The Forecast

Jack Clark, co-founder of Anthropic and author of the Import AI newsletter, published in Import AI 455 his estimate that there is approximately a 30% chance AI research becomes substantially automated by end of 2027, rising to over 60% by end of 2028.

The Core Argument

Clark argues AI research automation doesn't require genius-level creativity. Much of the research cycle — running experiments, iterating on hyperparameters, writing and reviewing code, synthesizing results — is systematic enough that current AI systems are already contributing meaningfully. The key evidence: the speed at which AI has moved from coding assistance to actual research participation.

The Self-Improvement Loop

If AI can participate in AI research, the logical extension is models helping generate training data and contributing to training the next generation — a recursive improvement dynamic where each model generation is partly designed by its predecessor.

Community Reaction

The r/singularity community was divided. Skeptics argued genuinely novel AI research still requires human insight current systems cannot replicate. Optimists pointed to the rapid progression from GPT-3 to today's models as evidence the timeline could be even shorter. Clark's quantified estimate is notably rare among AI lab leaders.

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Anthropic Co-Founder: 30% Chance AI Automates AI Research by End of 2027