AI for Good Global Summit · Geneva
Leveraging gen AI for human-rights work
Building transparent, testable human-rights tools — and teaching people to use gen AI well.
Łukasz Szoszkiewicz, PhD
Adam Mickiewicz University, Poznań · Expert to the AI and Education Group, Council of Europe
↓ Scan to explore the tools ↓
The shift
AI makes execution thin — the weight moves to deciding & delivering
EXECUTE shrinks
Writing and debugging code used to be the bottleneck. AI makes that layer thin — but it still has to be checked (coding assistants can also introduce vulnerabilities).
DECIDE grows
What should the tool do? What's the unit of analysis? What to exclude? This is where domain expertise becomes decisive.
DELIVER is the point
Easier to build → benchmarks matter more, not less (grounded in legal scholarship). The goal: tools that support implementation, not just more data.
How to navigate
Jagged intelligence — a skill you have to keep re-learning
- AI ability is uneven. Brilliant at one task, surprisingly weak at a neighbouring one. The capability frontier is jagged, not a smooth line — competence doesn't transfer where you'd expect.
- The only way to navigate it is experimenting. Every model behaves differently; each new generation has to be re-learned. Working with AI effectively is a skill — not something we can take for granted.
- But once you learn it, you can move mountains. One of the tools on the poster — HRC Voting — was built in a single evening with a cutting-edge model.
Responsible AI use isn't only about the model — it's about the workflow: decide what matters, build the safeguards, define the benchmarks.