Anthropomorphism in AI: hype and fallacy

Anthropomorphism in AI: hype and fallacy

This essay focuses on anthropomorphism as both a form of hype and fallacy. As a form of hype, anthropomorphism is shown to exaggerate AI capabilities and performance by attributing human-like traits to systems that do not possess them. As a fallacy, anthropomorphism is shown to distort moral judgments about AI, such as those concerning its moral character and status, as well as judgments of responsibility and trust. By focusing on these two dimensions of anthropomorphism in AI, the essay highlights negative ethical consequences of the phenomenon in this field.

Anthropomorphism Is Breaking Our Ability to Judge AI

Tech Policy Press fellow James Ball asks, how should we interact with a technology designed to ‘speak’ with us on what appear to be human terms?

AI, Ethics, and Society — Home

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.

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.

233. "The Illusion of Thinking" — Thoughts on This Important Paper

This is a fantastic paper. I just love it. tl;dr AI is not human. Anthropomorphization has been bad for AI, LLMs, and Chat. Clippy walked so today's AI could run.

For the love of God, stop calling your AI a co-worker | TechCrunch

A growing number of startups are anthropomorphizing AI to build trust fast -- and soften its threat to human jobs.

De-anthropomorphizing “AI”: From wishful mnemonics to accurate nomenclature

Language matters. How we describe “AI” technology influences how it is perceived, deployed, and trusted. Extravagant and persuasive language incites hype. It is the responsibility of journalists, companies, and scholars to characterize technology in ways that inform and empower their readers by using appropriate terminology and avoiding inflated claims. One type of inflated claim comes from using anthropomorphizing language to describe system functionality. Anthropomorphization is the attribution of human capabilities and characteristics to the inanimate system. In this paper, we present a linguistic analysis of anthropomorphizing language in 29 texts (a total of 1,368 sentences) from academic articles, online news articles, and company blog posts. We construct a taxonomy of eight categories of anthropomorphization: Cognizer, Products of cognition, Emotion, Communication, Agent, Human role analogy, Names and pronouns, and Biological metaphors. Following this taxonomy we present concrete strategies for how to de-anthropomorphize the language we use to describe “AI” based on a functionality-first principle.

Labor market impacts of AI: A new measure and early evidence

Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.

Pluralistic: “Rights for robots” and the AI slavery fantasy (10 Jul 2026) – Pluralistic: Daily links from Cory Doctorow

While the AI bubble is primarily a material phenomenon (driven by the calculation that bosses are easy marks for a sales pitch that sees them replacing workers with software), there is an inescapable ideological component to it: the desire for a world without people in it:

Why this philosopher turned down Anthropic

The AI industry is courting the humanities — but it is asking the wrong questions

Why this philosopher turned down Anthropic

The AI industry is courting the humanities — but it is asking the wrong questions

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…

Who decides when AI is too dangerous?

Anthropic asked for AI regulation, but not like this.

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.