiety comfort and safe seminars 48:50 Privacy, recording and shame 51:48 Student buy-in and agency 54:56 Ideal classroom and future research 58:03 Final Takeaways And Paper Credit

When does offloading become outsourcing? With Paul Kirschner

Are smartphones and laptops enabling or impeding students’ progress in class? On the plus side they give access to a wealth of resources, but they can also kill interaction and provide any number of distractions. Today we dig into the research on devices in class with educational psychologist Paul Kirschner. Paul also clears up the confusion around cognitive offloading, what it really means and what’s actually happening when we use AI. Is it really just another tool like a calculator? We talk about these and a range of other learning tech topics, including future research directions for multimedia assessment, and what we can reasonably ask of practitioner research. Check out Paul's Substack via the link below, and the posts for today's conversation on phones in the classroom [https://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/] and cognitive offloading vs outsourcing [https://paulkirschner173727.substack.com/p/offloading-no-outsourcing]. https://substack.com/@paulkirschner173727 [https://substack.com/@paulkirschner173727]  Guest bio Paul Kirschner is one of the most influential voices in the national and international education debate. For decades, he has done research on and has been translating scientific insights about learning, memory and teaching into clear applications for education. Paul is professor emeritus at the Open University of the Netherlands, honorary doctor (Doctor Honoris Causa) at the University of Oulu (Finland), visiting professor at the Thomas More University of Applied Sciences in Flanders and owner of the educational consultancy kirschner-ED. Previously, he worked as a teacher of Science, Chemistry and Mathematics in secondary education and was active in school boards and participation councils of both secondary and secondary education. He is regarded worldwide as a leading expert in his field and has published approximately 450 scientific articles, in addition to several hundred popular science contributions and blogs for teachers and school leaders. In addition, he is the first or co-author of several influential and widely read books, including Instructional Illusions, How Learning Happens, How Teaching Happens, Evidence-Informed Learning Design, Ten Steps to Complex Learning, Developing Curriculum for Deep Thinking and Urban Legends about Learning and Education. Further reading  Sungu, A., Choudhury, P. K., & Bjerre-Nielsen, A. (2025). Removing phones from classrooms improves academic performance. Available at SSRN: ssrn.com/abstract=5370727 or dx.doi.org/10.2139/ssrn.5370727

When is it ok to pull the plug? Reimagining the post GPT classroom. With Lily Abadal and Nidhi Sachdeva

Phil is joined by Lily Abadal and Nidhi Sachdeva to talk about reducing device reliance, rebuilding in-class writing, and using technology with clear pedagogical intent. Lily describes redesigning written assessments by breaking the traditional term paper into smaller in-class, long-form writing components, encouraging device-free classroom culture without heavy policing, and emphasizing silence, reflection, discussion, and mentorship.  Nidhi brings research from cognitive science to bear on tech-related concerns like distraction, cognitive load, and outsourcing thinking. She guides us through the limitations of flipped learning, and why we might want to bring some COVID legacy independent tasks back into the classroom.  We also lay out the stall for why personalised feedback, workbooks and visible teacher investment in students are things worth hanging on to. Speaker bios Lily Abadal is an Assistant Professor of Instruction in the Philosophy Department at the University of South Florida - St. Petersburg. She specializes in normative ethics, applied ethics, moral psychology, and philosophy of psychology. Her recent interests include moral injury, character formation, and AI Ethics. She explores all things through a Neo-Aristotelian lens.  She’s interested in helping mission-centered schools design pedagogical strategies, develop integrity-centered policies, re-imagine assessments that align with their values, and encourage genuine character formation in the age of AI. Lily writes about all of the above on her Substack, Wisdom in the Machine Age: https://substack.com/@wisdominthemachineage [https://substack.com/@wisdominthemachineage]  You can also find more information on her website: https://www.drlilyabadal.com/ [https://www.drlilyabadal.com/] Nidhi Sachdeva is a leading Canadian Science of Learning researcher, specializing in evidence-informed learning design, post-secondary education, and educational technology. She teaches online learning and microlearning from a cognitive science perspective at OISE’s Department of Curriculum, Teaching, and Learning at the University of Toronto. A recognized expert in translating educational research into practical classroom strategies, she has been featured on numerous podcasts and currently serves as Chair of researchED Toronto. Check out Nidhi’s Science of Learning Substack [https://scienceoflearning.substack.com/].  Listen to Nidhi’s previous TELSIG podcast appearance [https://baleaptelsig.podbean.com/e/nidhi-sachdeva-enhancing-learning-from-cognitive-load-to-effective-reading-practices/] on education myth busting.  Further reading Abadal, L.M. (2025) Only the Humanities can save the university from AI. [Online]. Public Discourse. Available at:  https://www.thepublicdiscourse.com/2025/07/98429/ [https://www.thepublicdiscourse.com/2025/07/98429/] [Accessed 23 January 2026].  Kirschner, P. (2025), When phones go out the window, learning comes in the door. [Online]. Krischnered. Available at: http://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/ [http://www.kirschnered.nl/2025/11/01/when-phones-go-out-the-window-learning-comes-in-the-door/] [Accessed 23 January 2026]. Oakley, B., Johnston, M. Chen, K, Jung, E. and Sejnowski, T.  (2025). The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI. [Preprint]. Available at: https://arxiv.org/abs/2506.11015 Timecodes 00:00 Intro  02:34 Lily’s background: ChatGPT forces a rethink of assessment 04:08 Rebuilding the term paper: in-class slow writing and device-free culture 08:29 Nidhi’s stance: thoughtful EdTech (not a tech war) 12:30 Offloading vs outsourcing: what cognitive science says about AI/tech 15:45 What is the classroom for now? Mentorship, practice, and attention 18:29 Lily’s new class design: handouts, recall, annotation, discussion 30:03 Lessons learned from flipped teaching 35:40 The practicalities of unplugging in Higher Ed 37:21 Lily’s case against ChatGPT in Philosophy 44:46 Distinguishing EdTech from AI and social media 53:48 In-class writing as an alternative to exams 55:04 Workbooks and human feedback 01:02:02 Beyond essays: low-Stakes Mastery Quizzes & Assessment for Learning 01:03:25 Why Handwriting Works: Engagement, Cognitive Science & Iterating as a Teacher