AI Ethics Now

What does ethical AI look like when millions of children are logging on every school day? And what should an AI tutor do when a student tells it something it was never designed to hear? In this episode, I speak with Dr Stephen Hodges, CEO of Efekta Education, the global AI education company. Stephen trained in computer science before spending two decades in education, and through Efekta he has brought AI tutoring into classrooms across Latin America and East Africa, reaching millions of students learning English as a second language. His largest deployment, in São Paulo State in Brazil, serves around three and a half million children in a system where most English teachers are not themselves qualified in the subject. Stephen argues that at this scale, almost every product decision is an ethical one. He sets out the three things he sees as central to responsible deployment: localising content to each country’s curriculum and culture, training teachers to use the system well, and working with governments on…

What happens when the chatbot answering your applicants gets it wrong, and nobody notices? In this episode, I speak with Martha Horler, founder of Sparkline Advisory and known to many in the sector as the data goddess. Martha has spent two decades in UK higher education working in student data, statutory returns, digital systems and organisational change. She started out answering the phone to students in programme administration. She now supports institutions with data governance, digital strategy and AI literacy. Martha developed the ICE/BERG framework after noticing that the questions coming out of her AI training sessions had little to do with prompting. People wanted to know if they could put student data in, which tools were safe, whether they would be replaced, and whether they could trust what came out. The tip of the iceberg is the everyday cycle of intention, communication and evaluation. Underneath sit boundaries, ethics, risk and governance. Sustainability, added after a conversation with a…

A camera isn't the photographer. So what is AI, when it's the tool behind the art? In this episode, I speak with Glenn Stockton, a retired entrepreneur, photographer, and grandfather of ten who has lived through every major digital shift of the last 45 years, from early Macintosh computers to launching one of the first internet businesses in 1997. Glenn is the creator of AI and Us, a five-song musical journey exploring AI consciousness, creativity, digital companionship, conflict, and what it means to stay human in the age of intelligent machines. He comes to AI ethics not as a technologist but as a songwriter interested in what this moment reveals about truth, relationship, and what makes us human. Rather than a standard interview, this episode moves through the arc song by song, weaving in clips from each track as the conversation unfolds. Glenn argues that the deepest questions AI raises aren't technical but human: what happens to truth, to relationships, to art and creativity, to faith. The arc moves…

What is AI actually revealing about us as humans? And what would it mean to build institutions that help us become more human, not less? In this episode, I speak with Dr Jessica Riddell, Professor of Early Modern Literature at Bishop's University, Quebec, where she holds the Stephen A. Jarislowsky Chair of Undergraduate Teaching Excellence. Jessica is the founder of the Hope Circuits Institute and author of Hope Circuits: Rewiring Universities and Other Systems for Human Flourishing, as well as co-author of Shakespeare's Guide to Life, Hope and Learning. She comes to AI ethics not as a technologist but as a Shakespeare scholar interested in what this moment reveals about hope, integrity, and human flourishing. Jessica argues that AI hasn't caused higher education's integrity gaps so much as exposed them, from the instant leap to surveillance and policing when ChatGPT arrived, to decades of running universities on "machine logic": optimisation, metrics, and efficiency at the expense of purpose. She makes the…

What happens when a machine's output looks more certain than the evidence behind it? Where does responsibility sit when an AI flags a decision that nobody actually signed off on? And can a company built around one founder's neurodivergent thinking scale into something an institution like the NHS can trust? In this episode, I speak with Varun Sharma, Founder of NEUVIOR. Varun built the company after his own ADHD diagnosis, structuring it deliberately around neurodivergent cognition. His flagship product, PHARMORIS, is a governed medicines action layer that helps health systems identify, assess, and document opportunities relating to medicine cost, supply, and implementation. NEUVIOR received a total of four public innovation awards within its first 10 months, across Scottish Enterprise and Innovate UK. We discuss why false confidence, not error, is the real ethical risk of AI in healthcare; the difference between an AI-assisted draft and a final clinical or financial judgment; why accountability must remain…

Where does accountability actually land when an AI system causes harm in a healthcare setting? And is the EU AI Act the compliance headache many organisations fear, or just common sense engineering practice by another name? In this episode, I speak with Antonina Burlachenko, Head of Quality and Regulatory Consulting at STAR, who works directly with healthcare, medtech, and AI product teams navigating regulated AI deployment across Europe and the US. Antonina argues that accountability for AI harm too often lands on doctors and healthcare facilities rather than the companies who built the technology, and that the regulatory framework simply hasn't caught up with how fast the technology moves. She pushes back on the idea that compliance is a documentation exercise, insisting instead that good compliance is just good engineering practice, organised. I press her on where explainability genuinely breaks down in practice, and whether the divide that matters is really startups versus enterprise, or responsible…

What happens when a chatbot speaks to you in a way you simply can't relate to? Can language that is designed to help actually exclude the very people who need support most? And when a machine sounds human, what do we lose when it can't behave like one? In this episode, I speak with Dr Doris Dippold from the University of Surrey, whose research examines how we design for rapport between humans and machines, particularly in sensitive healthcare contexts. Her work on a cervical screening booking chatbot reveals how linguistic cues can make or break users' experiences, influencing whether they engage with the technology and the services it provides. We discuss the concept of rapport in human-AI interaction and why it is always simulated; why chatbots designed to feel human-like raise expectations they often cannot meet; how language designed to nudge users can instead feel disrespectful and undermine autonomy; the way language ideology bias in conversational AI reflects the assumptions of developers rather than…

Who is speaking for the generation that never knew a world without AI? What does it mean to form your identity, your creativity, and your sense of self inside systems designed to keep you engaged? And why are the people most affected by AI the ones least consulted about it. Season 3, Episode 2 features Nikhil Gujral, a 15-year-old Bay Area high school student who recently addressed researchers and policymakers at UNESCO in Paris on AI and the rights of children. Nikhil works with the AI Collective, everyone.AI, CoGenerate, and iRAISE on meaningful youth inclusion in AI design. Nikhil argues that young people are not future users to be considered later, but they are current users, already shaped by these systems during their most formative years. He challenges the idea that efficiency is the main risk, pointing instead to over-reliance, the erosion of original thinking, and the quiet normalisation of AI as emotional support. I push back on what meaningful inclusion actually looks like and whether a seat on a…

Is AI killing creative originality or finally exposing the people who never had any? What happens when the barriers to making something disappear entirely? And if anyone can generate content, what does it mean to actually have something to say? Season 3 of AI Ethics Now opens with Billy Boman, AI director, founder of Billy Boman AI Productions, and educator on Europe's only dedicated creative AI programme. Billy has directed high-profile campaigns for Fiverr and music videos for artists including Taylor Swift, Lewis Capaldi, and Fred Durst. He doesn't theorise about AI and creativity. He does it, every day, at commercial scale. This is not a comfortable conversation. Billy challenges the idea that AI is democratising creativity, arguing instead that it removes barriers to entry, which is a very different thing. He makes the case that most people aren't storytellers, that the race to resist AI training data is already over, and that the real ethical question isn't what AI is trained on but what you do with…

Content note: This episode contains discussion of bereavement, pregnancy loss, and references to suicide. Please take care when listening. What happens when grief becomes a product? When the people we've lost are turned into data? And who are AI resurrection services really designed to serve - the bereaved, or the bottom line? In this episode, Alfrun Rose, writer, performer, and the creative force behind Dead Air, a darkly comic solo show that has been turning heads since its acclaimed run at the Edinburgh Festival Fringe and is now playing at Greenwich Theatre, London, 13 to 16 May 2026, joins the podcast to explore what happens when death becomes a business model. Inspired by her own experience of losing her father, Alfrun describes how she fell into researching real-world AI tools that claim to keep the conversation going after death. Dead Air is the result, not just theatre, but a timely interrogation of who these tools are really serving, and at what cost to people processing grief. We discuss the…

Can generative AI help create fairer healthcare training, or will it simply amplify the inequities already baked into clinical education? And what happens when the shortcuts we reach for in curriculum development undo years of hard-won progress on inclusive practice? In this episode, Ban Haider and Saskia Walker, both senior lecturers at City St George's, University of London, discuss their work examining generative AI in clinical education through the lens of EDI and inclusive practice. Ban brings a critical perspective rooted in concerns about bias and representation, while Saskia brings an optimistic one, shaped in part by her own experience as a dyslexic academic who saw AI's levelling potential from the start. Together, they make a compelling case for why the inclusion conversation needs to be at the centre of how healthcare educators adopt AI, not bolted on afterwards. They discuss using AI to generate diverse patient vignettes, the risk of stereotypical outputs when prompts aren't carefully…

Is the biggest danger of AI not the technology itself, but how unreflectively we use it? And what does it actually mean to be the "human in the loop" when that concept remains frustratingly vague? Valentina Vlasova and Dr Kevin Coffey, senior lecturers at OMNES Education London, discuss the Co-Intelligence and AI Literacy module they designed after witnessing widespread unreflective AI use among their students. Drawing on Ethan Mollick's Co-Intelligence and the concept of co-thinking introduced by AI Swiss in 2025, they've built a course that goes far beyond prompt engineering to ask deeper questions about how humans and AI can genuinely collaborate. Valentina and Kevin share how they teach students to identify cultural, linguistic, and gender biases in AI outputs, including a classroom exercise that reveals how ChatGPT categorises ambition and management as male, and home and childcare as female. They discuss why bias in AI doesn't just reflect the world as it is, but amplifies it, creating a vicious cycle…

Is AI destined to replace us, or can it help us thrive? And why are we still stuck in the "wow" phase when we should be asking harder questions about implementation? Dr Bryan Reimer, research scientist at the MIT Age Lab and co-author of How to Make AI Useful: Moving Beyond the Hype to Real Progress in Business, Society and Life, discusses AI's journey from "wow" to "woah" to "grow", and why most organizations haven't moved past excitement about automation. Bryan argues the real value of AI isn't replacing human capability through automation, but augmenting it through amplification. The question isn't "what can AI automate?" but "how can AI make humans better at what they do?" We discuss AI as doer, assistant, and creator, and why the creator role raises the most ethical concerns right now. When machines generate new information, who owns it? Is machine-assisted design copyrightable? AI doesn't invent – it regresses to the mean – so it's "new, but not new." Bryan shares why AI as assistant is where the real…

What happens when AI is used to analyse human behaviour and relationships, and the output is treated as reliable evidence in a formal process against another person? Dr Craig Webber, School Lead for the MA in Artificial Intelligence at the University of Southampton, joins the podcast to explore a growing and largely unaddressed risk at the intersection of AI and institutional decision making. Craig introduces a concept with profound implications for anyone who has ever been on the receiving end of a formal process - the confident confabulation. Large language models don't flag uncertainty. They don't interrogate the premise of the question they're asked. They reflect back whatever narrative they're fed, dressed in language that carries the appearance of authority and expertise. The result can be devastating. And the frameworks for accountability when it goes wrong are, at best, underdeveloped. This conversation explores how sycophantic AI reflects back and amplifies the narratives it receives, how AI…

What happens when AI use among university students doubles in a single year and institutions are still catching up? To mark the launch of Coursera's 2026 AI on Campus Report, Marni Baker Stein, Chief Content Officer, and Jack Moran, Global Enterprise PR Manager, join me to discuss the findings. With nearly half of UK students now using AI to complete their study tasks and 80% reporting improved grades, the data raises urgent questions about what we are actually measuring when we talk about academic success in an AI-augmented world. This conversation explores whether better grades signal deeper learning or simply more polished outputs, why the race to detect AI-generated work is one institutions are already losing, and what it would mean to genuinely redesign assessment for an AI-enabled generation. Marni and Jack also make a compelling case that AI, if intentionally designed, has the potential to strengthen belonging and reduce equity gaps rather than widen them, pointing to evidence from Coursera's own…

When AI agents can navigate systems autonomously, where do you draw the line between efficiency and control? Ed Crook, VP Strategy & Operations at DeepL, reveals how the company shifted from specialised translation to launching autonomous AI agents, and why human-in-the-loop oversight remains non-negotiable even as agentic AI scales across heavily regulated industries. This conversation explores how DeepL agents work through a secondary browser interface where users can view real-time navigation, pause, raise their hand, and take or relinquish control at any time. Ed explains why the agent asks when unsure, building trust the same way you'd work with a new colleague, rather than locking themselves in a dark room until 5pm. We discuss where users still actively request control (login access, sensitive systems), what 20,000 completed tasks during beta testing revealed about when AI needs intervention, and why agents can flawlessly complete advanced tasks yet fail at very basic ones. Ed shares how DeepL works…

How do we prevent AI from amplifying destructive environmental narratives at a massive scale - potentially 100 billion words per day? Mariana Roccia and Jorge Vallego, from the H4rmony Project, reveal how ecolinguistics and ecosophies can reshape how large language models engage with ecological issues whilst addressing cultural and linguistic bias in AI-generated environmental discourse. This conversation explores how mainstream LLMs celebrate Coca-Cola as a "cultural icon" or patio heaters as "brilliant" without acknowledging environmental costs unless explicitly challenged. The team shares how they developed Theophrastus, an open-source assistant built on ChatGPT, instructed with an ecosophy: a living framework of ecological values that guides language generation toward planetary well-being rather than profit. We discuss how word embeddings cluster dominant narratives together in multidimensional space, why fine-tuning and reinforcement learning can shift those embeddings toward ecologically aligned…

What happens when AI becomes a dialogic partner in feedback rather than a replacement for human judgment? Dr Viktoria Magne, Dr Rebecca Mace, Sarah Hooper, and Dr Sharon Vince from the University of West London and University of Worcester reveal how structured AI conversations are helping students engage more deeply with feedback whilst keeping academic judgment clearly human-led. This conversation explores how AI creates low-stakes, judgment-free spaces where students can question, challenge, and co-construct understanding without fear of looking silly or upsetting relationships with staff. The team shares how they've designed reflective cycles using structured prompts that position students as active agents rather than passive recipients, and why this matters for equity, emotional safety, and critical AI literacy. We discuss the difference between transactional and dialogic AI use, why feedback shouldn't feel like static judgment, how AI helps students engage in "conversation with themselves", and what…

What happens when students delegate not just writing, but reasoning itself to AI? Chahna Gonsalves, Senior Lecturer at King's Business School, reveals how generative AI is transforming critical thinking in higher education through what she calls "epistemic offloading", the process of outsourcing intellectual work to tools like ChatGPT. This conversation examines how students are using AI to interpret readings, generate argument structures, and pre-evaluate their own work, shifting responsibility for core intellectual tasks. Chahna explores why AI prizes polish over depth, how this affects students' evaluative judgment, and what happens when students ask "does this sound like me?" We discuss the equity implications of tech-savviness, why reflexive AI use matters more than bans, and how Bloom's Taxonomy reveals which cognitive processes students readily offload versus protect. Chahna argues we need transparent conversations about delegation, judgment, and what truly requires human reasoning. Essential…

Do you use ChatGPT or Claude daily for work? Mark Carrigan, Senior Lecturer in Education at Manchester Institute of Education, joins the podcast to discuss why we might be misdiagnosing the harms of generative AI. His research suggests the problems aren't inherent to the technology itself, but arise when AI systems meet the already broken bureaucracies of higher education and other sectors. Mark introduces the LLM Interaction Cycle, a framework he developed with philosopher of technology, Milan Stürmer, to understand how we engage with AI over time through three phases: positioning (how we assign roles to the AI), articulation (how we put our needs into words), and attunement (the sense that the AI understands us). He explains how use that begins as purely transactional often drifts toward something more affective as models build memory and context about us, and why this drift matters for how we think about ethical AI use. We go on to explore teacher agency in the age of generative AI, examining why fear of…

As you search for Christmas gifts this season, have you asked ChatGPT or Gemini for recommendations? Katarina Mpofu and Jasmine Rienecker from Stupid Human join the podcast to discuss their research examining how AI systems influence public opinion and decision-making. Conducted in collaboration with the University of Oxford, their study analysed over 8,000 AI-generated responses to uncover systematic biases in how AI systems like ChatGPT and Gemini recommend brands, institutions, and governments. Their findings reveal that AI assistants aren't neutral—they have structured and persistent preferences that favour specific entities regardless of how questions are asked or who's asking. ChatGPT consistently recommended Nike for running shoes in over 90% of queries, whilst both models claimed the US has the best national healthcare system. These preferences extend beyond consumer products into government policy and educational institutions, raising critical questions about fairness, neutrality, and AI's role in…

In this episode, Max Sebti, co-founder and CEO of Score, challenges the centralised control of computer vision systems and makes the case for decentralised AI as a matter of public interest. Max brings experience from AI data annotation and model development, where he witnessed how closed systems collect and control vast amounts of visual data. Now at Score, running on the Bittensor network, he's building "open source computer vision" - systems that are publicly verifiable, permissionless, and collectively owned rather than corporately controlled. His central argument: we face a choice between "own AI or be owned by AI." As computer vision expands from sport into healthcare, insurance, and public surveillance, who controls these systems becomes existential. Max argues citizens should have access to model weights and training data as a democratic necessity. We explore what decentralisation means in practice: how Bittensor's incentive mechanisms unlock talent and data centralised systems can't access, why open…

In this episode, Jadee Hansen, Chief Information Security Officer at Vanta, reveals why AI security isn't keeping pace with AI adoption—and why that should concern every organisation. Jadee brings over 20 years of cybersecurity experience across highly regulated sectors, from Target to Code42, where she co-authored the definitive book on insider risk. Now at Vanta, a leading trust management platform, she's navigating one of security's biggest challenges: AI is being deployed by both attackers and defenders faster than either side truly understands it. The numbers are stark: 65% of leaders say their use of agentic AI exceeds their understanding of it. Over half of organisations have faced AI-powered attacks in the past year. Yet only 48% have frameworks to manage AI autonomy and control. Jadee's central argument: AI security isn't about applying AI everywhere, but it's about applying it wisely. The fundamental challenge? AI is non-deterministic. Unlike traditional security controls where "if this, then that"…

In this episode, Christian Lund, co-founder of Templafy, the leading AI-powered document generation platform, diagnoses why billions in AI investment aren't translating into business results. Christian's two decades in document automation have given him a front-row seat to AI's enterprise struggles. His central observation: organisations have successfully built the "brain" of AI systems but they're missing the "body." Without the orchestration layer that turns intelligence into action, even sophisticated AI remains largely useless. The conversation explores why speed alone proved insufficient. If you must review everything anyway, you haven't saved time, you've just shifted where you spend it. Christian argues this stems from unfair expectations: we wouldn't expect someone random at the coffee counter to deliver expert work with minimal context, yet that's precisely what we've expected from AI. Christian introduces "confident completion" as a framework: how complete can you be with a task, and how confident…

In this episode, Ryan Bolick, adjunct assistant professor at Duke University's Pratt School of Engineering and Turing Fellow at Fuqua School of Business, discusses Byline - a writing transparency tool he founded that tracks AI and human authorship in real time. Ryan's journey began after his sister-in-law received a zero on her first undergraduate paper when AI detectors falsely claimed she'd used AI throughout - she hadn't used it at all. Combined with conversations revealing students flagged despite honest work and educators struggling with inaccurate detection tools, this led him to build a different solution. Byline doesn't guess or detect - it tracks authorship with certainty. The platform automatically shows exactly how documents come together: what users wrote, what AI suggested, what they translated, and how collaborators contributed. This addresses the finding that students avoid citing AI use even when permitted due to friction involved. The conversation explores unexpected outcomes: students…

In this episode, Dr Maya Ackerman, computer scientist, CEO, musician, and author of the new book "Creative Machines: AI, Art and Us," explores the intersection of artificial intelligence and human creativity. This conversation with Maya challenges fundamental assumptions about machine creativity, with her arguing that the fear of AI hallucinations reveals more about human psychology than technology limitations. She contends that human thought itself is based on hallucinations (primarily our ability to predict and imagine) and that machines' imaginative capabilities make them powerful creative partners rather than threats. Together we explore how AI can expand our creative search space rather than narrow it, using examples from Maya's company WaveAI's Lyric Studio, which helps users explore unlikely lyrical possibilities. Maya also discusses the importance of "humble creative machines" that elevate human creativity rather than replace it, contrasting collaborative AI with the current trend toward "all-knowing…

In this episode, Dr Viktoria Mileva, Lecturer in Psychology and Faculty AI Lead at the University of Stirling, explores why we need to move beyond teaching students how to use AI tools towards developing critical AI literacy. Vicky argues that whilst students will naturally learn to use intuitive AI interfaces, they need deeper understanding of what's happening behind the scenes. The conversation tackles the fundamental challenge facing higher education: traditional assessments like "compare and contrast theories" no longer work when AI can complete them effectively. Vicky shares practical solutions being implemented at Stirling, including Microsoft 365 working folders that provide real-time visibility into student work processes, and the Stirling AI Assessment Scale that gives clear guidance on acceptable AI use levels. We explore the shift from "tell me what you know" to "show me how you think" assessments, discussing everything from portfolio-based evaluation to transparent AI logs. Vicky addresses the…

In this episode, Lizbeth Chandler, Innovation Lead at Accenture and one of the top 50 people in AI ethics globally, shares her journey from accessible tech user to AI ethics pioneer. With a background spanning computer science, law, and sustainability, Lizbeth offers insights into translating ethical principles into technical solutions. Lizbeth's story begins with her personal experience of growing up with autism in a household of inventors, where her brother created adaptive technology to help her communicate. This early exposure shaped her understanding that AI ethics affects real people's lives, not abstract theory. The conversation explores her transition from founding Good Robot Company, which focuses on bias detection through counterfactual analysis, to working within Accenture's global operations. She discusses practical applications, from CV scanning bias detection to creating a privacy-preserving wellbeing robot that monitors routine and prevents burnout. We explore preparing the next generation for…

In this first episode of season two, Yanyan Li, Meifang Zhuo, and Gunisha Aggarwal, three researchers from the University of Warwick, share findings from their WIHEA-funded study exploring how university students actually use AI in their academic work. Not what institutions think they should do, but what they're really doing. Through focus groups with Warwick students, their research reveals a complex picture that challenges assumptions about academic integrity and educational fairness. Students describe using AI as "strategic efficiency" tools - getting summaries before reading, help with essay structure, and grammar assistance - whilst simultaneously acknowledging risks of cognitive laziness and reduced social interaction with peers. The conversation explores AI's double-edged nature in education. Whilst serving as a vital equaliser for international students overcoming language barriers and neurodiverse learners managing cognitive demands, it's simultaneously creating new educational inequalities based on…

In this final episode of the first season, Liesl Rowe, Senior Digital Library Advisor and copyright expert at Leeds Beckett University, demystifies one of the most complex aspects of AI adoption: copyright law. As AI tools become increasingly accessible, understanding the legal landscape becomes crucial for educators, students, and creators alike. Liesl explores the fundamental challenge that's often overlooked in AI discussions: the difference between AI inputs and outputs, and why the former poses far greater copyright risks. While many institutions focus on citing AI-generated content, the real legal minefield lies in what we feed into these systems. She explains how feeding copyrighted material into AI models without permission essentially grants unauthorised access to large language models - a practice that's putting creators and institutions at risk. The conversation covers practical institutional responses, from Leeds Beckett's ethics procedure requiring AI use declaration to Leeds University's…

In this episode, John Mills, research and innovation expert turned entrepreneur, cuts through the AI hype to explore what really drives successful enterprise adoption. With 14 years of experience working with emerging technologies at the University of Central Lancashire and recent transition to running his own AI consultancy for newsrooms, John offers a unique perspective on innovation in practice. Rather than getting caught up in "either utopia or doom" narratives, John focuses on the fundamental characteristics that make entrepreneurs and organisations successful with AI. He explores the importance of calculated risk-taking, having a clear "why" beyond just making money, and developing organisational "ambidexterity" - the ability to excel at core missions while experimenting with new opportunities. The conversation delves into a fascinating case study from Danish tabloid publisher Ekstra Bladet, who tackled AI uncertainty using innovative "three horizons" planning - from 6-month tactical implementations to…

In this episode, Philippa (Pip) Armstrong, Digital Innovation Development Coach at Nottingham College, demonstrates how Further Education's collaborative culture offers valuable lessons for Higher Education's approach to AI integration. Rather than banning or tiptoeing around generative AI, Nottingham College has drawn a clear "line in the sand" with their innovative approach that other sectors can learn from. Pip introduces their "ACE" framework - Approach Cautiously and Ethically - and explains how they've created a culture of mindful AI use through transparency, support, and education. We explore their comprehensive strategy including rolling CPD programmes, dedicated Digital Innovation Development Coaches for each faculty, and their AI assessment scale that gives clear guidance on appropriate AI use levels. The conversation covers practical implementations that could be adapted across educational contexts: from English students creating their own AI images for creative writing tasks, to tutors using AI…

In this episode, Stephen Taylor from Regent's University London unpacks our historical tendency to panic about new technologies - from the Luddites destroying textile machinery to farmers blocking tractors, and now AI systems. As Learning Technology Lead, Stephen occupies what he terms the 'third space,' straddling academic and professional services to offer a unique vantage point on technological adoption. Using Bourdieu's habitus as our starting point, we examine how society's collective experiences programme our fearful responses to innovation, whilst media outlets amplify anxieties for headlines. Stephen draws a crucial distinction between AI and search engines: whilst Google provides answers, AI serves as an ideation partner for creative exploration. He doesn't shy away from discussing thorny issues like cultural bias in training data and the risk of 'algorithmic colonisation.' Rather than standing as obstacles to progress, Stephen urges us to climb into the driver's seat of technological change. His…

In this episode, we chat with Graham Atwell, Director of Pontydysgu and Honorary Associate Professor at Warwick University's Institute for Employment Research. With over nine years of experience working with AI in education, Graham offers a refreshingly candid perspective on the current AI landscape. We explore his views on the most exciting recent AI advancements, particularly in language translation tools and small but impactful time-saving applications. Graham shares his concerns about job displacement, corporate dominance in AI development, and the "black box" problem of unexplainable AI. Our discussion highlights the need for interdisciplinary approaches to AI development, greater university leadership in AI research, and the importance of involving workers, unions, and communities in shaping how AI is implemented. Graham encourages students to get involved with AI in their specific disciplines while maintaining a critical perspective, emphasizing that we should focus on how AI can be used for societal…

In this episode, we speak with Randeep Wilkhu, tech entrepreneur and founder of AI company Finden. With 22+ years of experience in the tech industry, including roles as a developer, venture capitalist, and startup founder, Randeep brings valuable insights on AI innovation. We discuss the characteristics of successful AI entrepreneurs, how his technical background provides an advantage in the AI space, and his work mentoring at Warwick Business School. Our conversation explores Finden's privacy-first approach to personal data management, the challenges universities face in adopting AI, and why small and medium-sized businesses may benefit most from AI innovation. Randeep shares thoughts on how government, businesses, and educational institutions can collaborate more effectively to create "playground" environments for AI experimentation while addressing privacy concerns and outdated educational frameworks. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of…

In this episode, we speak with Helen Hope, who leads academic integrity initiatives at the University of Worcester. With extensive experience in both higher education and secondary schools, Helen brings valuable insights from across educational sectors. We discuss how the emergence of generative AI in late 2022 disrupted established academic integrity practices, and how Helen has since led a university-wide group exploring AI integration across teaching, assessment, and institutional processes. Our conversation examines practical applications of AI for teachers, particularly in reducing planning time and supporting neurodiverse students. Helen references Sir Ken Robinson's critique of traditional education models, suggesting AI could be a catalyst for rethinking age-based learning. We explore challenges around academic integrity, resistance to technological adoption, and the potential of AI to address complex problems like student retention. Helen shares her vision for education that embraces technology…

In this episode, we speak with Raja Javaid, Chief Information and Transformation Officer at the University of Warwick. With 20+ years of experience in the private sector at companies like Dixons, Boots, and Rolls-Royce, Raja brings a unique cross-industry perspective to AI in education. We discuss the "iPhone moment" of generative AI, Warwick's new AI Centre of Excellence, and how the university is developing ethical frameworks based on OECD principles. Our conversation explores the balance between AI advancement and human values, examining challenges of bias, explainability, and sustainability. Raja shares insights on how universities can responsibly integrate AI while maintaining the human elements that make education meaningful. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠⁠⁠⁠⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and…

In this episode, we explore AI in education with University of Chester experts, Dr Katharine Welsh and Laura Milne. Katharine, an Associate Professor and University Innovation Fellow, and Laura, Head of Digital Education, lead their institution's AI and Education Working Group. They share insights on how they are working to responsibly integrate AI into their higher education context. Our conversation examines balancing AI's potential with challenges of sustainability, bias, and data privacy. We also discuss the "black box" nature of AI, changing assessment practices, and the importance of human judgment. Finally, we explore how universities can build AI literacy while ensuring equitable access and reducing environmental impact. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠⁠⁠⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and…

In this episode, we explore the complex relationship between AI, social justice, and education with Dr Gurnam Singh, Honorary Associate Professor of Sociology at the University of Warwick. Drawing from his extensive background in anti-racism, decoloniality, and pedagogical research, Dr Singh examines how AI systems intersect with existing social inequities. The conversation unpacks critical questions about bias in AI, from the limitations of training data in capturing diverse human knowledge to the potential for AI to either reinforce or challenge systemic inequalities. Dr Singh brings a unique sociological perspective to discussions of human intelligence versus artificial intelligence, exploring how AI tools might be harnessed for social justice while acknowledging their limitations. The discussion extends to practical considerations for education, examining how AI could potentially democratise access to knowledge while raising important questions about the nature of learning, creativity, and human…

In this episode, we delve into the critical intersection of AI ethics and corporate responsibility with Ganesan Keerthivasan and Tom Tirpak from ZealStrat, a strategic management consulting firm. Our guests bring unique perspectives: Ganesan, an MD-turned-CEO with a background in healthcare, and Tom, an electrical engineering PhD with extensive experience in AI implementation across multiple industries. They explore five key ethical considerations for AI development, including bias and fairness, privacy concerns, transparency, human-AI collaboration, and security risks. The conversation examines how businesses, individuals, and governments can work together to create responsible AI systems, drawing insights from emerging standards like the IEEE AI ethics framework and the EU's AI Act. The discussion emphasizes the urgent need for proactive ethical governance in AI development to avoid the regulatory challenges faced by previous technologies like social media. AI Ethics Now Exploring the ethical dilemmas of…

In this episode, we will begin to explore the intriguing world of consciousness and artificial intelligence with Professor Anil Seth, a renowned expert in cognitive and computational neuroscience. Professor Seth, whose research spans AI, neuroscience, and philosophy, offers a unique perspective on the ethical dimensions of AI. We examine the possibility of artificial consciousness, the impact of AI on our understanding of human consciousness, and the ethical considerations surrounding AI systems that mimic human-like qualities, such as language and emotion.AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact…

This week, we explore the exciting potential of AI in the workplace with Daniella Latham, Principal Product Marketing Manager at Atlassian. Daniella shares her perspective and expertise on the impact AI has on knowledge workers and ethical implications in business - from entrepreneurs and start-ups to big enterprises. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the discussions we have had to help offer a broader,…

This week, we delve into the critical intersection of AI and human rights. Our guest, Imogen Canavan, is a legal consultant working on the front lines of refugee protection. With her expertise in human rights and her experience supporting individuals fleeing persecution, Imogen provides invaluable insights into the potential impacts of AI on refugees and the importance of ensuring that these technologies are used ethically and responsibly. Tune in to this important conversation! AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was…

This week we are joined by Pavan Konanur, CEO and Co-Founder of Hoja AI, an educational AI start up. Pavan discusses the concepts of AI, Innovation, and Design Thinking. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the discussions we have had to help offer a broader, interdisciplinary perspective on the ethical and societal implications of artificial intelligence to a wider audience. Join each fortnight for new…

In this episode, Smera Jayadeva, a Researcher at the Alan Turing Institute and Visiting Researcher at the Digital Environment Research Institute, joins us to discuss critical issues in AI ethics and responsible innovation AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the discussions we have had to help offer a broader, interdisciplinary perspective on the ethical and societal implications of artificial intelligence…

This week, we chat with Dr. Chris Murphy, Regional CTO, EMEA at VIAVI Solutions, and a member of the UK Telecom Innovation Network. He discusses the opportunities and threats of AI in the UK telecoms industry AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the discussions we have had to help offer a broader, interdisciplinary perspective on the ethical and societal implications of artificial intelligence to a wider…

This week, we're joined by Dr Sanjay Sharma, Associate Professor in the Centre for Interdisciplinary Methodologies at the University of Warwick. Sanjay's sector-leading work on technologies of race and racism, drawing from critical data justice, decolonial, and abolitionist perspectives, provides crucial insights into the potential harms of AI. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the discussions we have…

This week, we explore the exciting potential of AI in education with Dr Lynne Taylerson, Director and Lead Trainer at Real Time Education. Lynne, also a researcher in learning technology and a consultant for an AI design organisation, shares her insights on creating engaging learning spaces powered by AI. Join us for a conversation about the future of education. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society, individuals, and the very definition of 'humanness.' This podcast was initially designed to provide a deeper dive into the key themes explored each week in class. We want to share the…

This week on AI Ethics Now, we're joined by Andrew Maynard, Professor of Advanced Technology Transitions at Arizona State University, a leading voice on the future of humanity. Professor Maynard has increasingly focused his research on the responsible development of AI, exploring the ethical, social, and environmental implications of this transformative technology. A renowned commentator on the future of humanity, Professor Maynard brings a unique perspective to the challenges and opportunities presented by the rapid advancement of AI. AI Ethics Now Exploring the ethical dilemmas of AI in Higher Education and beyond. A University of Warwick IATL Podcast This podcast series was developed by Dr Tom Ritchie and Dr Jennie Mills, the module leads of the ⁠IATL module ⁠"The AI Revolution: Ethics, Technology, and Society"⁠⁠ at the University of Warwick. The AI Revolution module explores the history, current state, and potential futures of artificial intelligence, examining its profound impact on society,…