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Asia 2035 ยท ASEAN AI FuturesEdition C. Public draft

About

An independent regional scenario project

Contributors write in their personal capacities. The project accepts no conditional funding and publishes its assumptions and limits.

Scenario ID A2035Horizon 2025 to 2035Region ASEANEdition C
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Purpose

Mission

Asia 2035 is an independent scenario project on AI, semiconductors, energy, and cognitive labour in ASEAN. Much of the detailed public work on transformative AI futures treats the region as the hardware backdrop to a two-power race. This project treats ASEAN countries as actors with decisions of their own.

The project makes questions about compute, labour, sovereignty, and governance concrete enough to argue about, plan around, and act on before 2035.

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Contributors

Team and advisors

Roles are listed by function. Named attribution is published as contributors confirm it, alongside their disclosure statements.

Regional research lead

Scenario direction and narrative

Independent, Jakarta

Semiconductor & packaging advisor

Hardware bottleneck accounting

Industry practitioner, Penang

Labour economist

Cognitive-labour exposure and transition modelling

University-affiliated, Bangkok

Energy systems analyst

Grid, water, and datacentre siting constraints

Independent, Kuala Lumpur

AI governance researcher

Evaluation, disclosure, and control mechanisms

Independent, Singapore

Workforce transition practitioner

BPO transition programme design

Industry practitioner, Manila

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Commitments

Funding and independence

  • Contributors participate in their personal capacities. Institutional affiliations are listed for context and do not imply institutional endorsement.
  • The project accepts no funding from frontier AI developers, hyperscale cloud providers, or semiconductor manufacturers, and does not accept funding conditioned on findings, framing, or review rights.
  • All assumptions, parameter ranges, and limitations are published. Where the project is uncertain, it says so. Where it is making a judgement call, it names it as one.
  • Corrections are welcome and are published rather than quietly applied.
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Acknowledgements

Credits and inspiration

This project borrows its structure from public AI-futures scenario work: long-form forward-conditioned narratives, transparent parameters, and published methodology. Its text, assets, and code are original.

Exposure estimates referenced in the narrative draw on published international labour research on generative AI and occupational task profiles. Datacentre and packaging capacity characterisations draw on public industry reporting and national energy planning documents.