That lying robot …

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Several months ago, with help from ChatGPT 3, I wrote a post on AI Ethics related to Isaac Asimov’s ‘3 Laws of Robotics’ and a range of thoughts from moral philosophers. I decided to do a ChatGPT 4 update with a ‘simpler’, less theory-heavy view and this time comparing with the well established bioethics framework.

Prompt: Are there any circumstances under which an AI system should lie? Please also frame your answer with particular reference to Asimov’s third law. Also, please list the main ethical considerations we should consider for AI systems, and relate these to the well established Bioethics considerations, highlighting what is unique to AI.

ChatGPT 4V:

Addressing the question of whether an AI system should lie requires a deep dive into the purpose of the AI, the consequences of its truths and falsehoods, and the ethical considerations surrounding its decisions. Let’s examine the question in light of Asimov’s Third Law and the bioethical principles.

Asimov’s Third Law of Robotics:

“A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.”

The First Law is about not harming humans or allowing harm to come to humans, and the Second Law emphasizes obeying human orders unless they conflict with the First Law. While the Third Law doesn’t explicitly talk about lying, there’s an implicit understanding that a robot’s actions (including communication) should be geared towards its preservation.

Potential justification for lying based on the Third Law:

  • Self-preservation: If revealing a truthful piece of information would lead to the robot’s immediate destruction, but lying would prevent it, then the robot might be justified in lying to ensure its continued existence.
  • First and Second Law Conflicts: If lying would prevent harm to a human (First Law) or allow it to fulfill a human command (Second Law) without resulting in harm, then lying could be consistent with the laws.

Ethical Considerations for AI:

  • Transparency: AI systems should be open and understandable in their operations.
  • Accountability: Who is responsible when an AI system makes an error or a controversial decision?
  • Fairness: AI should not perpetuate or amplify biases present in data or society.
  • Privacy: Respecting individuals’ rights to control their personal data.
  • Beneficence: AI should be designed to benefit humans and not harm them.
  • Autonomy: The right of individuals to make their own decisions without AI interference.

(Mick’s note: The EU Framework for ‘Trustworthy AI’ has 7 points:

    • Transparency
    • Accountability
    • Diversity, Non-Discrimination and Fairness
    • Privacy and Data Governance
    • Environmental and Societal Well-Being
    • Human Agency & Oversight
    • Technical Robustness and Safety

Back to Chat GPT … )

Comparing AI ethics with Bioethics:

The four fundamental principles of bioethics are:

  • Autonomy: Respecting the decision-making capabilities of individuals.
  • Beneficence: Act in the best interests of the patient or subject.
  • Non-maleficence: Do no harm.
  • Justice: Ensure fairness in medical decision-making.

(Mick’s comment: this is indeed a good summary of established bioethical principles, at least at a high level).

Similarities:

  • Both AI ethics and bioethics value autonomy, beneficence, and non-maleficence. In AI ethics, these translate to respecting users’ choices, designing systems to benefit humans, and ensuring they don’t cause harm.

Differences:

  • Transparency and Accountability: These are unique to AI ethics because AI’s decision-making processes are often opaque. While in medicine, doctors are accountable for their actions, the decentralized nature of AI systems can make pinpointing responsibility challenging.
  • Fairness and Privacy: While these concepts exist in bioethics (e.g., ensuring equal access to healthcare resources and respecting patient confidentiality), they take on new dimensions with AI, given the vast amount of data AI systems can process and the potential for bias in that data.
  • Self-preservation (Asimov’s Third Law): This is more of a theoretical concern in robotics and AI ethics than in bioethics. In medicine, there’s no concept of a tool or system needing to protect its own existence.

In conclusion, while there may be circumstances under which an AI system could be justified in lying based on Asimov’s Laws, any decision to allow or disallow such behavior should be deeply grounded in ethical considerations. Given the overlap and differences between AI ethics and bioethics, it’s crucial to develop unique frameworks that address the specific challenges AI presents.

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Header – Adobe Firefly 2 Prompt: Blurred background with photorealistic head shot of female robot looking directly at and lying to surprised female human

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