Digest Issue 92: The AI Ethics Brief #202 | What Happens When You Have a Choice? | Reading the Label on AI | Pangram is not an oracle | A Fresh Look at The World Map of Encryption Laws and Policies

AI, Ethics, and Society — Home

The Future of AI

The Parents’ Paradox: AI, Ethics, and the Limits of Machine Morality This post is based on a talk I gave at The AI & Automation Conference in London on February 25, 2026, and my slides. A…

Let’s talk about AI and end-to-end encryption

Recently I came across a fantastic new paper by a group of NYU and Cornell researchers entitled “How to think about end-to-end encryption and AI.” I’m extremely grateful to see th…

The tech industry hijacking of the AI ethics research agenda and why we should reclaim it

This paper reflects on the tech industry’s colonization of the AI ethics research field and addresses conflicts of interest in public policymaking concerning AI. The AI ethics research community faces two intertwined challenges: In the first place, we have a tech industry heavily influencing the AI ethics research agenda. Secondly, cleaning up after the tech industry has implied that we have turned to value-driven design methods to bring ethics to AI design. But by framing research questions relevant to a technical practice, we have facilitated the technological solutionism behind the tech industry’s business model. Therefore, this paper takes the first steps to reshape the AI ethics research agenda by suggesting moving toward an emancipatory framework that brings politics to design while, at the same time, bearing in mind that AI is not to be treated as an inevitability. As a research community, we must focus on the repressive power dynamics exacerbated by AI and address challenges facing the vulnerable groups seldom heard, despite the fact that they are the ones most negatively affected by AI initiatives.

AI & Ethics Workgroup | Lincoln Center for Applied Ethics

Artificial Intelligence (AI) is a term with an array of contingent and shifting meanings, unified only by a general aspiration to use mathematical computation to emulate human cognition, language and problem-solving. Rather than a technical term, “AI” can be thought of as a sociotechnical system and assemblage, consisting of technical objects and social imaginaries, practices and ideologies. How we characterize and conceptualize AI shapes how, why and when we use it and when we may constrain or refuse its use. This paper provides a primer on various technologies that often fall under the rubric of “AI” and outlines the various discursive and cultural meanings carried by the term. 

The Real Existential Risk Is AI CEOs Avoiding Oversight: “Alternative Nobel” Winner Timnit Gebru

We speak to the prominent AI researcher and leading critic of the AI industry, Timnit Gebru, who was recently awarded a 2026 Right Livelihood Award for her work investigating the harms and hype behind the global buildup of artificial intelligence. “Instead of discussing faulty, unreliable systems,” Gebru says tech leaders like SpaceXAI’s Elon Musk, OpenAI’s Sam Altman and Anthropic’s Dario Amodei are “marketing their systems as all-knowing, superpowerful, superintelligent,” and lobbying for “self-policing and self-regulation” to avoid being held “liable through existing laws.” Gebru expresses skepticism over increasingly widespread claims that AI algorithms pose an existential risk to humanity, warning that such claims are overblown and that “what is actually happening is regulatory capture.”

AI and the crisis of the author

Editor’s note (September 21, 2026): We have removed this essay. AI was used in its preparation. The TLS editorial guidelines prohibit the use of AI in the

How Shifting Responsibility for AI Harms Undermines Democratic Accountability | TechPolicy.Press

The moralization of individual AI use deflects responsibility away from powerful actors like corporations and governments, Suvradip Maitra and others write.

Taking AI Welfare Seriously

In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood, i.e. of AI systems with their own interests and moral significance, is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously. We also recommend three early steps that AI companies and other actors can take: They can (1) acknowledge that AI welfare is an important and difficult issue (and ensure that language model outputs do the same), (2) start assessing AI systems for evidence of consciousness and robust agency, and (3) prepare policies and procedures for treating AI systems with an appropriate level of moral concern. To be clear, our argument in this report is not that AI systems definitely are, or will be, conscious, robustly agentic, or otherwise morally significant. Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.

Compare CIRIS: Verifiable Ethical AI vs the Alternatives, With Receipts

How CIRIS's signed, on-device, checkable ethical AI stacks up against the alternatives — the safety case, with receipts.

AI and the Dangerous Fiction of ‘All Lawful Use’

Dunstan Allison-Hope and Iain Levine argue that human rights commitments are essential for all companies selling their products to governments worldwide.

Amnesty International: Encryption is a Human Rights Issue

New Report Analyzes How Crypto Backdoors, Interference with Crypto, and Compelled Disclosure of Encryption Keys All Impact Free Expression and Privacy Defending encryption is a human rights issue,

The Impact of Artificial Intelligence on Human Thought

This research paper examines, from a multidimensional perspective (cognitive, social, ethical, and philosophical), how AI is transforming human thought. It highlights a cognitive offloading effect: the externalization of mental functions to AI can reduce intellectual engagement and weaken critical thinking. On the social level, algorithmic personalization creates filter bubbles that limit the diversity of opinions and can lead to the homogenization of thought and polarization. This research also describes the mechanisms of algorithmic manipulation (exploitation of cognitive biases, automated disinformation, etc.) that amplify AI's power of influence. Finally, the question of potential artificial consciousness is discussed, along with its ethical implications. The report as a whole underscores the risks that AI poses to human intellectual autonomy and creativity, while proposing avenues (education, transparency, governance) to align AI development with the interests of humanity.