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Observatori d'Ètica en Intel·ligència Artificial

Blog Post OEIAC - Moving towards AI for Social Good: European National Strategies

Atia Cortés (and Francesca Foffano, Teresa Scantamburlo)

Artificial Intelligence (AI) has become a driving force in modern research, industry and public administration and the European Union (EU) is embracing this technology with a view to creating societal, as well as economic, value. This effort has been shared by EU Member States which were all encouraged to develop their own national AI strategies outlining policies and investment levels. Our paper “Investing in AI for Social Good: An Analysis of European National Strategies” (1) focuses on how EU Member States are approaching the promise to develop and use AI for the good of society through the lens of their national AI strategies. In particular, the objective of our research is to investigate how European countries are investing in AI and to what extent the stated plans contribute to the good of people and the society as a whole.

Over the last years, we have observed a prevalent interest to move towards the achievement of AI for social good, which spans a variety of stakeholders and actions including public events, scientific publications, movements and organisations special programmes. Our work starts by providing a conceptualization of the notion of “AI for social good”, where we introduce three possible and complementary definitions. The first interpretation regards AI for Social good “as applications”, where the objective is to produce a positive impact to societal and environmental challenges. The second meaning is understood “as ethical principles”, and there have been several efforts in the last years to define sets of principles to inspire the design and assessment of AI-based systems. However, there is an emerging challenge to move from principled AI to concrete approaches to put them into practice and make them relevant. The final strand in this field, and the main focus of our work, is “AI for social good as policies”, which set up priorities and action plans for the development and adoption of AI in the public interest. Hence, this paper focuses on how national strategies commit to the human-centric approach put forward by the European Commission (EC) through the European Guidelines for Trustworthy AI (2).

Our work presents a qualitative analysis of 15 European national strategies mapping investment plans and suggesting their relation to the social good. To perform the analysis we previously conducted a study on the European policy documents on AI from 2018 to 2020, identifying a set of macro-areas that helped us contextualise our analysis:

  • Beneficial innovation to improve public services and tackle social problems.
  • Education and life-long learning to prepare the society for an AI future.
  • Governance mechanisms to steer AI towards a beneficial use aligned with human rights and the rule of law through the elaboration and adoption of an ethical and legal framework.
  • Cooperation and dialogue among stakeholders to exchange best practices or create alliances and research networks.
  • Pan-European data and technological infrastructure including the creation of trusted data spaces, testing facilities and sandboxes, among others.

The policy directions outlined above aim to achieve the goals set out in the European AI strategy (3) and try to contribute to sustainable innovation. In addition, each policy area suggests measures that can foster AI for social good and contribute to build a roadmap for our qualitative analysis of the investment plans stated in National AI strategies.

Results suggest that European national strategies incorporate money allocations in the sphere of AI for social good in certain areas such as education, where we have identified a cluster of measures aimed at preparing the society to the transformation brought about by AI in the labour market. However, there is still a broader variety of underestimated actions in the rest of areas that can boost the European commitment to sustainable and responsible AI innovation (e.g., creating a multidisciplinary approach in STEM curricula or defining concrete actions to enable the dialogue among stakeholders). A general observation regards the gap between the language used by states and private organisations in these kinds of documents, that put responsible AI on top of their agendas, and the actions described, which are still not clearly formulated.  It is essential to move from the “ethics narrative” and support real actions to achieve AI for Social Good and to contribute to building a culture of trustworthiness of AI. In this sense, efforts should be put in place to achieve societal and environmental challenges aligned with the UN’s Sustainable Development Goals, such as climate change, health or migration. Hence, it is essential to follow-up the progress of resource and money allocation  plans defined in strategy plans and ethical guidelines and to observe the engagement of all stakeholders in this process, in particular governments and policy-makers. Further details on the qualitative analysis methods and the obtained results can be found in (1).

*Blog Post written by Atia Cortés, Recognised Researcher at Barcelona Supercomputing Center (BSC) and former co-director of AI4EU Observatory on Society and AI.


(1) Foffano, F., Scantamburlo, T. & Cortés, A. Investing in AI for social good: an analysis of European national strategies. AI & Soc (2022).

(2) High-Level Expert Group on Artificial Intelligence. Ethics Guidelines for Trustworthy AI (2018).


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