







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.
AI, Ethics, and Society — Home
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 Class
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.

What Does 'Human-Centred AI' Mean?
While it seems sensible that human-centred artificial intelligence (AI) means centring "human behaviour and experience," it cannot be any other way. AI, I argue, is usefully seen as a relationship between technology and humans where it appears that artifacts can perform, to a greater or lesser extent, human cognitive labour. This is evinced using examples that juxtapose technology with cognition, inter alia: abacus versus mental arithmetic; alarm clock versus knocker-upper; camera versus vision; and sweatshop versus tailor. Using novel definitions and analyses, sociotechnical relationships can be analysed into varying types of: displacement (harmful), enhancement (beneficial), and/or replacement (neutral) of human cognitive labour. Ultimately, all AI implicates human cognition; no matter what. Obfuscation of cognition in the AI context -- from clocks to artificial neural networks -- results in distortion, in slowing critical engagement, perverting cognitive science, and indeed in limiting our ability to truly centre humans and humanity in the engineering of AI systems. To even begin to de-fetishise AI, we must look the human-in-the-loop in the eyes.

What Does 'Human-Centred AI' Mean?
While it seems sensible that human-centred artificial intelligence (AI) means centring "human behaviour and experience," it cannot be any other way. AI, I argue, is usefully seen as a relationship between technology and humans where it appears that artifacts can perform, to a greater or lesser extent, human cognitive labour. This is evinced using examples that juxtapose technology with cognition, inter alia: abacus versus mental arithmetic; alarm clock versus knocker-upper; camera versus vision; and sweatshop versus tailor. Using novel definitions and analyses, sociotechnical relationships can be analysed into varying types of: displacement (harmful), enhancement (beneficial), and/or replacement (neutral) of human cognitive labour. Ultimately, all AI implicates human cognition; no matter what. Obfuscation of cognition in the AI context -- from clocks to artificial neural networks -- results in distortion, in slowing critical engagement, perverting cognitive science, and indeed in limiting our ability to truly centre humans and humanity in the engineering of AI systems. To even begin to de-fetishise AI, we must look the human-in-the-loop in the eyes.

Field Theory: AI as Social Science Question, Object & Tool
Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.
ETCH
We believe technology should serve humanity and that human creativity is essential and irreplaceable. We support the ethical development and deployment of AI by funding protective technologies and translating research into real-world tools for creative communities.

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…

Mathematical methods and human thought in the age of AI
Artificial intelligence (AI) is the name popularly given to a broad spectrum of computer tools designed to perform increasingly complex cognitive tasks, including many that used to solely be the province of humans. As these tools become exponentially sophisticated and pervasive, the justifications for their rapid development and integration into society are frequently called into question, particularly as they consume finite resources and pose existential risks to the livelihoods of those skilled individuals they appear to replace. In this paper, we consider the rapidly evolving impact of AI to the traditional questions of philosophy with an emphasis on its application in mathematics and on the broader real-world outcomes of its more general use. We assert that artificial intelligence is a natural evolution of human tools developed throughout history to facilitate the creation, organization, and dissemination of ideas, and argue that it is paramount that the development and application of AI remain fundamentally human-centered. With an eye toward innovating solutions to meet human needs, enhancing the human quality of life and expanding the capacity for human thought and understanding, we propose a pathway to integrating AI into our most challenging and intellectually rigorous fields to the benefit of all humankind.

Ali Alkhatib: Defining AI
The main issue I have with a lot of work that tries to define AI is that the criteria they use to draw boundaries often turn out to be functionally useless for my needs; these definitions lead us to weird places, letting scholars fixate on strange, unworkable frameworks. Those pedantic fixations don’t really benefit the organizers, activists, regular people who are getting crushed by the systems they’re trying to work against. So I’m going to try to unpack how I think about AI; how I trace the boundaries of the term in a way that’s as useful as possible for me and my needs; and how I would encourage you to scope or define ideas that are important to your work.

AI is An Ideology, Not A Technology
At its core, "artificial intelligence" is a perilous belief that fails to recognize the agency of humans.

Human-Centered Artificial Intelligence: Three Fresh Ideas
Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation. These human aspirations also encourage consideration of privacy, security, environmental protection, social justice, and human rights. This commentary reverses the current emphasis on algorithms and AI methods, by putting humans at the center of systems design thinking, in effect, a second Copernican Revolution. It offers three ideas: (1) a two-dimensional HCAI framework, which shows how it is possible to have both high levels of human control AND high levels of automation, (2) a shift from emulating humans to empowering people with a plea to shift language, imagery, and metaphors away from portrayals of intelligent autonomous teammates towards descriptions of powerful tool-like appliances and tele-operated devices, and (3) a three-level governance structure that describes how software engineering teams can develop more reliable systems, how managers can emphasize a safety culture across an organization, and how industry-wide certification can promote trustworthy HCAI systems. These ideas will be challenged by some, refined by others, extended to accommodate new technologies, and validated with quantitative and qualitative research. They offer a reframe -- a chance to restart design discussions for products and services -- which could bring greater benefits to individuals, families, communities, businesses, and society.
2026 Cosmos HAI Lab Lecture with Jack Clark, Co-founder of Anthropic
> the central promise of “ai” is that nothing is worth doing and that community doesn’t exist. It’s individual entitlement as software. It’s Thatcherism. post.lurk.org/@emenel/117441848350524047
emenel (@emenel@post.lurk.org)
post.lurk.orgProperty Testing with Agent Swarms

Agency and Agents
ГАЛЬВАНИЗАЦИЯ АВТОРА, ИЛИ ЭКСПЕРИМЕНТ С НЕЙРОННОЙ ПОЭЗИЕЙ. Борис Орехов. «Новый мир» №6, 2018

Personal Online RL | 🌱 | Offprint
Approaching an unknown communication system by latent space exploration and causal inference | Royal Society Open Science | The Royal Society

Surya Narreddi