Ethical Machines Orchestrating Ethics
Nov 13, 2025
In a thought-provoking conversation, David Danks, a Professor of Philosophy and Data Science known for his work on AI ethics, explores the crucial concept of ethical interoperability. He discusses the risks of differing ethical standards when companies integrate AI models from multiple sources. Danks emphasizes the need for case-by-case ethical alignment and the challenges of accountability in AI deployment. He also delves into how transparency and operational clarity can enhance ethical assessments, urging firms and governments to recognize mismatched ethical practices.
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Ethical Interoperability Defined
- Ethical interoperability names the problem that different builders and integrators may have conflicting ethical standards.
- Distributed AI development requires matching ethical expectations across organizations before deployment.
The Risk Of Ethical Outsourcing
- Relying on another party's ethics creates a risk of 'ethical outsourcing' where responsibility is evaded.
- Organizations may pick partners with weaker ethics and claim compliance by proxy.
MSG Facial Recognition Example
- David Danks uses an example of face recognition at venues like Madison Square Garden to show allocation of responsibility.
- He asks whether the model builder, deployer, or venue bears ethical responsibility for wrongful detentions.