The Impact of Human-AI Interaction on Discrimination

This large-scale study assesses the impact of human oversight on countering discrimination in AI-aided decision-making for sensitive tasks. We use a mixed research method approach, in a sequential explanatory design whereby a quantitative experiment with HR and banking professionals in Italy and Germany (N=1411) is followed by qualitative analyses through interviews and workshops with volunteer participants in the experiment, fair AI experts and policymakers. We find that human overseers are equally likely to follow advice from a generic AI that is discriminatory as from an AI that is programmed to be fair. Human oversight does not prevent discrimination when the generic AI is used. Choice when a fair AI is used are less gender biased but are still affected by participants' biases. Interviews with participants show they prioritize their company's interests over fairness and highlights the need for guidance on overriding AI recommendations. Fair AI experts emphasize the need for a comprehensive systemic approach when designing oversight systems.JRC.S.1 - EU Policy Lab: Foresight, Design & Behavioural Insight

The potential of generative AI for the public sector: current use, key questions and policy considerations

The advent of generative AI presentes unprecedents opportunities and challenges within the public sector, calling for a detailed examination of its influence to harness its capabilities while safeguarding fundamental European values. This policy brief aims to examine the current usage, possible benefits, challenges and future prospects for the use of generative AI in the public sector. It analyses the phenomenon from three perspective. At individual level, our analysis of the current landscape reveals that 30% of public managers are using online generative AI technologies, with anticipation of increased adoption, as evidenced by an additional 44% planning to integrate these tools in the near future. At organisational level, public administrations are actively exploring the creation of in-house generative AI applications, with approximately 60 use cases currently identified across Europe. Moreover, still at organisationa level, some public administrations are developing guideline sto suppoort civil servants in using generative AI. Finally, at national level, there is a burgeoning effort to craft necessary policy frameworks and regulatory mechanisms to guide the ethical and effective use of generative AI. Some member states are also considering the development of national generative AI models to better support official national lan-guages, particularly those less represented. Despite these advancements, the discourse surrounding generative AI in the public sector is punctuated by numerous unresolved questions, particularly regarding long-term implications, governance, and the balance between innovation and privacy. As the landscape continuously evolves, an urgent need for continuous evaluation and policy adaptation emerges. Addressing these open inquiries will be critical in ensuring that the integration of generative AI into public services not only boosts efficiency and effectiveness but also adheres to the high standards of ethics and transparency expected within European public institutions.JRC.T.1 - Digital Econom

Shaping the Next Generation of Virtual Worlds

Next generation virtual worlds present a strong, multifaceted potential that also need to be analysed in light of the challenges they may pose along societal, technological, and economic and policy dimensions. To dive deeper into the EU's strategic approach to immersive technologies, the Joint Research Center organised the ‘Shaping the Next Generation Virtual Worlds – Science for Policy (online) event’, gathering experts and policymakers to foster collaboration and knowledge exchange to navigate the socio-economic and technological landscapes of virtual worlds. Key discussions addressed the role of research in policy, the socio-economic implications of virtual worlds, and the EU's actions to support new business models and applications in virtual environments.JRC.T.1 - Digital Econom

Scoping Review Protocol: Virtual Worlds and Mental Health

This document contains the protocol for a scoping review on the impact of virtual worlds on users' mental health. The protocol outlines the motivation for the review, its objectives and scope, the research questions addressed, and the method used. It also includes the data extraction form employed.JRC.S.4 - Scientific Development Programme

AI Watch: Artificial Intelligence Standardisation Landscape Update

The European Commission presented in April 2021 the AI Act, its proposed legislative framework for Artificial Intelligence, which sets the necessary regulatory conditions for the adoption of trustworthy AI practices in the European Union. Once the final legal text comes into force, standards will play a fundamental role in supporting providers of concerned AI systems, bringing the necessary level of technical detail into the essential requirements prescribed in the legal text. Indeed, harmonised standards provide operators with presumption of conformity with legal requirements. AI has been an active area of work by many standards development organizations in recent years. In this report, we analyse a set of specifications produced by the IEEE Standards Association covering aspects of trustworthy AI. Several of the documents analysed have been found to provide highly relevant technical content from the point of view of the AI Act. Furthermore, some of them cover important standardization gaps identified in previous analyses. This work is intended to provide independent input to European and international standardisers currently planning AI standardisation activities in support of the regulatory needs. This report identifies concrete elements in IEEE standards and certification criteria that could fulfil standardisation needs emerging from the European AI Regulation proposal, and provides recommendations for their potential adoption and development in this direction.JRC.T.1 - Digital Econom

AI Watch: Revisiting Technology Readiness Levels for relevant Artificial Intelligence technologies

Artificial intelligence (AI) offers the potential to transform our lives in radical ways. However, we lack the tools to determine which achievements will be attained in the near future. Also, we usually underestimate which various technologies in AI are capable of today. This report constitutes the second edition of a study proposing an example-based methodology to categorise and assess several AI technologies, by mapping them onto Technology Readiness Levels (TRL) (e.g., maturity and availability levels). We first interpret the nine TRLs in the context of AI and identify different categories in AI to which they can be assigned. We then introduce new bidimensional plots, called readiness-vs-generality charts, where we see that higher TRLs are achievable for low-generality technologies focusing on narrow or specific abilities, while high TRLs are still out of reach for more general capabilities. In an incremental way, this edition builds on the first report on the topic by updating the assessment of the original set of AI technologies and complementing it with an analysis of new AI technologies. We include numerous examples of AI technologies in a variety of fields and show their readiness-vs-generality charts, serving as a base for a broader discussion of AI technologies. Finally, we use the dynamics of several AI technologies at different generality levels and moments of time to forecast some short-term and mid-term trends for AI.JRC.B.6 - Digital Econom

Data quality requirements for inclusive, non-biased and trustworthy AI

A decade of rapid development of artificial intelligence (AI) resulted in the release of a large diversity of practical applications across sectors. Data play a fundamental role for AI systems, which can be seen as adaptive data processing algorithms that adjust outputs to input training data. This fundamental role of data is reflected in the EU policy agenda where for example guidance on handling the data is specified in the AI Act. A Putting Science Into Standards workshop on data quality requirements for inclusive, nonbiased, and trustworthy artificial intelligence took place on 8 and 9 June 2022, with more than 178 participants from 36 countries gathering for the first time European standardisation experts, legislators, scientists, and societal stakeholders to map pre-normative research and standardisation needs. We highlighted those during the creation and documentation of datasets all along to data quality requirements, bias examination and mitigation during the employment of the AI system. We identified steps to start the process of drafting new standards and recognised that inclusiveness and full representation of all relevant stakeholders, including industry, SMEs representatives, civil society, and academia is crucial. Building a stronger engagement of experts in AI standardisation is essential to contribute to the development of standards that are needed not only to support the market deployment of AI systems in accordance with the AI act but also to support this growing field of research.JRC.A.5 - Scientific Developmen

Artificial Intelligence for the Public Sector

The Public Sector plays different roles with regard to AI. First, it acts as regulator, establishing the legal framework for the use of AI within society. Second, governments play also the role of accelerator, providing funding and support for the uptake of AI. Third, public sector organisations develop and use Artificial Intelligence. To explore these roles, with particular emphasis on the latter, the Joint Research Centre (JRC) and the Directorate-General for Informatics (DIGIT) of the European Commission jointly organised a webinar series and a “science for policy” conference in 2022. This report includes the conclusions of each one of the webinars, together with the material and main findings of the closing event. It reveals recent challenges, opportunities, and policy perspectives of the use of AI in the public sector, and distils a set of short takeaway messages. In a nutshell these finding are (i) AI in the public sector implies multi-stakeholders; (ii) experiment first, scale-up later; (iii) trustworthiness is a must; (iv) there is a need for upskilling public sector to be ready for the AI revolution; and (v) adapt procurement for digital and AI innovation. The report concludes that the AI promise is high for the society and in particular for the Public Sector, but the risks are not to be minimized. Europe has the ambition to succeed as whole in the digital transition powered by data and by AI-based applications, and wants to do it the European way, by putting citizens in the centre of this transformation.JRC.T.1 - Digital Econom

Next Generation Virtual Worlds: Societal, Technological, Economic and Policy Challenges for the EU

This report provides an overview of the opportunities that next generation virtual worlds may bring in different sectors such as education, manufacturing, health, and public services among others. This potential will need to be harnessed in light of the challenges the EU may need to address along societal, technological, and economic and policy dimensions. We apply a multidisciplinary and multisectoral perspective to our analysis, covering technical, social, industrial, political and economic facets. The report also offers a first techno-economic analysis of the digital ecosystem identifying current key players in different subdomains related to virtual worlds.JRC.T.1 - Digital Econom

Decoding Depression: Exploring the Environome Across Life Course

Depression is a central marker in mental health issues due to its widespread prevalence, significant disability burden, and extensive social and economic impacts. The COVID-19 pandemic, ongoing conflicts, natural disasters, and the climate crisis have exacerbated mental health challenges across populations, necessitating robust and adaptive policy responses, particularly affecting youth and individuals with pre-existing conditions linked to e.g., genetic, biological, medical, psychological, social and environmental factors. These global events highlight the need for comprehensive mental health strategies that can withstand and mitigate such polycrises. The European Commission has recognised this urgency through its political guidelines for 2024-2029, with a renewed commitment to mental health as a key component of its preventive health strategies and social policies. It issued a Comprehensive Approach on Mental Healthe on June 7th, 2023, to address the urgent need for action on mental health and depression. In line with President Ursula von der Leyen's strategic priorities, the Commission's approach integrates mental health into broader socio-economic initiatives, including anti-poverty, social rights, affordable housing, and health plans aimed at fostering resilience and inclusivity. This report draws on scientific knowledge and insights from transdisciplinary healthcare professionals alongside lived experience experts, gathered during the scientific workshop “Crowdsourcing Knowledge on Depression Mechanisms: From Risk Factors to Treatment” held at the European Commission’s Joint Research Centre in April 2023, and further refined in a co-editing workshop in June 2024, “Decoding Depression: A Life Course Exploration of Vulnerabilities through Transdisciplinary Inquiry”. It emphasises the complex, environome-driven nature of depression, where personal, social, natural, and built environments converge to shape mental health outcomes. Central to our approach is embracing the advancements from various disciplines, including life sciences, environmental studies, education, and technological innovation. The report champions a One Health Governance and transdisciplinary collaboration to address the multifaceted challenges of depression, integrating insights from a broad spectrum of scientific and societal perspectives. It identifies seven key areas essential to tackling depression: healthcare and social inclusion, education, arts with an emphasis on cultural sensitivity and equity, technology and digital tools, labor market and economics, humanitarian considerations alongside local and global welfare, urban planning and environmental health. These categories, underpinned by the Commission's framework, are integral to formulating comprehensive policies that apply the multifaceted evidence-based scientific nature of depression. An evolving Interactive Depression Dashboard (InDepDash) has been created as a dynamic, centralised information hub, offering a comprehensive navigation and synthesis of the extensive and evolving scientific literature on depression. It supports the strategic vision of the European Commission by providing an evidence-based digital platform for policy-makers, helping to guide decision-making processes and fostering a culture of Open Science. We focus on identifying essential policy interventions that span prevention, the spectrum of supportive resources —both conventional and alternative— and recovery processes.JRC.F.7 - Digital Healt