The Global Risks Forum (GRF)
Artificial intelligence, biotechnology and other emerging technologies change faster than the rules that govern them, and their risks cross sectors and borders. Technology policy covers how governments set rules, standards, oversight and public investment for innovation while protecting safety, rights and security. This page sets out how regulatory risk develops around new technologies, how governance capacity is measured, and which institutions hold the decisions.
GRF · Established · service level R0
Technology policy is how governments set rules, standards, oversight and public investment for emerging technologies such as artificial intelligence and biotechnology, while protecting safety, rights and security. These technologies change faster than rules and cross sectors and borders, which creates the pacing problem and gaps between jurisdictions.
For technology policy, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water with place names and borders from NASA GIBS, framed on Africa; every other NASA layer, live feed and forecast waits in the layer list.
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For technology policy, in GRF's situational-awareness reading, the map opens on population density, night lights and flood water with place names and borders from NASA GIBS, framed on Africa; 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.
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The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Technology policy · Member state A · Session 3
| A · guidance only | 38 | Low | Mixed | High |
| B · duty with standards | 67 | Medium | Positive | Medium |
| C · duty, standards, funding | 78 | High | Positive | Low |
AI, biotechnology and innovation. 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 evolve within months while legislation takes years. Rules written for one generation of technology misfit the next, leaving gaps where harms emerge and overlaps where developers face conflicting obligations.
A single AI system or biotechnology product may fall under data protection, product safety, sector regulators and export controls at once. Divergent national approaches create regulatory arbitrage and uneven protection.
Developers know far more about capabilities and failure modes than regulators do. Without disclosure duties, access for testing and technical capacity in supervisory bodies, oversight relies on what firms choose to share.
Knowledge and tools built for benefit can be misused, and they diffuse across borders through publication, trade and openly released models. Controls at one point are bypassed at another unless they are coordinated internationally.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Pacing problem | The gap that opens when technology develops faster than the laws and institutions that govern it. |
| Experimentation clause | A legal provision allowing time-limited exceptions to test new technologies under supervision. |
| Dual use | The capacity of a technology or research to be used for both beneficial and harmful purposes. |
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 |
|---|---|---|---|---|
| National AI strategies and policy initiatives | count of initiatives by instrument type | continuous | OECD.AI national policy database | DECLARED |
| Designated supervisory authority for AI or emerging technology | yes or no, with mandate | periodic review | National legislation and gazettes | OFFICIAL |
| Regulatory sandboxes and experimentation clauses | count of active schemes by sector | annual | Regulator registers | OFFICIAL |
| Public consultation on draft technology rules | share of draft rules consulted, with consultation period in days | annual | Regulatory impact assessment registers | OFFICIAL |
| Regulatory quality | estimate and percentile rank | annual | World Bank Worldwide Governance Indicators | ESTIMATED |
| Biosafety and biosecurity legal framework coverage | categorical, by function | periodic review | WHO and Biological Weapons Convention national reporting | DECLARED |
| Science, technology and innovation policy instruments | count by instrument type and target group | periodic | EC-OECD STIP Compass | DECLARED |
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 strategies, policy initiatives and governance bodies | Open, CC BY 4.0 |
| EC-OECD STIP Compass | Science, technology and innovation policy initiatives reported by governments | Open, CC BY 4.0 |
| EUR-Lex | Legislative texts of the European Union, including the AI Act, with consolidated versions | Free reuse with attribution under the Commission reuse decision |
| Biological Weapons Convention confidence-building measures | State Party declarations on facilities, programmes and legislation, where made public | Public portion, UN terms |
| WIPO Lex | National intellectual property laws and treaties | Free, WIPO terms |
| National regulatory impact assessment registers | Published impact assessments and consultation records for technology rules | Public sector information, national terms |
Policy 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 |
|---|---|---|
| National legislatures | Whether to legislate horizontally across technologies or through sector rules | Comparative review of legislative approaches and their impact assessments |
| Sector and digital regulators | How to supervise AI systems and biotechnology products within existing mandates | Supervisory practice compared across jurisdictions; capacity and disclosure requirements |
| Data protection authorities | How data protection law applies to model development and deployment | Published decisions and guidance compared across authorities |
| Ministries of foreign affairs and trade | Which technologies to control for export, and how to coordinate controls with partners | Records of multilateral control regimes and treaty obligations |
Technology policy experts ask how to govern what is not yet fully understood.
Technologies such as AI and biotechnology develop faster than legislative and regulatory processes. Early on, little is known about risks, so regulation risks being either premature or too late. Once a technology is embedded, it becomes harder to change. This dilemma has led to approaches such as risk-based regulation, regulatory sandboxes, mandatory testing and disclosure, and adaptive rules that are revisited as evidence accumulates.
Technology policy also involves strong economic and geopolitical interests. Concentration of capabilities in a few firms or countries raises competition and security questions. Divergent national rules can fragment markets or push activity to less regulated jurisdictions, while coordinated standards can raise the floor of safety everywhere.
Comparing technology rules across jurisdictions with policy and institutional science. Rules are new and evolving.
Designing incentives and institutions for safe development using game theory and mechanism design. Models simplify real behaviour.
Exploring possible developments with decision analysis. Scenarios are not predictions.
Structured exchange through policy dialogues. Views of affected groups must be sought deliberately.
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.