Research

What changes for scientific research with AI?

Who's accountable when a product decision is made on synthetic-user data that turns out not to reflect real users?

Is hypothesis generation still a scientist's job when AI systems can propose and rank novel hypotheses themselves?

How does lab structure change when one PI plus AI agents can do the throughput that used to require five postdocs?

How do we measure research team impact when "insights delivered" is no longer a scarce output?

Should research ops still gatekeep access to real participants now that synthetic panels are the default first pass?

Is the paper still the right unit of scientific output when AI can generate them faster than humans can read them?

Is peer review still meaningful when a meaningful share of reviews at major venues are already AI-generated?

What's the point of training PhD students on tasks an AI agent already does end to end?

Is synthesis (turning transcripts into themes) still a research skill worth having when AI does it in seconds?

Do I still need to run real user interviews when synthetic users can simulate them in minutes?

Is replication/verification now the scarce, valuable skill that hypothesis generation used to be?

What changes for user research with AI?