Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15 · primary
Themes: Closed vs. Open Split · Safety Debate
Compute, not algorithms or talent, decides who can compete at the frontier.
Overall my view is that AI is *structurally* a technology that tends to concentrate power, for reasons that have nothing to do with regulation (more to do with the extreme implications of the scaling laws). Open-weights do help some with this but are nowhere near a sufficient solution because they simply shift the concentration somewhat to those with the most compute and chips (which are roughly the frontier labs plus maybe hardware providers).
Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15
Capable models should be required to pass pre-release testing, binding open weights and closed APIs alike.
BTW I do not think that the events of the last few months have “failed to result in [my] preferred regulatory path”. The approach that the Trump administration is reported to be taking — pre-deployment testing for frontier models, and also testing of open-weights models when they get closer to the frontier — is one that I am very supportive of, though of course I have to see the details to be sure. I am also supportive of Demis Hassabis’ ideas around a FINRA-like entity.
Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15
Open models keep AI continually available, rather than dependent on any one provider's decisions.
Open weights commoditise the model layer, moving durable value to distribution, data, and the infrastructure underneath.
Open weights prevent AI from being controlled by a few actors, because anyone can run them.
A coordinated slowdown is worth pursuing even at the cost of advantage, because uncoordinated speed is the greater risk.
This is why Anthropic has always made its policy proposals very carefully. We try very hard to make proposals that disadvantage (slow down) frontier AI companies while *advantaging* smaller competitors. California’s SB53 (which we supported), and even the much-maligned SB 1047 (which we were ambivalent on), completely exempt any company below a certain amount of revenue or model training costs from being covered at all (it was $500M for SB 53, lower for 1047 but we objected to that).
Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15
AI regulation in practice concentrates power in the largest labs rather than constraining them.
First, on regulation, I think that “either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely” is a false choice. I know that there’s a sort of Silicon Valley shorthand where regulation = regulatory capture = concentration of power, but I’ve always found this to be an overly simplified picture of the world. Many people outside this bubble think of regulation as something that constrains corporate power and benefits ordinary people.
Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15
# Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker
Regulation and Messaging — Dario Amodei's X Reply to Gavin Baker · 2026-08-15
Open models move the binding scarcity to hardware — compute, chips and the networking between them.
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