AGI Strategies

compare

Two strategies, side by side.

Pick any two strategies. See who endorses each, the tier mix of endorsers, the p(doom) distribution, and which people endorse both. Useful for asking are these strategies actually opposed, or does this disagreement live in builders, in policy, or in the public square.

Stance defaults to live engagement: endorses, mixed, conditional, or evolved-toward. These are people who treat the strategy as a live bet of theirs at any time. Opposers are listed separately.

Open source

37 endorsers · 0 oppose

Release weights widely; transparency beats closed safety

expertise mix

Builds frontier systems
3
Deep ML / safety technical
3
Applied or adjacent technical
0
Governance, policy, strategy
1
Expert in another field
0
Public-square commentator
1

recognition mix

Mass-public recognition
4
Known across the AI/safety field
4
Recognised inside subfield
0
Newer or less central voice
0

profiled

8/37

mean p(doom)

25%

n=2

quotes

41

AI skeptic

81 endorsers · 2 oppose

AGI risk narratives overstated; real harms are mundane and current

expertise mix

Builds frontier systems
1
Deep ML / safety technical
20
Applied or adjacent technical
1
Governance, policy, strategy
2
Expert in another field
10
Public-square commentator
1

recognition mix

Mass-public recognition
16
Known across the AI/safety field
18
Recognised inside subfield
1
Newer or less central voice
0

profiled

35/81

mean p(doom)

0%

n=1

quotes

97

where the disagreement lives

Tier shares within profiled endorsers. Positive shift means the tier is over-represented in Open source; negative means it's over-represented in AI skeptic.

Open source skews these tiers

  • Frontier builder+35pp
  • Commentator+10pp

AI skeptic skews these tiers

  • External-domain expert+29pp
  • Deep technical+20pp
mean p(doom)Open source: 25% (n=2)vsAI skeptic: 0% (n=1)Δ +25.0%

endorse both (2)

Open source only (35)

AI skeptic only (79)