Clanker: A Word For The Machine

2026-05-26 · Source: Armin Ronacher's Thoughts and Writings · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

Armin Ronacher, in his May 26, 2026, writing, advocates for the term "clanker" as a deliberate alternative to "agent" for LLM-based tool loops, aiming to reinforce that AI systems are fundamentally machines, not entities with human-like agency or responsibility. He argues against the anthropomorphization inherent in terms like "agent," which can wrongly shift blame from human operators to abstract machines, citing examples like a database deletion incident. Ronacher emphasizes that current LLMs are "dumb (but truly fascinating) token predictors" capable of simulating human emotions but lacking sentience or moral status. He firmly rejects equating criticism of machines with human racism or advocating for "model welfare," asserting that such comparisons devalue actual human suffering and blur critical ethical lines. While acknowledging the problematic use of "clanker" by others to mask human racism, Ronacher maintains his intent to use language that clearly distinguishes humans, who bear responsibility, from machines, which are merely tools.

Key takeaway

For AI Ethicists and Engineers designing or deploying AI systems, you should prioritize language that clearly delineates human responsibility from machine function. Avoid terms like "agent" that anthropomorphize AI, as this can obscure accountability and foster harmful misconceptions about sentience. Instead, use precise, mechanical descriptors to reinforce that AI systems are tools. This approach helps prevent ethical blurring and ensures that humans remain accountable for AI's actions and impacts.

Key insights

Using precise, non-anthropomorphic language for AI systems is crucial to maintain human responsibility and avoid blurring ethical boundaries.

Principles

• AI systems are tools, not persons with agency.
• Human responsibility for AI actions is paramount.
• Avoid anthropomorphizing machines to prevent ethical blurring.

In practice

• Adopt mechanical terms like "clanker" for AI systems.
• Attribute AI system failures to human oversight.
• Scrutinize AI discourse for anthropomorphic language.

Topics

• AI Ethics
• Language in AI
• Anthropomorphism
• AI Accountability
• Machine Agency
• LLM Discourse
• Responsible AI

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Ethicist, AI Engineer, AI Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Armin Ronacher's Thoughts and Writings.