The Product Experience Rerun: AI ethics advice from former White House technologist - Kasia Chmielinski (Co-Founder, The Data Nutrition Project)
Dec 24, 2025
Kasia Chmielinski dives into the fast-evolving world of AI ethics and data quality. She emphasizes the importance of balancing innovation with responsibility, especially within large organizations like the UN. By advocating for marginalized users, she encourages product managers to redesign processes to be more inclusive. Discover the intriguing concept of nutrition labels for datasets, enhancing transparency and quality. Kasia also addresses ethical challenges in product management, offering compelling strategies for overcoming these dilemmas.
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PM Trade-Offs Shape Long-Term Bias
- Product management's focus on rapid value maximization creates design decisions that become a product's long-term DNA.
- Those early trade-offs often embed exclusions that later surface as bias or misuse.
Close Feedback Loops After Launch
- If you join a product midstream, build real feedback loops and show users the launched product to get meaningful post-launch feedback.
- Monitor usage and change the product over time instead of treating launch as the end point.
Refuse Or Redirect Harmful Requests
- Refuse to build products you believe are harmful, or research and propose an alternative that solves the same problem.
- Use that redirect tactic to steer stakeholders toward safer, practical solutions when a straight refusal isn't viable.