The Global Centre for Risk and Innovation (GCRI)
Information ecosystems decide what people know about risk: which warnings reach them, which claims they believe and which institutions they trust. This lab studies news, platforms, recommender systems, synthetic media and verification practice, and tests media innovations before they scale. This page sets out how misinformation and information gaps develop and spread, how interventions are evaluated, and who decides on the evidence.
Future of media lab · Field lab coast · Campaign 3
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| S-01 tide | 95 | 0.3 | Nominal |
| S-04 salinity | 86 | 0.8 | Recalibrate |
| S-07 wave | 90 | 0.1 | Nominal |
Fig.Testbed operations. Design wireframe with placeholder names and illustrative values, not a record or a live system.
Misinformation research studies how false or misleading information spreads, who believes it and what reduces its harm. It covers news, platforms, recommender systems, synthetic media and verification practice, and tests interventions such as corrections and prompts before they scale, since some backfire.
For future of media lab, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, population density, night lights and land cover, framed on World; every other NASA layer, live feed and forecast waits in the layer list.
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For future of media lab, in GCRI's spatial-intelligence reading, the map opens on true-colour imagery, population density, night lights and land cover, framed on World; 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
Information ecosystems and responsible media 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.
Ranking systems optimise for engagement, and content that provokes strong reactions can travel further. Small changes in ranking rules alter what large audiences see, which makes platform design a research object in its own right.
Generated images, audio and video can impersonate people and events cheaply. Provenance standards and detection help, but neither is complete, and the existence of fakes also lets genuine evidence be dismissed.
Where local journalism closes, fewer sources report on councils, courts and hazards. Gaps are filled by rumour or partisan content, and trust in institutions shapes how warnings are received when they arrive.
Labels, corrections, prebunking and friction aim to reduce false beliefs. Effects measured in surveys may fade, may not change behaviour, or may raise scepticism of accurate content too, which is why field evaluation matters.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Truth discernment | The ability to tell true from false claims, measured as the gap in belief between them. |
| News desert | A community with little or no local news coverage. |
| Researcher data access | Provisions, such as Article 40 of the EU Digital Services Act, that give vetted researchers access to platform data. |
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 |
|---|---|---|---|---|
| Exposure to flagged content | proportion of impressions | per study | Platform researcher data access | OBSERVED |
| Belief accuracy | proportion of true and false claims correctly rated | per study | Survey experiments | OBSERVED |
| Truth discernment | difference between belief in true and false items | per study | Survey experiments | ESTIMATED |
| Trust in news | percent of respondents | annual | Audience surveys | REPORTED |
| Provenance credential coverage | percent of published media carrying provenance data | annual | Publisher and platform audits | OBSERVED |
| Local news coverage | news outlets per local area | annual | News outlet census | ESTIMATED |
| Researcher data access granted | count of approved access requests | annual | Platform transparency reports | 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 |
|---|---|---|
| Reuters Institute Digital News Report (University of Oxford) | Cross-national survey of news use, trust and platform reliance | Report free access; data by request |
| Media Pluralism Monitor (European University Institute) | Risks to media pluralism by country and area | Open access, attribution |
| DSA Transparency Database (European Commission) | Statements of reasons for content moderation decisions by platforms | Free and open, EU reuse terms |
| Code of Conduct on Disinformation transparency centre | Signatory reports on measures against disinformation | Free access, terms of use |
| GDELT Project | Global news event and tone records from monitored media | Free and open, attribution |
| ClaimReview records (Google Fact Check Tools) | Structured fact checks published by verification organisations | Terms of use |
Nexus Labs 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 |
|---|---|---|
| Media and communications regulators | Whether platform risk assessments and mitigation measures meet legal duties | Independent audits, transparency database records, researcher access evidence |
| Newsroom editors and publishers | Whether to adopt a verification, labelling or provenance practice | Field evaluations of the practice with audience and trust outcomes |
| Platform trust and safety teams | Which interventions to deploy at scale and how to monitor side effects | Randomised evaluations with effects on accurate as well as false content |
| Public health and emergency communicators | How to issue warnings that reach, and are believed by, different audiences | Reach, trust and comprehension evidence by audience group |
Information spreads through networks of people and platforms. Network science shows that a few highly connected nodes can make diffusion fast and that clustering can create communities where some claims circulate and others do not. Platform design adds feedback: content that draws engagement is shown more, and engagement does not track accuracy.
Trust is a central variable. During disasters and health emergencies, people combine official warnings with what they hear from family, local leaders and online sources. Where trust in institutions is low, accurate warnings may be ignored and rumours fill the gap. Misinformation, shared in error, and disinformation, shared deliberately, have different drivers and call for different responses.
Generative AI lowers the cost of producing convincing text, images, audio and video. This affects both the volume of misleading content and the credibility of genuine evidence, which can be dismissed as fabricated.
Mapping how material moves across accounts and platforms. Platform data access is restricted and changes, which limits replication.
Measuring trust, exposure and belief over time. Self-reports are imperfect and samples may miss key groups.
Testing labels, corrections and warning formats under ethics review. Laboratory effects may differ from real-world use.
Testing tools that identify synthetic media, using machine learning methods. Detection is an arms race and accuracy declines as generators improve.
Research on information is itself sensitive. The lab is designed to protect participant privacy, avoid amplifying harmful content and respect freedom of expression.
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.