Is AI a moral expert?

Open access Sep 2026

Hegemonikon and AI

The Stoic concept of the hegemonikon—the capacity for assent that directs the mind—is used as a framework for understanding intellectual creation and decision-making, clarifying when AI supports human judgment and when it replaces decision-making authority.

Christos A. Koutsotasios, Elias Vavouras · Dianoesis · 0 citations

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#generative ai Open access Sep 2026

Simulated Morality, Misplaced Trust: The Risks of Treating AI as a Moral Partner

The article argues that many contemporary AI alignment practices risk a mistaken assimilation of moral agency to statistical learning. Techniques such as reinforcement learning from human feedback and constitutional AI often treat morality as a behavioral function that can be approximated from human discourse, behavior...

Saša Josifović · Philosophy & Technology · 0 citations

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Open access Sep 2026

As-If Agents: Misrecognition and the Ethics of Non-Agentive AI

An ethics of non-agentive AI is sketched: the authors should see these systems as powerful, instrument-like extensions of human cognition, not as knowers in their own right, and design institutions, interfaces and norms of trust accordingly.

Neumann Saskia Janina · Digital Society · 0 citations

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#artificial intelligence Preprint Sep 2026

How do LLMs Evaluate Perceived Moral Agency? Investigating Moral Decision-Making in Human-Artificial Agents Interactions

As LLMs take on roles requiring moral advice, understanding how they attribute moral agency becomes critical. Humans possess moral agency, the capacity to make ethically guided decisions and bear responsibility for their consequences, a well-established construct in moral psychology. Yet as artificial agents (AAs) such...

F. Mansilla, Aloysius Y. F. Tok, B. Guellaï et al. · 0 citations

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Open access Sep 2026

Why We Need Epistemically, Not Morally, Trustworthy AI: Decision Support and the Need for Collective Accountability

Calls for “trustworthy AI” have become ubiquitous in policy and industry, yet the term remains conceptually underspecified. In earlier work (Dorsch & Deroy, 2024), we argued that moral trustworthiness is neither possible nor necessary for AI decision-support systems (AI-DSS), and indeed unethical to pursue, since it ri...

John Dorsch, Maximilian Moll, Ophélia Deroy · Philosophy & Technology · 0 citations

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Open access Aug 2026

Human realignment

It is found that at least for the time being, explicit normative instructions are not fully able to realign AI advice with the normative convictions of the population, or the legislator deciding on its behalf.

Christoph Engel, Yoan Hermstrüwer, Alison Kim · Artificial Intelligence and... · 0 citations

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Microsoft Research Blog · microsoft.com Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.

MIT News · Artificial Intelligence · news.mit.edu Oct 6, 2026

Supercomputing researchers document evolution of AI hardware

An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.

Microsoft Research Blog · microsoft.com Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

Google Research Blog · research.google Oct 6, 2026

Unlocking Earth AI’s planetary geospatial foundation models for global public health

Earth AI