SuperFuturesAtlas of Human Futures

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Biopolitical Control | SuperFutures

SuperFuturesAtlas of Human Futures

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Scenario 29Emerging

Biopolitical Control

Genetic Governance

Also known as Genetic Governance · Algorithmic Eugenics · Computational Biopolitics

AI monitors, predicts, and controls biological populations: tracking health, predicting behavior, managing reproduction based on biological data.

Type: Dystopian
Time horizon: Near-term
Human position: Passive
Framing: Pessimistic

AI gives states unprecedented power over biological populations through prediction, scoring, and resource allocation based on bio-behavioral data.
Central thesis

Overview

AI + genomics + biometrics + behavioral prediction enables population management more precise and pervasive than any precedent.

Classification

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Geographic concentration: Global; most advanced in countries with strong biometric infrastructure
Tags: health
governance
security
Scenario type (full): Dystopian / Governance scenario
Human position: Subordinated; managed as biological populations, not autonomous agents
Time horizon: Near to mid term (0–15 years); building on existing infrastructure

SuperFutures— a structured atlas of the scenarios imagined for humanity’s long-term future.

Discourse status

Emerging; partially underway in health surveillance and predictive policing

Impacts

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Mechanism: Convergence of AI analytics, genomic databases, biometric surveillance, health monitoring, and predictive behavioral modeling.
Domain impacts: Labor & Income Workers evaluated on predictive health and behavioral models. Education Students sorted by AI predictions of ability. Governance & Democracy States use biological data for population management. War & Security Predictive policing based on biological and psychological data. Inequality & Class Biological data becomes discrimination source. Culture & Art Self-optimization intensifies; biological conformity rewarded. Meaning & Purpose Life becomes performance of health metrics. Family & Reproduction Reproductive decisions influenced by genetic scoring. Health & Longevity Comprehensive but surveillance-oriented. Rights & Agency Fundamental: bodily autonomy, genetic privacy, reproductive freedom. Environment Population management may include biological resource allocation. Existential Survival Low extinction; high loss of bodily autonomy.

Discourse

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Key proponents: Analytical frameworks: Foucault (biopolitics), Harari (‘dataism’ warnings), bioethicists
Key institutions: Council of Europe, WHO, privacy advocacy organizations
Critiques: Legal frameworks prevent this; biological data too noisy; health AI can be deployed ethically.

Pop culture

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Pop-culture references: Film: Gattaca (1997), Minority Report (2002). TV: Black Mirror ‘Nosedive’, Psycho-Pass (2012–19, anime). Literature: Aldous Huxley, Brave New World (1932); Margaret Atwood, The Handmaid’s Tale (1985); Kazuo Ishiguro, Never Let Me Go (2005).
Cultural note: High cultural footprint when combined with surveillance and genetic scenarios. Gattaca, Brave New World, and The Handmaid’s Tale together form a powerful cultural triptych about biological control.

Acceptance

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Key assumptions: Assumes biological data is predictive enough; assumes states will use it for control; assumes legal protections fail.
Primary audiences: Bioethicists, genetic privacy advocates, disability rights, critical theorists

Personas

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Persona 1: The Genetic Privacy Advocate – Campaigns against employer genetic data access.
Persona 2: The Health-Optimized Citizen – Shares all biological data willingly; doesn’t perceive threat.
Hard-believer profile: Name & Age: Dr. Ananya Sharma, 40. Occupation: Bioethicist and genetic privacy researcher; advises multiple governments on health data governance. Location: New Delhi, India. Core Conviction: India has the world’s largest biometric database (Aadhaar). When you add AI analysis of genomic, health, and behavioral data, you get the most precise system of population management in history. Biggest Fear: That health AI systems become mandatory and biological data determines access to employment, insurance, education, and reproduction. Biggest Hope: That strong legal frameworks prevent the worst applications while allowing beneficial health AI to flourish.

References

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Canonical texts: Foucault, ‘The Birth of Biopolitics’ (1978-79 lectures) Harari, ‘Homo Deus’ (2016)
Further references: Michel Foucault, The Birth of Biopolitics (lectures 1978-79). Yuval Noah Harari (2016), Homo Deus, Harvill Secker. Gattaca (1997). WHO health data governance guidelines.

A scene from this future

The Profile

A clinic, approximately 2037

The screen at the employment agency showed Priya’s Biological Fitness Score: 74.

She didn’t know all the inputs. Genomic risk factors. Biometric history. Exercise patterns from her smartwatch. Sleep data. Dietary analysis from her grocery purchases. Mental health indicators inferred from her social media and communication patterns. A family medical history that went back three generations.

The score determined her job tier. Tier 1 (85+) got the best positions: creative, managerial, client-facing. Tier 2 (70-84) got mid-level roles. Tier 3 (below 70) got monitored positions with mandatory wellness programs.

Priya was Tier 2. She knew her score was dragged down by her father’s diabetes and her own history of mild depression, which she’d disclosed to a therapist three years ago in confidence that turned out to be a legal fiction.

She applied for a marketing position. The system suggested she might be “better suited” to data entry. Better suited. She stared at the phrase and felt the full weight of a world that knew her body better than she did and had already decided what it was worth.

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