Summary of Acting For the Right Reasons: Creating Reason-sensitive Artificial Moral Agents, by Kevin Baum et al.
Acting for the Right Reasons: Creating Reason-Sensitive Artificial Moral Agents
by Kevin Baum, Lisa Dargasz, Felix Jahn, Timo P. Gros, Verena Wolf
First submitted to arxiv on: 23 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: 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 proposes a novel approach to reinforcement learning by enabling agents to make moral decisions based on normative reasons. The architecture involves a reason-based shield generator that produces a moral shield, binding the agent to actions that conform with recognized normative reasons. This ensures the agent’s actions are internally morally justified. Furthermore, the authors describe an algorithm for iteratively improving the reason-based shield generator through case-based feedback from a moral judge. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes artificial intelligence better by teaching machines how to make good decisions based on what is right and wrong. The idea is to create a “moral shield” that stops the machine from doing things that go against what we consider morally acceptable. To do this, the researchers developed a special system that looks at reasons why certain actions are good or bad. This helps the machine learn from its mistakes and make better choices in the future. |
Keywords
* Artificial intelligence * Reinforcement learning
