Article Links Published by Neil Raden on Issues of AI Ethics on Diginomica: 2019–2021

1. Here’s looking at you, kid — the problematic adoption of facial recognition systems

2. Can AI be an effective tool against disinformation and hate speech? A geopolitical view

3. The last mile in AI deployment — answering the top questions

4. How AI ethics falls short — preserving jobs is not enough

5. AI and human rights — a different take on an old debate

6. The last mile in AI deployment — where the biggest risks (and payoffs) happen

7. AI ethics is growing up — towards an AI maturity model organizations can use

8. How did a proprietary AI get into hundreds of hospitals — without extensive peer reviews? The concerning story of Epic’s Deterioration Index

9. Why is AI harder than we think?

10. AI ethics have consequences — learning from the problem of autonomous weapons systems

11. Statistical bias in context — AI didn’t invent quantitative methods of bias

12. The US National Security Commission issues its “Final Report on AI in Defense and Intelligence” — here are the takeaways

13. Is fairness in AI a practical possibility? A new angle on designing ethical systems

14. In search of trustworthy AI — is the insurance industry using AI to fairwash FICO scores?

15. AI doesn’t explain itself — machine learning has a “Deus ex Machina” problem

16. The problem of algorithmic opacity, or “What the heck is the algorithm doing?”

17. Can fairness be automated with AI? A deeper look at an essential debate

18. Robot empowerment — a viable alternative to Asimov’s three laws of robotics?

19. Can we measure fairness? A fresh look at a critical AI debate

20. Can fairness be automated with AI? A deeper look at an essential debate

21. Revisiting ethical AI — where do organizations need to go next?

22. Revisiting ethical AI, part two — on data management, privacy, and the misunderstood topic of bias

23. The fragility of privacy — can differential privacy help with a probabilistic approach?

24. AI inevitability — can we separate bias from AI innovation?

25. Unethical AI unfairly impacts protected classes — and everybody else as well

26. AI ethics — why teaching ethics and “ethics training” is problematic

27. Rethinking AI Ethics — Asimov has a lot to answer for

28. Moral licensing, AI teams, and you — a problem yet to be reckoned with