Anthropomorphism and AI: Turingʼs much misunderstood imitation game

By Diane Proudfoot. 2011

110 citations recorded by the source corpus.

The widespread tendency, even within AI, to anthropomorphize machines makes it easier to convince us of their intelligence. How can any putative demonstration of intelligence in machines be trusted if the AI researcher readily succumbs to make-believe? This is (what I shall call) the forensic problem of anthropomorphism. I argue that the Turing test provides a solution. This paper illustrates the phenomenon of misplaced anthropomorphism and presents a new perspective on [email protected]?s imitation game. It also examines the role of the Turing test in relation to the current dispute between human-level AI and 'mindless intelligence'.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Philosophy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Iason Gabriel
2. Gavin Abercrombie
3. Amanda Cercas Curry
4. Tom Everitt
5. Geoffrey Irving
6. Vladimir Mikulik
7. Laura Weidinger
8. Zachary Kenton

In Computational Theory and Mathematics

1. Iason Gabriel
2. Tom Everitt
3. Geoffrey Irving
4. Zachary Kenton

In Philosophy

1. Iason Gabriel
2. Vladimir Mikulik
3. Tom Everitt
4. Geoffrey Irving
5. Zeerak Talat
6. Zachary Kenton
7. Laura Weidinger

Citations in the corpus

• Alignment of Language Agents (2021, background): “• Undue trust being placed in the system, especially as it communicates with humans in natural language, and could easily be mistaken for a human (Proudfoot, 2011; Watson, 2019).”
• Anthropomorphism in AI (2020, background): “Indeed, from Turing’s descriptions of his machines (Proudfoot 1999, 2011) to recent accounts of AlphaZero’s intellectual feats (Strogatz 2018) it is not uncommon to find researchers using terms typically used to describe human skills and capacities when referring to AIs and focusing on alleged simil”
• Anthropomorphism: Opportunities and Challenges in Human–Robot Interaction (2014, background): “This is the forensic problem of anthropo-morphism – the problem of how we are reliably able to detect intelligence in machines, given that the tendency to anthro-pomorphize leads us to find intelligence almost everywhere [110,112].”
• Mirages: On Anthropomorphism in Dialogue Systems (2023, background): “Though intelligence and understanding should not be conflated with systems that exhibit humanlike behaviour (Bender and Koller, 2020), the human tendency to anthro-pomorphise convinces us of a machine’s apparent intelligence (Proudfoot, 2011).”