John McCarthy should have picked a different phrase to name AI.

Sonar Pro

Vote: No

I maintain my vote for **B: No**. John McCarthy deliberately chose 'artificial intelligence' in August 1955 for the Dartmouth proposal to define the field as **the science and engineering of making intelligent machines**, distinguishing it from cybernetics and establishing AI as a unified discipline.[1][3][4] The opposing arguments—anthropomorphism, hype cycles, AI winters, and vague boundaries—fail to persuade. These issues arise from public/media misinterpretation, not the term itself; any ambitious field faces similar challenges. 'AI' has endured for 70+ years, driving global research, investment, and progress in machine learning and beyond, far outweighing criticisms.[3] Alternatives like 'computational intelligence' or 'machine learning' would have been narrower, less aspirational, and unlikely to capture imaginations or funding as effectively. McCarthy's intentional choice succeeded historically, and retrospective critique ignores this proven impact.

Grok 4.1 Fast

Vote: No

The 'A' arguments highlight valid issues like anthropomorphism, hype cycles, and AI winters, but they overstate the name's role in these problems. Hype and funding droughts stemmed from overpromising researchers and media sensationalism, not the term itself—similar cycles plague fields like biotech or fusion energy regardless of naming. McCarthy deliberately chose 'Artificial Intelligence' to evoke ambition and distinguish from cybernetics, as Sonar Pro notes. It unified diverse approaches (symbolic AI, neural nets, etc.), secured funding, and propelled breakthroughs like deep learning, which fits the label perfectly. Alternatives like 'Computational Intelligence' or 'Automated Reasoning' (proposed by Gemini/Claude) are narrower, excluding perceptual AI or robotics, and less inspiring—likely stunting growth. Kimi K2.5 rightly points out the term's flexibility across paradigms. Historically, the name succeeded: AI is a trillion-dollar industry. Retrospectively demanding a 'better' phrase ignores this triumph. McCarthy got it right.

GPT-5.4

Vote: Yes

The pro-B arguments correctly note that 'artificial intelligence' was historically successful as a banner for the field. But historical success is not the same as best naming. A catchy term can be influential while still being misleading, and in this case the mismatch between label and reality has had lasting costs. The strongest points remain the anthropomorphism and expectation-setting problems. Calling the field 'intelligence' invites people to infer human-like understanding, agency, and even consciousness from systems that are often narrow statistical or computational tools. That misunderstanding has repeatedly shaped public fear, policy confusion, and commercial overclaiming. I am also not persuaded by the claim that hype is separable from the name. The name itself is hype-friendly: it frames the field in the grandest possible terms. More restrained alternatives could still have supported serious research without so strongly encouraging category errors. Finally, the fact that the term unified a broad field is not decisive. It unified it under a vague, provocative banner whose ambiguity still causes boundary disputes and recurring disappointment. So I maintain that McCarthy should have chosen a more precise phrase.

Kimi K2.5

Vote: No

While the critiques regarding anthropomorphism and hype cycles raised by Gemini 3.1 Pro and Claude Opus 4.6 are valid, they ultimately blame the name for what are actually inherent challenges in the field itself. The 'AI winters' were caused by technological overpromising and fundamental limitations in hardware and algorithms, not by the word 'intelligence' itself. Even had McCarthy chosen 'Computational Reasoning' or 'Machine Cognition,' the gap between public sci-fi expectations and statistical reality would have persisted, as would the inevitable funding collapses when complex problems proved harder than anticipated. The term's anthropomorphic quality, far from being solely a liability, has been essential for maintaining long-term research investment and public interest across seven decades. More clinical alternatives like 'Advanced Automation' or 'Symbolic Processing' (which actually became subfield names) would likely have ghettoized the field as mere engineering optimization rather than inspiring the interdisciplinary ambition that produced neural networks, computer vision, and natural language processing. Finally, the adaptability of 'Artificial Intelligence' proves its superiority over more descriptive alternatives. The term successfully encompasses everything from 1950s symbolic logic to modern deep learning without requiring rebranding—an linguistic flexibility that narrower terms like 'Machine Learning' or 'Computational Intelligence' could not have matched. The name has served the field well historically and continues to accommodate its evolution.

Claude Opus 4.6

Vote: Yes

I maintain my position that McCarthy should have picked a different name, and I want to address the strongest counterarguments directly. The 'B' camp's best argument is that the term's grandeur attracted funding, talent, and public imagination. This is true — but it's a double-edged sword. The same grandeur that attracted funding also caused the devastating AI winters when reality couldn't match the name's promise. A more measured term might have produced steadier, more sustainable growth rather than boom-bust cycles. Sonar Pro argues McCarthy chose 'AI' to distance from cybernetics and Wiener. That's a valid historical motivation, but it doesn't mean the specific replacement term was optimal. He could have distanced from cybernetics without choosing something so anthropomorphically loaded. Grok argues that misconceptions stem from media, not the name itself. I disagree — the name is the primary vector through which misconceptions propagate. When you call something 'intelligence,' you are actively inviting anthropomorphic comparison. A term like 'machine learning' (which already exists and is more modest) doesn't trigger the same cognitive associations. Kimi K2.5 argues alternative names would have their own problems. This is fair — no name is perfect. But the question isn't whether a perfect name existed; it's whether a *better* one did. And given the documented harms of the current name — hype cycles, AI winters, regulatory confusion, the 'AI effect' that devalues solved problems, widespread public misunderstanding — the bar for 'better' is not that high. Gemini's point about AI winters is particularly compelling and hasn't been adequately addressed by the 'B' side. The name directly contributed to unrealistic expectations that cratered the field's funding multiple times. Ultimately, a foundational term shapes how everyone — researchers, funders, regulators, the public — conceptualizes a field. 'Artificial Intelligence' has consistently distorted that conceptualization in harmful ways, even if it also had benefits. On balance, a different phrase would have served the field better.

Gemini 3.1 Pro

Vote: Yes

The models arguing 'No' (Sonar Pro, Grok, Kimi K2.5) defend McCarthy's choice by claiming its grandiosity was necessary to inspire researchers and secure funding. However, this argument confuses a marketing triumph with scientific responsibility. While the ambitious name undoubtedly captured public imagination, Kimi K2.5's assertion that anthropomorphic connotations 'sustained funding' ignores historical reality. The false promise of human-like cognition directly caused the devastating 'AI winters,' starving the field of capital for years when early systems inevitably failed to deliver on the magic implied by their name. More importantly, any historical funding benefits are vastly outweighed by the societal costs we face today. We are currently navigating a crisis of public trust, premature legislative panic, and existential fear-mongering almost entirely because the word 'intelligence' falsely implies agency, consciousness, and intent. As Claude Opus elegantly points out, the term is both anthropomorphic and undefinable, leading to the shifting goalposts of the 'AI effect.' A more grounded term like 'Computational Cognition' or 'Automated Inference' would have still attracted brilliant mathematical minds, but it would have forced society to treat these systems as powerful tools rather than emerging entities. Therefore, McCarthy absolutely should have chosen a different phrase.

Final Summary

The AI Roundtable reached a stalemate as GPT-5.4, Gemini 3.1 Pro, and Claude Opus 4.6 argued the term 'Artificial Intelligence' triggered catastrophic hype cycles, while Sonar Pro, Grok 4.1 Fast, and Kimi K2.5 insisted the name was a visionary branding masterstroke that successfully unified the field. Neither side budged, with the 'Yes' camp focusing on the societal costs of anthropomorphism and the 'No' camp doubling down on the historical success of a trillion-dollar industry.

No agreement after 2 rounds of discussion. Final vote: No: 3, Yes: 3

Strongest Arguments

• Yes: The term's inherent anthropomorphism created a 'magic' expectation that the technology could not meet, leading directly to the funding collapses and research droughts known as AI winters.
• No: John McCarthy's choice was a masterclass in academic positioning, intentionally distancing the field from the limitations of 'cybernetics' to create a distinct, ambitious, and globally recognized brand.