Summary of The Human and the Mechanical: Logos, Truthfulness, and Chatgpt, by Anastasia Giannakidou and Alda Mari
The Human and the Mechanical: logos, truthfulness, and ChatGPT
by Anastasia Giannakidou, Alda Mari
First submitted to arxiv on: 2 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper examines whether ChatGPT models can be considered “mechanical minds” and argues against this notion by highlighting the importance of veridicality judgments in human communication. It posits that these judgments are formed through a combination of exogenous evidence related to reality and endogenous evidence such as preferences and private beliefs, which mechanical minds lack. The paper suggests that while ChatGPT models can mimic veridicality judgments, their outputs are not grounded in the same foundations as human beliefs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper asks if it’s okay to talk about “mechanical minds” and whether AI chatbots like ChatGPT can really think for themselves. The answer is no – these machines lack something called “veridicality judgments”. This means they can’t form their own opinions or decisions based on what’s true or not. Instead, they just copy human thoughts without understanding the reasons behind them. |
