LEADERSHIPOngoing practice85% confidence

Institutions as the Trust Layer

When formats become fakeable, trust migrates to institutions — not better formats

Problem it solves

Predicting how societies will respond to AI-generated deepfakes using historical pattern

Best for

Understanding the long-term demand for institutional verification infrastructure; explaining why epistemic collapse from deepfakes is not inevitable; identifying where decentralized verification infrastructure becomes structurally necessary

Not ideal for

Short-term signals or tactical decisions

Overview

Why this framework exists

Harari identifies a recurring historical pattern: when a communication technology becomes fakeable or manipulable, trust does not collapse permanently and does not migrate to a 'better' format — it migrates to the institution behind the format. With writing, anyone could put words on paper. Trust migrated to institutions with reputation at stake: The Guardian, The Times, The Wall Street Journal. People don't believe something because it is written — they believe it if it appears on the front page of the New York Times, because they trust the institution, not the paper or the ink.

With video, the format was previously unfakeable, so it was trusted on its format alone. 'If we saw a video, we said ah, this has to be true.' AI deepfakes break that assumption. Harari's prediction, drawn from the historical pattern: the same transition that happened with print will happen with video. 'We are still not used to it. So when we see a video of Donald Trump or Joe Biden, the video still gets to us because we grew up in a time when it was impossible to fake it. But I think very quickly people will realize: you can't trust videos, you can only trust the institutions.'

The democratic stakes: if institutional trust itself collapses — if the institutions that certify content are themselves captured, corrupted, or destroyed — the result is not a neutral epistemic landscape. Harari's argument is that 'if you can't believe anything, this is the ideal for dictators. Democracy works on trust but dictatorship works on terror and fear. You don't need to trust anything in a dictatorship — you fear.' Epistemic collapse is not neutral; it is structurally favorable to authoritarian power.

Core principles

5 total
  1. When a communication format becomes fakeable, trust migrates to institutions — not to better formats
  2. Institutional trust is more durable than format trust because it is backed by reputation, accountability, and accumulated track record
  3. Epistemic collapse is not neutral — it is structurally favorable to authoritarian power that operates through fear rather than trust
  4. The current transition period (video becoming fakeable) mirrors the historical transition when writing became widely accessible
  5. The second-order problem — AI becoming the bureaucracy — requires decentralized, cryptographically verifiable certification infrastructure

Steps

4 steps
  1. Identify the current trust mechanism for any information format
    Determine whether trust in a format is format-based (video, because video was unfakeable) or institution-based (The New York Times, because institutions have accountability). Format-based trust is fragile once fakeability is achieved; institution-based trust persists as long as institutional integrity holds.
    Pro tipTest: would you believe this content if it appeared on a random website versus on the front page of an established institution you trust? The delta reveals how much of the trust is format-based versus institution-based.
  2. Apply the historical pattern to predict trust migration
    When a format becomes fakeable, predict that trust will migrate to institutions rather than collapsing permanently. Identify which institutions are positioned to certify content in the new environment, and assess their integrity and independence. The transition period — before the new trust architecture is established — is the highest-risk period.
    WarningThe transition period can be exploited by actors who benefit from epistemic chaos. The historical pattern shows the trust architecture eventually stabilizes, but the intervening period can cause significant political and social damage.
  3. Assess institutional integrity in the current environment
    Evaluate whether the institutions that would serve as the trust layer are themselves under threat — from political pressure, financial capture, regulatory attack, or public trust erosion. The institution-as-trust-layer answer only holds if institutions maintain their independence and integrity.
    Pro tipThe democratic stakes are asymmetric: institutional capture or collapse does not produce a neutral epistemic landscape — it produces conditions structurally favorable to authoritarian power.
  4. Identify the second-order certification problem
    When AI becomes the bureaucracy that certifies content, ask who certifies the AI certifiers. The institution-as-trust-layer answer requires a further layer of verification that is not capturable by any single actor. Cryptographically verifiable, decentralized verification infrastructure addresses this second-order problem structurally rather than through trust in any particular human institution.
    WarningCentralized AI certification infrastructure — operated by governments or major platforms — reproduces the capture risk at a deeper level than human institutional capture.

Checklist

Saved in your browser

Examples

2 cases
Print media trust migration

When writing became widely reproducible (printing press, then mass literacy), anyone could put words on paper. The format — written text — became unreliable as a trust signal. Trust migrated to institutions with accountability: established newspapers and publishers whose reputation was staked on their editorial decisions. The institution, not the format, became the trust carrier.

OutcomeDemonstrates the historical pattern: format-trust collapse does not produce permanent chaos, but produces institution-based trust as the stable resolution. The parallel predicts the same transition for video as deepfakes make the format unreliable.
Venezuela as elected-to-authoritarian capture

Harari cites Venezuela as the proximate historical example of how democratic institutions can be captured by an elected leader who changes the rules of the game from within. The precondition: once epistemic trust in democratic institutions erodes sufficiently, the population cannot coordinate to resist the capture because they cannot agree on what is true.

OutcomeIllustrates the democratic stakes of institutional trust collapse — not abstract epistemic concern, but concrete historical precedent for authoritarian capture of functioning democracies within a single political generation.

Common mistakes

3 traps
Assuming epistemic collapse is the end state
The historical pattern shows that format-trust collapse does not produce permanent epistemic chaos — it produces a transition to institution-based trust. Assuming deepfakes will produce irreversible epistemic collapse misreads the historical pattern. The real question is which institutions survive and emerge as the new certification layer.
Treating the transition period as the stable state
The current moment — where video is becoming fakeable but new institutional trust architecture hasn't fully formed — is a transition period, not a stable equilibrium. Policy and investment decisions should account for where the trust architecture is heading, not only where it is now.
Ignoring the second-order certification problem
Stopping at 'institutions will certify content' without asking who certifies the institutions — and eventually, who certifies the AI institutions — leaves the framework incomplete. The second-order problem is where decentralized, non-capturable infrastructure becomes necessary.

Origin story

How this framework came to be

This framework emerges from Harari's historical methodology: when facing an apparently novel technological challenge, identify whether history has produced analogous transitions and what the resolution pattern looked like. The writing-to-institution trust migration is well-documented; Harari applies it to video as a predictive tool.

The framework's most important extension is the second-order question Harari names but leaves unresolved: 'Will those bureaucratic institutions be AI?' As AI becomes the bureaucracy that certifies content, the institution-as-trust-layer answer requires a further layer — who certifies the AI certifiers? This is where cryptographically verifiable, decentralized verification infrastructure becomes structurally necessary, not ideologically preferred.

Source

Traced to primary
Source · PODCAST
Yuval Noah Harari: They Are Lying About AI! The Trump Kamala Election Will Tear The Country Apart!
Yuval Noah Harari · 2024
Open source →

Related frameworks

Browse all Leadership →