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.
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.
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.