Data Skeptic
Do LLMs Make Ethical Choices
Oct 16, 2023
Josh Albrecht, CTO of Imbue, discusses the limitations of current language models (LLMs) in making ethical decisions. The podcast explores imbue's mission to create robust and safe AI agents, the potential applications and limitations of AI models, and the need for improvements in LLMs. The speakers also touch on reevaluating metrics, liability for AI systems, and societal issues in machine learning research.
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Quick takeaways
- LLMs, despite their superhuman performance, are not suitable for making ethical decisions due to their sensitivity to word choice and lack of physical reasoning abilities.
- Evaluating LLMs should go beyond traditional accuracy measurements and include metrics like worst case accuracy, framing effects, and adversarial examples to develop reliable and useful models.
Deep dives
Unsuitability of LLMs for Ethics and Safety Decisions
Current large language models (LLMs) exhibit superhuman performance in ethics data sets, but their suitability for ethical decision-making is questionable. LLMs show high accuracy in answering ethical questions when compared to human performance. However, they are sensitive to word choice and can be easily tricked or influenced by slight perturbations in the inputs. LLMs lack physical reasoning abilities and may miss the implications of certain scenarios. Despite achieving high accuracy in in-domain tasks, LLMs struggle with out-of-domain examples and adversarial scenarios. These limitations suggest that LLMs, as currently developed, are not reliable for making ethical decisions.
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