Forging Successful AI Applications for European Economy and Society: FORSEE

Informazioni relative al progetto

FORSEE

ID dell’accordo di sovvenzione: 101177579

DOI

10.3030/101177579

Data della firma CE 1 Ottobre 2024

Data di avvio 1 Febbraio 2025

Data di completamento 31 Gennaio 2028

Finanziato da

• Culture, creativity and inclusive society

Costo totale

€ 3 544 868,75

Contributo UE

€ 3 544 868,75

Coordinato da

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Ireland

Periodic Reporting for period 1 - FORSEE (Forging Successful AI Applications for European Economy and Society: FORSEE)

Periodo di rendicontazione: 2025-02-01 al 2026-02-28

Sintesi del contesto e degli obiettivi generali del progetto

Redefining the Concept of AI Success
While AI capabilities are advancing rapidly, we still lack a clear understanding of what defines successful AI for society. We remain unsure about the conditions for its successful deployment. AI promises economic growth, medical breakthroughs, and improved lives. Yet success remains defined in technological and economic terms—measured by accuracy, efficiency, and growth. This narrow view ignores the social contexts in which AI is embedded, which can reflect and reinforce both inequalities and aspirations.

Towards a Holistic Approach to AI Success
The FORSEE project broadens the definition of AI “success,” moving beyond technical performance and economic return. We emphasise societal impact, sustainability, and stakeholder involvement. Through collaboration with institutions, CSOs, and the public, FORSEE explores how success is understood, where practice clashes with EU priorities, and how AI affects society and the economy. This supports policymakers and stakeholders in navigating future risks and opportunities. We begin with institutional perspectives across professional bodies, EU and global institutions, while also engaging SMEs, CSOs, and public debate. These projects will deliver reports on success criteria and their alignment with EU values.

The Multifaceted Impact of AI
Gender is a critical lens in understanding AI success, intersecting with wider social dynamics. FORSEE engages CSOs to identify gendered vulnerabilities and SMEs to explore inclusion in both design and outcomes. We also assess AI’s impacts on labour and sustainability. Using stakeholder dialogue, we examine worker perspectives, hidden costs of adoption, and local infrastructure impacts, including supply chains viewed through sustainability and digital sovereignty.

Mapping AI Success to Inform Policy Design
By spotlighting successful AI examples, FORSEE raises expectations and promotes systems that deliver broad social value. Our findings guide policymakers and scholars with practical, values-driven tools. These help SMEs align their work with EU priorities. Analysing decisions behind success shows how trade-offs like sustainability versus efficiency can be managed. FORSEE argues that human-centred, sustainable AI is Europe’s strategic edge. Beyond reports, we are building tools to help stakeholders advance this broader vision, keeping AI value-aligned and technically robust.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

Mapping Institutional Understandings of AI Success
This research strand investigates how supranational bodies, technical organisations, academic institutions, and professional associations define AI success. These actors shape formal criteria through standards, guidelines, and ethical frameworks that influence how AI is developed, deployed, and evaluated.

Understanding Success from a Lifeworld Perspective
This component explores how SMEs define and experience success in AI. By analysing their expectations and concerns, the research connects social positions with specific visions of AI, offering grounded insights into how SMEs conceptualise the development and deployment of AI systems alongside the specific opportunities and challenges that arise from the EU regulatory environment.

Identifying AI Tensions, Controversies, and Failures
This area focuses on public controversies and societal tensions surrounding AI. It examines how AI is framed in news media and in social media platforms, allowing for an understanding of controversies in the public debate around emerging technologies. Litigation case studies are also examined to uncover legal and ethical concerns. Scenario-building exercises help anticipate current and future challenges.

Investigating AI’s Societal and Economic Impacts
This strand evaluates AI’s impact on the economy and society, focusing both on issues of productivity and competitiveness, while also engaging with AI’s influence on climate change and sustainable development. This is grounded research that includes workers’ perspectives on how AI is transforming contemporary workplaces. Furthermore, it also engages with the often mystified impact of AI –and the supply chains that underpin its development– on the environment.

Aligning AI with EU Values and Priorities
This area assesses how the perspectives across different stakeholders and the specific applications identified, align with EU priorities — digital sovereignty, sustainability, rights, and human-friendly design. It identifies alignment and gaps , and future potential, using policy analysis and compliance assessment to support informed action.

Enhancing Governance and Regulatory Capacity
Building on prior findings, this final strand identifies regulatory gaps and areas of controversy. It develops a taxonomy of risks and challenges, proposes a risk register, and outlines governance structures to support independent oversight and participatory policymaking for AI.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

1. Understanding and Communicating AI Success and Its Limits
FORSEE highlights AI applications with strong social and economic outcomes while identifying their limits. It links stakeholder definitions of success, from institutions, SMEs, and public discourse, to EU values. These insights help assess AI’s impacts on productivity, sustainability, and digital sovereignty. Findings feed into an evaluative framework scoring applications across key dimensions. This tool, with supporting reports and datasets, helps SMEs and policymakers identify strengths and address gaps. By sharing results through its network, FORSEE raises awareness of what value-aligned AI looks like and how limitations can be addressed.

2. Applying AI Ethics Principles in Practice
Building on successful deployments, FORSEE examines how principles for trustworthy AI, lawfulness, ethics, and robustness, are applied in practice. It evaluates legal compliance, contrasts stakeholder views with EU ethical guidelines, and analyses technical robustness and environmental impacts. These findings form a measurable framework translating ethics principles into concrete benchmarks. This supports SMEs, policymakers, and the public in evaluating AI applications and turning high-level values into actionable development tools.

3. Anticipating and Managing Future AI Risks
FORSEE creates tools to identify and manage future AI risks and opportunities. It maps blind spots, categorises risk types, and builds a flexible risk register. Process-tracing of successful cases reveals key decisions and structures.
Resources such as the risk catalogue and tracing reports will guide future AI development, helping SMEs and regulators anticipate challenges and adapt governance strategies.

4. Informing European AI Policy with Evidence and Values
FORSEE offers policy recommendations to help Europe address AI risks and support value-aligned innovation. Its taxonomy of risks and governance gaps informs proposals to strengthen oversight. Partnering with the Digital SME Alliance, FORSEE connects findings to the tech startup ecosystem and promotes distributed governance by involving CSOs, trade unions, and gender-vulnerable groups. These structures complement the AI Act with flexible, participatory oversight mechanisms.