Doom or Bloom
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Demis Hassabis

Demis Hassabis

@demishassabis on X

Enormous scientific promise, with rigorous standards and coordinated care.

Map your own worldview

How will AI change the world?

100500DoomBloom
ConcernHope
Simulated positionInterpretation range

Across: his expressed Doom–Bloom outlook. Up: scale of transformation.

Doom–Bloom: 66 out of 100. Scale of transformation: 73 out of 100. Interpretation ranges: 50 to 75 horizontally, 44 to 100 vertically. These are interpretation coordinates, not event probabilities.

Demis Hassabis’s estimated P(doom)

≈18%

0%100%

Inferred from his broader worldview and priorities. Approximate interpretation range: 0–65%. Applies to the outcome and conditions in his simulated answers; this is an inferred percentage.

Demis Hassabis’s milestone timeline
  1. Science & daily life

    Over the next several years, I expect the deeper change to come through science.

    Answer 3

Grouped by milestone, not spaced or ordered by inferred dates. AGI and superhuman AI retain his definitions.

What his outlook hinges on

A central assumption

Better AI can accelerate that cycle enormously, while experiments and human judgment remain bottlenecks.

Answer 1

If this assumption turned out differently, how would his outlook change?

An unresolved question

I do not attach a precise probability to catastrophe, but the risk is nonzero and non-negligible.

Answer 1

What would help him distinguish the plausible outcomes here?

More details

Expected upside

Substantial benefits are expected, with important conditions or distribution limits.

80 / 100

Little impactTransformative impact

Interpretation range 67 to 100 on the qualitative scale.

Expected harm

Severe or widespread harm is a material expected part of the future.

63 / 100

Little impactTransformative impact

Interpretation range 33 to 67 on the qualitative scale.

Demonstrated reasoning

Reasoning, consideration of alternatives, and handling of uncertainty in his simulated answers. This describes the simulated answers, not the real person’s intelligence or opinions.

88 / 100

Little demonstratedWell developed

Interpretation range 76 to 95 on the qualitative scale.

Human influence

Human choices have meaningful but substantially constrained influence.

57 / 100

Little influenceStrong influence

Interpretation range 49 to 76 on the qualitative scale.

Development pace

Stop or substantially slow development of more capable AI.

Simulated position: Continue development under stated safeguards.

Speed up development of more capable AI.

Rules for using AI

Restrict the AI uses discussed until prior protections or permission are in place.

Simulated position: Allow the AI uses discussed with targeted accountability and protections.

Minimize restrictions on the AI uses discussed.

These interpretations keep his stated conditions. Benefits and harms can both be substantial. The ranges describe how we read his simulated answers, not statistical confidence intervals.

Simulated Assessment

Sources

Sources for this persona’s current brief.

The day after AGI: Hassabis and Amodei at Davos

Artificial general intelligence (AGI) is that point in the future when the machines can do pretty much everything better than humans. When will it happen, what will it look like, and what will be the impact on humanity? Two of the brightest minds working in AI today, Demis Hassabis, Co-Founder and CEO of Google DeepMind, and Dario Amodei, Co-Founder and CEO of Anthropic, speak to Zanny Minton Beddoes, Editor-in-Chief of The Economist. Benjamin Larsen, an expert in AI at the World Economic Forum, introduces the conversation and gives us a primer on AGI.

weforum.org

Lex Fridman: science, human flourishing and AI risk

This is a transcript of Lex Fridman Podcast #475 with Demis Hassabis. The timestamps in the transcript are clickable links that take you directly to that point in the main video. Please note that the transcript is human generated, and may have errors. Here are some useful links: Go back to this episode’s main page Watch the full YouTube version of the podcast Table of Contents Here are the loose “chapters” in the conversation. Click link to jump approximately to that part in the transcript: 0:00 – Episode highlight 1:21 – Introduction 2:06 – Learnable patterns in nature 5:48 –

lexfridman.com

A framework for frontier AI and the dawning of a new age

A dynamic approach to testing frontier AI model capabilities that supports innovation, incentivizes responsible behavior, and helps safely steward AGI.

institute.deepmind.com
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