Summary of Concept Induction Using Llms: a User Experiment For Assessment, by Adrita Barua et al.
Concept Induction using LLMs: a user experiment for assessment
by Adrita Barua, Cara Widmer, Pascal Hitzler
First submitted to arxiv on: 18 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 proposes a novel approach to Explainable Artificial Intelligence (XAI) by leveraging Large Language Models (LLMs) like GPT-4 to generate high-level concepts that provide transparent insights into AI models. The authors use prompting with minimal textual object information to facilitate concept discovery, comparing the results with human-generated explanations and the ECII heuristic concept induction system. The study finds that while human-generated explanations remain superior, LLM-generated concepts are more comprehensible to humans than those generated by ECII. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand how we can make artificial intelligence (AI) more transparent and easy to understand. Right now, AI models are very good at doing things like recognizing pictures, but they’re not very good at explaining why they made certain decisions. This is a problem because humans need to be able to trust the decisions that AI makes. The authors of this paper explore an idea called “concept-based” models that try to understand complex concepts in order to provide better explanations. They use a special type of language model, called GPT-4, and ask it to generate high-level concepts that can be used as explanations for humans. The results show that while human-generated explanations are still the best, the AI-generated concepts are more understandable than those generated by other methods. |
Keywords
» Artificial intelligence » Gpt » Language model » Prompting
