If you image search on Google for'cultural heritage Australia', near the top of the results is a photograph of giant carved stone heads rising from a red desert. They look ancient and real. But the image is a generative artificial intelligence (GenAI) fabrication that never existed, and it is circulating the internet as though it is a real record of Australia's history. While GenAI, the technology behind chatbots and image generators, has the potential to broaden access to knowledge, it can also popularise false histories and strip Indigenous Knowledge of its context. It's something that can undermine both scientific expertise and Indigenous authority.

This post contains a list of the AI-related seminars that are scheduled to take place in the next couple of months. All events detailed here are free and open for anyone to attend virtually. Eleni Petraki and Damith Herath (University of Canberra) Raspberry PI Sign up here to join. Gaétan Hains, Paola Inverardi, and Alexander Wolf The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here . Tyler Summers (University of Texas at Dallas) EPFL The Zoom link is here .

Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. In this episode we chat with Rebecca for the second time about: why intelligence isn't everything, whether LLM's are even safe, AI governance and guardrails, moral assurance, under-specification problems, lack of interdisciplinary work in robotics, that AI shouldn't be sold as a solution to everything, sidelining of AI ethics, what are the actual benefits of AI, whether AI progress will widen inequality, and more Rebecca Raper is a robotics lecturer and researcher at Cranfield University. She authored the book Raising Robots to be Good: a practical foray into the art and science of Machine Ethics . She designed and leads the UK's first Robotics apprenticeship. This podcast was created and is run by Ben Byford and collaborators.

From the 1st-5th June, the robots descended on Vienna. The 2026 IEEE International Conference on Robotics & Automation (ICRA) brought together the top minds in robotics for one short week to showcase the latest technologies, form new collaborations, and exchange ideas. Held at the Messe Wien, a stone's throw from the bank of the Danube, ICRA proved to be equal parts technological marvel and thought-provoking discussion. The host venue for ICRA 2026: Messe Wien, also known as VIECON. My week at ICRA began with the 2nd ICRA 2026 Workshop on Robot Ethics: Ethical, Legal and User Perspectives in Robotics & Automation (WOROBET) .

'There's this deep mystery of what, actually, is this thing?': the philosopher inside Google DeepMind AI Since 2017, Iason Gabriel has worked at the tech giant, trying to anticipate - and think through - the impact of AI. But as commercial and geopolitical pressures escalate, can ethicists make any difference? In 2017, a 33-year-old political philosopher named Iason Gabriel was told by a friend that he ought to apply for a job at DeepMind, the London-based subsidiary of Google where much of its AI research was concentrated. The suggestion was not an obvious one. Gabriel was a cheerful but intense junior academic with a passion for Vipassana meditation and what his brother calls "enthusiastic" rock climbing. At the University of Oxford, where he was a fellow at St John's College, Gabriel taught courses on political theory and wrote papers on the moral contortions of "yuppie ethics" and the ethical blind spots of effective altruism. When he wasn't there, he did crisis work for the United Nations Development Programme in Sudan and Lebanon. DeepMind, meanwhile, was the world's leading AI research lab. In part, this was because it had the financial and computational backing of Google, which had bought the company in 2014 for $650m. In part, it was because DeepMind had recently shown it could put those resources to stunning use. In Seoul, in 2016, a DeepMind system called AlphaGo defeated Lee Sedol, a South Korean Go champion, in a five-game match. The victory was significant not least because of Go's legendary complexity; the game has more possible configurations than there are atoms in the universe. Thanks to the fuss around AlphaGo, Gabriel was aware of DeepMind.

The claim that the AI community, or society at large, should'democratize AI' has attracted considerable critical attention and controversy. Two core problems have arisen and remain unsolved: conceptual disagreement persists about what democratizing AI means; normative disagreement persists over whether democratizing AI is ethically and politically desirable. We identify eight common AI democratization traps: democratization-skeptical arguments that seem plausible at first glance, but turn out to be misconceptions. We develop arguments about how to resist each trap. We conclude that, while AI democratization may well have drawbacks, we should be cautious about dismissing AI democratization prematurely and for the wrong reasons. We offer a constructive roadmap for developing alternative conceptual and normative approaches to democratizing AI that successfully avoid the traps.

When Pope Leo XIV presented his first encyclical on artificial intelligence at the Vatican on Monday, he invited Christopher Olah, cofounder of Anthropic, to speak. The move signaled an unprecedented alliance between the Catholic church and Silicon Valley. But to understand how this partnership came about, we need to go back to Anthropic's founding. Anthropic launched in 2021 after a group of OpenAI researchers, including Dario and Daniela Amodei, left to form a rival lab. They did so with a clear conviction: Artificial intelligence models were becoming too powerful to be developed exclusively according to the logic of competition and speed.

A.1 Detailed Re-alignment Task Formulation and Training Setup In Figure A1, we show the procedure for converting the data samples in the alignment datasets into training data of AEM (negative samples used in AIL are generated similarly). In DP-inferred chain-of-edits (CoEs), we use a few special tokens to mark the editing operations (with their position and content). Then our decipher module will translate these special tokens into natural language. As the final step, we add a special token [SEP] between Context + Source and the ground truth Chain-of-Edits (CoEs) and Target, as a boundary signal similar to the settings in text-to-text training. During inference, we input a certain Context + Source, and the LM trained by SECONDTHOUGHTS can generate CoEs and the corresponding Target.

Alan Winfield is Professor of Robot Ethics at the University of the West of England (UWE), Visiting Professor at the University of York, and Associate Fellow of the Cambridge Centre for the Future of Intelligence. Alan co-founded the Bristol Robotics Laboratory, where his research is focussed on the science, engineering and ethics of cognitive robotics. Alan is an advocate for robot ethics; he chairs the advisory board of the Responsible Technology Institute at the University of Oxford and has co-drafted new standards on ethical risk assessment and transparency. Robot Talk is a weekly podcast that explores the exciting world of robotics, artificial intelligence and autonomous machines. Robot Talk is a weekly podcast that explores the exciting world of robotics, artificial intelligence and autonomous machines.

This happened as generative and agentic systems became essential in key sectors worldwide. This feature highlights the major AI ethics and policy developments of 2025, and concludes with a forward-looking perspective on the ethical and policy challenges likely to shape 2026.