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What Should ChatGPT Mean for Bioethics?

I Glenn Cohen1

  • 1Petrie-Flom Center for Health Law Policy, Biotechnology & Bioethics, Harvard Law School.

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Summary
This summary is machine-generated.

Large Language Models (LLMs) like ChatGPT present familiar bioethics challenges, such as data privacy and bias, alongside new concerns like AI disclosure and deepfakes. Ethical considerations must guide LLM development to ensure equitable access and prevent risks.

Keywords:
ChatGPTbiasenvironmentinformed consentlarge language model (LLM)oligopolyprivacy

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Area of Science:

  • Bioethics
  • Artificial Intelligence
  • Medical Ethics

Background:

  • The rapid advancement of Large Language Models (LLMs) like ChatGPT necessitates an examination of their implications across various professional fields, including medicine.
  • Existing bioethical frameworks address many AI-related concerns, providing a foundation for evaluating new technologies.
  • The unique characteristics of LLMs introduce novel ethical considerations beyond those of current medical AI applications.

Purpose of the Study:

  • To explore the potential impact of ChatGPT and similar LLMs on the field of bioethics.
  • To identify both recurring and novel ethical issues arising from the integration of LLMs in healthcare and research.
  • To propose a framework for addressing these ethical challenges proactively.

Main Methods:

  • Review and analysis of existing bioethical principles and their applicability to LLMs.
  • Identification and categorization of ethical issues raised by LLMs in a medical context.
  • Comparative analysis of ethical challenges posed by LLMs versus traditional medical AI.

Main Results:

  • Many bioethical issues, including data ownership, consent, bias, and privacy, are mirrored in LLM applications, though with distinct nuances.
  • Novel ethical concerns highlighted include informed consent for AI interaction, the potential for medical deepfakes, and risks of market oligopoly and inequitable access.
  • The pursuit of technological dominance may overshadow crucial ethical considerations, impacting global health equity and environmental sustainability.

Conclusions:

  • Existing bioethical frameworks offer a valuable starting point for addressing LLM-related challenges in medicine.
  • New ethical considerations, such as transparency in AI use and equitable access to foundational models, require urgent attention.
  • Proactive ethical deliberation and regulation are essential to harness the benefits of LLMs while mitigating potential harms in bioethics.