GRF · Innovation Nexus
Innovation and society
Innovation raises productivity and opens new possibilities, but its gains and costs are not shared evenly. Automation reshapes work, digital platforms reorder markets, and access to new technologies follows income, place, gender and age. This page sets out how the social effects of innovation develop and accumulate, how inequality in adoption and benefit is measured, and what the labour, education, competition and social institutions that hold the decisions need from the evidence.
Innovation and society on the record.
Innovation and society: how the risk develops.
Inequality and social impacts. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Tasks change before jobs
New technologies automate some tasks and create others. Workers whose tasks are routine lose bargaining power before jobs disappear, and transition costs fall on them unless institutions share them.
Leading firms pull ahead
Digital markets with network effects and low marginal cost reward leading firms. Gaps in productivity and pay between frontier firms and the rest can widen even as the average rises.
Access follows advantage
Connectivity, skills and money decide who uses new services first. Those left out can lose access to public services as these move online, turning a digital divide into a service divide.
Trust shapes uptake
People adopt what they trust. Harms that are visible and unaddressed, from biased decisions to data misuse, slow beneficial uses and harden public opposition to whole technologies.
How innovation and society is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Policy instrument matrix
The kinds of instrument available on innovation and society, by level of government and cooperation.
| Instrument type | Local | National | Regional | Global |
|---|---|---|---|---|
| Regulatory | Zoning, building codes | Laws, standards, licensing | Harmonised rules | Conventions and treaties |
| Economic | Local levies, grants | Budget lines, taxes, insurance schemes | Risk pools, regional funds | Financing mechanisms |
| Information | Local warnings | Disclosure, early warning, statistics | Data sharing arrangements | Global monitoring and reporting |
| Institutional | Local committees | Lead agencies, coordination councils | Regional bodies and secretariats | Multilateral mandates |
| Cooperative | Community agreements | Partnership compacts | Memoranda and joint programmes | Agreements and joint commitments |
What is measured, and how well.
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 |
|---|---|---|---|---|
| Individuals with basic or above basic digital skills | percent of individuals by age, sex and income | biennial | Household ICT usage surveys | Published statistics |
| Households with broadband access | percent of households | annual | Household surveys and regulator data | Published statistics |
| Employment in occupations with high task exposure to automation | percent of employment | periodic | Labour force surveys with task models | MODELLED |
| Productivity gap between frontier and other firms | ratio of labour productivity | annual | Firm-level microdata | ESTIMATED |
| Women among inventors on patent applications | percent of inventors | annual | Patent databases with name-gender matching | ESTIMATED |
| Public trust in science and new technology | percent of respondents | periodic | Attitude surveys | REPORTED |
| Adult participation in learning | percent of adults in the reference period | periodic | Adult education and labour force surveys | Published statistics |
Where the evidence comes from.
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 |
|---|---|---|
| Eurostat ICT usage in households and by individuals | Digital skills, internet use and use of online public services by group | Open, attribution (Eurostat reuse policy) |
| ITU World Telecommunication/ICT Indicators Database | Connectivity and access indicators by country | Licensed, ITU terms; key indicators free |
| ILOSTAT (International Labour Organization) | Employment, occupations and earnings by country | Open, attribution |
| OECD Survey of Adult Skills (PIAAC) | Literacy, numeracy and problem-solving skills of adults | Open, attribution (OECD terms); microdata by access |
| WIPO data on gender and innovation | Women's participation as inventors in international patent applications | Free, WIPO terms |
| Special Eurobarometer surveys on science and technology | Public attitudes to science, AI and emerging technologies | Free reuse, attribution |
Who decides, and what the evidence serves.
Innovation 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 |
|---|---|---|
| Ministries of labour and social affairs | How to support workers through task change: retraining, income support and transition services | Task exposure estimates with method stated; comparative reviews of transition policies |
| Education and skills authorities | Where to invest in digital and adult learning, and for whom | Skills and participation indicators by group and region |
| Competition authorities | Whether market power in digital markets limits entry and the spread of gains | Productivity gaps; concentration evidence in relevant markets |
| Telecommunications regulators and digital government agencies | How to keep public services reachable for people offline or with low digital skills | Access and skills gaps by group and place; service channel records |
Outputs this topic produces
- Distributional maps of adoption, skills and access by group and place
- Transition scenario sets for occupations with high task exposure, with assumptions stated
- Comparative reviews of labour, skills and social protection responses to automation
- Dialogue designs that bring affected groups into technology governance
What experts ask.
The core question is who gains, who loses and who decides.
- How does a technology change the demand for different skills and kinds of work?
- Who gains access to new products and services, and who is excluded by cost, connectivity or design?
- How are the gains from innovation shared between workers, firms, consumers and regions?
- Does automation of decisions affect fairness, privacy or due process?
- How do affected people take part in decisions about technologies that change their lives?
Mechanisms and drivers.
Technologies tend to complement some skills and substitute for others. Historically, gains in productivity have come with periods of disruption for particular occupations and places. Whether gains are broadly shared depends on institutions: education and training systems, labour market policies, competition policy, social protection and taxation.
Access gaps arise where innovations require infrastructure, money or skills that not everyone has. Design choices matter too: systems trained or tested on narrow populations may work less well for others. Trust is a social effect in its own right; when people feel innovation is done to them rather than with them, resistance and backlash can follow.
Why now: public acceptance has become a deciding factor for technologies from AI to gene editing, and acceptance depends on whether people feel heard before deployment. Innovation Nexus convenes deliberation that includes affected communities and records dissent alongside agreement.
How it is studied, and where the methods stop.
| Method or data | What it shows | Limits |
|---|---|---|
| Labour market and task analysis | Exposure of occupations to technological change | Exposure does not equal job loss |
| Distributional analysis | How gains and losses fall across groups | Long-run effects are hard to isolate |
| Algorithmic audits | Fairness of automated systems | Access to systems and data is often restricted |
| Participatory and deliberative methods | Public values and priorities | Small groups may not represent everyone |
How it is studied, and what the methods cannot say.
- 01Policy, institutional and decision scienceMandate and gap mapping · Programme evaluation design · Comparative regulatory analysisApplied here
- 02Artificial intelligence and machine learningCoding policy and legal texts · Mapping patents and papers to technologiesApplied here
- 03Systems engineeringRequirements traceability for AI governance · Readiness gates for transfer programmesApplied here
Questions and answers.
Will new technologies reduce total employment?
What is task exposure?
Does Innovation Nexus take positions on labour policy?
Does innovation always increase inequality?
Why involve affected people?
Does the platform take positions on particular technologies?
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