AI literacy
Know what the tools can do, where they fail, and how to verify them.
AI & HUMANITY · EVIDENCE OVER HYPE
The future is moving.
Understand what matters.
A living research project tracking what AI can actually do, what remains uncertain, and how humans can prepare without surrendering judgment, creativity or agency.
KNOWN measured evidenceUNCERTAIN open questionsSPECULATION possible futures
LATEST · SEPTEMBER 2026 · AI SECURITY
THE QUESTION
What happens when AI can find software vulnerabilities on its own?
Researchers tested coding agents against real Android apps using executable security probes. The capability is real. The leap to “autonomous hackers” is not.
Current agents can discover and trigger genuine software vulnerabilities in controlled real-world app environments.
Explore the full evidence →ALL RESEARCH
Questions, not predictions.
Every published evidence brief, labeled by the question it investigates.
AI SECURITY · SEP 2026 · LATEST
Can AI find software vulnerabilities on its own?
Real capability, benchmark limits, and the attacker–defender race.
Explore evidence →WORK · RESEARCHWill AI take your job—or change how careers begin?
Evidence on exposure, entry-level work, productivity and adaptation.
Explore evidence →AI RISK · RESEARCHCould advanced AI pose catastrophic risk?
What expert assessments and current evidence can—and cannot—tell us.
Explore evidence →FUTURE SCENARIO EXPLORER
Don't bet on one future.
Prepare across several.
These are scenarios, not forecasts. We deliberately avoid fake precision. Select a path to see its evidence status, potential impact and preparations that remain useful even if the scenario is wrong.
Gradual AI integration
AI becomes a normal layer inside software and work. Many tasks change faster than entire occupations disappear.
ROBUST PREPARATION
Become AI-capable inside a real domain.
Learn where AI genuinely improves your work, strengthen judgment and domain knowledge, and keep building skills that let you verify machine output.
We show evidence strength rather than invented probability percentages. Long-range AI outcomes are too uncertain for precise personal forecasts.
PREPARE WITHOUT PREDICTING
Five moves that survive multiple futures.
Real expertise
Build domain knowledge AI can amplify rather than replace with shallow output.
Financial flexibility
Maintain room to adapt if work, industries or opportunities change quickly.
Human networks
Trust, relationships, reputation and collaboration remain valuable across scenarios.
Ownership & agency
Create, build, invest, decide and retain the ability to act rather than only consume.
HOW WE THINK
Evidence has layers.
What happened?
Start with measured results, primary research and documented deployments.
What doesn't it prove?
Expose benchmark limits, confounders, missing data and alternative explanations.
What should we watch?
Explore plausible implications without quietly turning forecasts into facts.
THE HUMAN QUESTION
As machines become more capable, what should humans become?
This project isn't about cheering for AI or fearing it. It's about staying awake to the transition: learning what is real, preparing for what is plausible, and protecting the parts of human life worth carrying forward.