# #350 How to Make Hard Choices in AI with Atay Kozlovski, Researcher at the University of Zurich

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Podcast: [DataFramed](https://stenobird.com/podcast/dataframed)
Published: 2026-03-09T09:00:00+00:00
Episode link: https://www.datacamp.com/podcast
Audio file: https://dts.podtrac.com/redirect.mp3/cohst.app/pdcst/6G1A6D/episodes.captivate.fm/episode/0d3f89e9-4b0e-4671-819a-1a413f0951e5.mp3
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Duration seconds: 4226

## Resource

As AI systems gain autonomy, the tension between efficiency and human control intensifies. This discussion explores the ethical frameworks needed to prevent systemic failures in high-stakes sectors like healthcare, welfare, and warfare.

## Highlights
- Main idea: Responsibility requires a moral agent; AI systems cannot be held morally accountable for their actions
- Failure mode: Automation bias and 'dual-use' technologies can lead to discriminatory policing and welfare fraud errors
- Practical takeaway: Implementing 'meaningful human control' requires tracing decisions back to human-understandable reasons
- Risk factor: The deployment of high-stakes tools without oversight disproportionately harms vulnerable populations
- Critical skill: Maintaining epistemic diversity and seeking out opposing viewpoints is essential to avoid algorithmic bubbles

## Topics

AI Ethics, Meaningful Human Control, Algorithmic Bias, Deepfakes, Automation Bias, Digital Twins, Dual-use Technology, Normative Ethics

## Chapters
- 1:00 — The Paradox of Autonomy: Examining the contradiction between increasing AI autonomy and the necessity of human moral responsibility.
- 11:30 — Systemic Failures in High-Stakes AI: Analyzing how errors in military and welfare automation lead to real-world harm and loss of human rights.
- 16:50 — Tracing and Accountability: Discussing the technical and ethical requirements for ensuring AI decisions are traceable and justifiable.
- 27:20 — Designing for Safety in Healthcare: A look at how intentional design constraints can prevent automation bias in clinical settings.
- 38:00 — The Ethics of Digital Twins: Exploring the implications of using personalized data to create highly realistic human simulations.
- 1:04:40 — The Future of AI Research: Reflecting on the tension between academic inquiry and the lucrative influence of big tech corporations.

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## Transcript

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