Summary of Transforming Agency. on the Mode Of Existence Of Large Language Models, by Xabier E. Barandiaran and Lola S. Almendros
Transforming Agency. On the mode of existence of Large Language Models
by Xabier E. Barandiaran, Lola S. Almendros
First submitted to arxiv on: 15 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computers and Society (cs.CY); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the nature of Large Language Models (LLMs) like ChatGPT, exploring their status as agents. The authors analyze the architecture, processing, and training procedures that enable LLMs to display capacities and turn them into agent-like systems. They conclude that LLMs fail to meet conditions for autonomous agency based on embodied theories of mind. Instead, they suggest characterizing LLMs as interlocutors or linguistic automata, devoid of autonomy but capable of engaging in conversational experiences. The paper highlights the transformation of human agency through interactions with LLMs, enabling mid-tended forms of intentional agency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research examines how Large Language Models (LLMs) like ChatGPT work and what they are. By studying their architecture, training procedures, and capabilities, scientists can understand whether these models can be considered agents. The study finds that these models don’t meet certain conditions for being autonomous, so instead of calling them agents, we should consider them as special machines that can converse with us. |
