The Global Risks Forum (GRF)
Emerging and converging technologies, from artificial intelligence and synthetic biology to quantum computing and space systems, change faster than the institutions that govern them. Their futures are shaped by research, investment, standards, regulation and public acceptance together. This page sets out how technology foresight works, why impacts are hard to anticipate before a technology is locked in, and which institutions hold the decisions on research funding, standards, regulation and export controls.
GRF · Established · service level R0
Technology foresight is the structured exploration of how emerging and converging technologies, from artificial intelligence and synthetic biology to quantum computing and space systems, may develop and be governed. Their futures are shaped together by research, investment, standards, regulation and public acceptance, and breakthroughs resist point prediction.
For technology futures, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water with clouds now from NASA GIBS, framed on the Arctic; every other NASA layer, live feed and forecast waits in the layer list.
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For technology futures, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water with clouds now from NASA GIBS, framed on the Arctic; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
Layers and dates
Emerging and converging technology. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Technologies seldom change the world alone. Advances in computing, biology, materials and data combine in ways that no single field anticipates, and the consequential futures often sit at their intersections.
Early in a technology's life its impacts are hard to foresee but it is easy to shape; once impacts are clear, it is embedded in markets, infrastructure and habits and is hard to change. Anticipatory governance works in that early window.
Expectations rise and fall faster than capability. Foresight that follows attention tends to overstate near-term change and understate long-term change; diffusion depends on cost, complements, skills and regulation, not capability alone.
Standards, liability rules, export controls and safety regimes lag capability. Gaps open between jurisdictions and between regulators whose mandates were drawn for earlier technologies.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Technology convergence | The combination of technologies from different fields into new capabilities. |
| Collingridge dilemma | The difficulty that a technology is easiest to shape before its effects are known. |
| Forecast resolution | The point at which a forecast question can be scored against what happened. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Patent families in emerging technology classes | count of families | annual | Patent office records | OFFICIAL |
| Research publications in emerging fields | count of articles | annual | Bibliometric databases | OBSERVED |
| Government budget allocations for research and development | national currency per year | annual | Budget statistics | OFFICIAL |
| Technology readiness assessments | technology readiness level | per assessment | Structured expert assessment | ESTIMATED |
| Reported incidents involving AI systems | count of incidents | monthly | Incident databases | REPORTED |
| Regulatory and standards instruments adopted | count of instruments | quarterly | Policy and standards trackers | OFFICIAL |
| Accuracy of resolved technology forecasts | Brier score | per question set | Forecasting platform records | REPORTED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| OECD.AI Policy Observatory | National AI policies, research and investment indicators across countries | OECD terms, free with attribution |
| Stanford AI Index | Annual compilation of research, technical performance, investment and policy data on AI | CC BY-ND 4.0 |
| WIPO PATENTSCOPE and WIPO Technology Trends | Patent records and technology landscape studies | WIPO terms of use |
| AI Incident Database (Responsible AI Collaborative) | Public records of harms and near-harms involving AI systems | Open access, database terms |
| OECD Main Science and Technology Indicators | Research spending, personnel and patent indicators by country | OECD terms, free with attribution |
| arXiv metadata | Preprint records for tracking the emergence of research fronts | CC0 for metadata |
| Metaculus and Good Judgment Open question records | Public forecasts on technology milestones with resolution records | Platform terms of use |
Foresight Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Science, technology and innovation ministries | Where public research funding should anticipate convergence rather than follow single fields | Bibliometric and patent evidence on emerging fronts, with expert readiness assessments and their uncertainty |
| AI, data protection and telecommunications regulators | Which emerging uses fall outside current mandates and need guidance or rules | Incident records, capability trajectories and the governance gaps they reveal |
| Standards bodies and national standards institutes | When a technology is mature enough for a standard and what it should cover | Readiness assessments, diffusion scenarios and the interests of affected parties |
| Trade and export control authorities | Which dual-use technologies need controls and how to review them as capability moves | Technology trajectories, convergence maps and forecasts with their track records |
Technological change rarely follows a straight line. Many technologies pass through cycles of inflated expectations and disappointment before finding lasting uses, while others arrive faster than expected when costs fall or complementary technologies mature. Convergence, such as artificial intelligence applied to biology or materials science, can accelerate change in unexpected directions.
Governance faces a well-known dilemma: early in a technology's life, its effects are hard to foresee but easy to shape; later, effects are clear but the technology is entrenched. Anticipatory governance responds by building foresight, public engagement and adaptive regulation into the early stages of development. Regulatory sandboxes, staged approvals and review clauses are examples of tools that let rules evolve as evidence accumulates.
Tracking research, patents, investment and deployment to assess maturity and pace.
Structured methods such as Delphi gather and compare expert judgements on timelines and impacts.
Exploring how technologies could interact with social and economic forces, using scenario design and stress testing.
Expert timelines are often wrong in both directions, adoption depends on social and economic factors that are hard to predict, and commercial interests can shape available information.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.