Summary of Language Models Are Alignable Decision-makers: Dataset and Application to the Medical Triage Domain, by Brian Hu et al.
Language Models are Alignable Decision-Makers: Dataset and Application to the Medical Triage Domain
by Brian Hu, Bill Ray, Alice Leung, Amy Summerville, David Joy, Christopher Funk, Arslan Basharat
First submitted to arxiv on: 10 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 addresses the challenge of conflicting opinions among expert decision-makers in difficult scenarios. The authors introduce a novel dataset for medical triage decision-making, labeled with attributes that characterize individual decision-makers’ ethical principles and moral desert. They propose a software framework for human-aligned decision-making using these attributes, enabling trustworthy AI with better guardrails. Specifically, they show how large language models (LLMs) can serve as ethical decision-makers, aligning their decisions to different attributes using zero-shot prompting. The authors experiment with various open-source LLMs, including Falcon, Mistral, and Llama 2, and introduce a weighted self-consistency technique that improves overall performance. The results provide new research directions for using LLMs as alignable decision-makers. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to make important decisions with others, but you all have different opinions. This can be really hard! In this paper, scientists try to solve this problem by creating a special kind of data and software that helps people work together better. They do this by using big computers called language models that can think like humans. These computers can help make decisions based on what’s important to us, like fairness and being fair. The scientists tested these ideas with different computer models and found some ways to make them work better. This could be really helpful in the future for making big decisions. |
Keywords
» Artificial intelligence » Llama » Prompting » Zero shot
