Ethics Oversight

How public money is shaping the future of AI

An analysis of the EU’s investment in AI development reveals a significant mismatch between EU’s ambition in leading on responsible AI and allocation of its own funds to deliver on this objective.

AI Fundings · Ethics Oversight · AI Ethics

The European Union aims to become the “home of trustworthy Artificial Intelligence” and has committed the biggest existing public funding to invest in AI over the next decade. However, the lack of accessible data and comprehensive reporting on the Framework Programmes’ results and impact hinder the EU’s capacity to achieve its objectives and undermine the credibility of its commitments. 

This research commissioned by the European AI & Society Fund, recommends publicly accessible data, effective evaluation of the real-world impacts of funding, and mechanisms for civil society participation in funding before investing further public funds to achieve the EU’s goal of being the epicenter of trustworthy AI.

Abstract
Key Concepts

Among its findings, the research has highlighted the negative impact of the European Union’s investment in artificial intelligence (AI). The EU invested €10bn into AI via its Framework Programmes between 2014 and 2020, representing 13.4% of all available funding. However, the investment process is top-down, with little input from researchers or feedback from previous grantees or civil society organizations. Furthermore, despite the EU’s aim to fund market-focused innovation, research institutions and higher and secondary education establishments received 73% of the total funding between 2007 and 2020. Germany, France, and the UK were the largest recipients, receiving 37.4% of the total EU budget.

The report also explores the lack of commitment to ethical AI, with only 30.3% of funding calls related to AI mentioning trustworthiness, privacy, or ethics. Additionally, civil society organizations are not involved in the design of funding programs, and there is no evaluation of the economic or societal impact of the funded work. The report calls for political priorities to align with funding outcomes in specific, measurable ways, citing transport as the most funded sector in AI despite not being an EU strategic focus, while programs to promote SME and societal participation in scientific innovation have been dropped.

European Fundings

Readour report


Full Report

10bn

amount invested by the EU into AI from 2014-2020, 13.4% of all available funding

73%

amount that went to research and educational establishment institutions between 2007 and 2020

37.4%

amount that went to Germany, France and the UK between 2007 and 2020

1/5

proposals funded that were focused purely on technological development without application

A top-down system, with little space for SMEs

The European Commission has been dominant in AI funding, which has resulted in a supply-led-innovation system, with money directed from the top down rather than the bottom up. This approach does not acknowledge AI demand trends or competitiveness, and while public funding can support initiatives where the market is not willing to engage, the rigidity of framework programs and lack of consultation may hinder the development of AI that benefits society.

Also, the concentration of funding in established research centers and specific geographies like France, Germany or the UK, raises the question of whether EU investment reflects the innovation landscape. Do universities receive more funding because that is where the most innovative work in AI is taking place? What is the space of SMEs within this landscape?

A techno-solutionist approach, without proper evaluation

There is a tendency towards techno-solutionism in AI development, and issues of trustworthiness and responsibility are not integrated into most of the calls for proposals that are being funded by the EU.

On the other hand, there is a concerning lack of meaningful impact indicators and evaluation in the EU’s funding programmes.

The EU’s evaluation measures have clear methodological flaws, such as assessing impact solely in relation to the call topic and domain, and oversight mechanisms focusing on the fulfillment of contractual obligations rather than actual results and overall impact. Without a strategic approach to evaluation and impact indicators, the EU’s funding programmes risk becoming a hollow process of devolution of funds to Member States without any strategic direction or regional positioning.

Lack of investment on innovation

At the moment, there is a lack of a clear strategy and direction for EU innovation, despite substantial changes made every 5-7 years to the pillars and domains of the Framework Programme (FP). The EU funding efforts still prioritize research actors but at a decreasing rate. Private sector investments prioritize areas such as AI and big data, manufacturing, and life sciences.

The EU should explore and fund areas not covered by private investment funds and align political strategic priorities with funding outcomes in measurable ways. There is a need to translate commitments to a human-centric AI model into specific data governance and engineering requirements, and the ethics review process needs to be emphasized, as well as to include the civil society in both the design or receipt of funding to represent the public interest in AI development.

Between the lines

Keeping all these findings in mind,Eticas recommends:

  • Transparency: the EU institutions need to make public all data on public funding mechanisms and outcomes in ways that allow for systematic analysis and research.

 

  • Metrics: the EU Commission needs to develop and implement impact assessments that address the economic and societal impacts of the research they are funding.

 

  • Inclusion: the EU institutions and Member States need to create mechanisms to incentivise the participation of civil society in funding, to ensure that the public interest is represented in the development of AI.

Consolidating the space carved out by the EU and taking specific steps towards trustworthy AI, will require an effort to contribute to the future of AI in ways that serve people and society.