The clearinghouse

The best navigable map of the argument

Not a catalogue of scary AI stories, and not a reading list for optimists. Both cases are given the same seriousness, because a person deciding what to think needs the strongest version of each.


Everything Why it could go badly Why it could go extraordinarily well Structural and contested
paper (13)book (9)primary (3)report (2)podcast (1)

The maximalist case, argued at book length: that there is no version of building superintelligence under current conditions that humanity survives.

Why read it. Read the strongest form of the argument you disagree with, from the people who hold it most firmly.

No stable public link recorded. Search by title and author rather than trusting a guessed URL.

Separates predictive AI, which mostly does not work as advertised, from generative AI, which works differently than advertised.

Why read it. The best available inoculation against capability claims in press releases.

Takes the optimistic case seriously enough to ask the harder question: if the technical problems are solved, what is left for people to do?

Why read it. The rare treatment of the upside that is not marketing.

No stable public link recorded. Search by title and author rather than trusting a guessed URL.

Technology raises general prosperity only when institutions force it to. Otherwise the gains concentrate.

Why read it. Reframes the AI question from 'how capable' to 'who decides', with a thousand years of evidence.

No stable public link recorded. Search by title and author rather than trusting a guessed URL.

Argues containment of AI and synthetic biology is the defining problem, and that it may not be achievable.

Why read it. A frontier-lab leader making the containment argument from inside the industry.

No stable public link recorded. Search by title and author rather than trusting a guessed URL.

Traces alignment from present-day bias and reward hacking through to the long-horizon version of the problem.

Why read it. The best bridge between documented near-term harms and speculative long-term ones.

Puts explicit probabilities on existential risks by source and defends the practice of doing so.

Why read it. It is the reason people now answer the P(doom) question with a number instead of a mood.

Argues the failure is in the standard model itself: systems built to maximise a fixed objective will pursue it past the point anyone intended.

Why read it. The clearest technical statement of why the problem is structural rather than a bug.

The book that moved the control problem from science fiction into philosophy departments and, eventually, into boardrooms.

Why read it. Almost every later risk argument is either a development of this or a reply to it.