1. The document discusses European leadership in human-centered and trustworthy artificial intelligence, focusing on the AI4Media project. 2. AI4Media involves 30 partners across universities, research centers, and industry working on applications of AI for the media industry and society, including detecting deepfakes and manipulated media. 3. The summary emphasizes the need to balance fundamental and applied AI research, ensure open data and industry datasets, and focus on issues like bias, discrimination, and transparency to develop society-centered AI and maintain European leadership.

1. 1
European Leadership in Human-
Centred Trustworthy AI
Yiannis Kompatsiaris, CERTH - ITI
12th European Innovation Summit, December 11th, 2020

2. AI4Media: Artificial Intelligence for the
Society and the Media Industry
Delivering the next generation
of core AI advances to serve
the key sector of Media 2

3. 30 partners:
universities
research
centers
industry

4. 4
Media
• Information and communication production and delivery
• News and journalism
• Social Media
• Entertainment, film production
• Arts and creativity
Society and Democracy
• Economic value
• Societal values and opinions towards a democratic society
• If things go wrong, polarization and crises (e.g. fake news,
deepfakes)
Media, Society and Democracy

5. Manipulation and synthetic content
detection
5
DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection
• Easy way to identify
manipulated media
without any expertise
• Mitigate the spread of
disinformation and fake
news, prevent frauds
• Future challenges:
• sophisticated online bots
+ synthetic content
• from fake news to fake
humans

6. 6
• Continue supporting R&D
• Great progress in AI but we are not there yet
• Cannot be leaders if we follow advances happening
elsewhere
• Balance between fundamental aspects and
problem/application-driven specific/targeted research
• Balance between small-scale and large-scale efforts
(e.g. lighthouse vs collaborative projects)
• ΑΙ and data
• Openness and availability
• Industry-relevant effective datasets
• Transforming data assets (e.g. media archives) to
useful datasets
• Ensure quality and fairness
Leadership in AI

7. 7
• Mainstream Education About AI
• For European Business - and for the Public
• Enhance AI uptake and AI effectiveness/acceptance
• Society-centred AI: challenges of AI at the group
level
• Mitigate biases and beyond, detect faster
discrimination and fundamental rights issues
• AI in creating new forms of inequality: uneven
distribution of AI systems, know how, impact on certain
groups, “'leave no one behind’.
• Tech and human aspects integration, how AI is used
and consumed by their intended (and unintended)
users. Transparency: people have the right to know
what’s going on behind the scenes.
Leadership in AI

8. 8
International AI Doctoral Academy (IAIDA)
• a dense programme of internships, secondments and
collaborative PhD programmes
• establish links that will extend even beyond media, to
all aspects of European AI research
• build long-term links between academia and industry
Cascade Funding Programme
• focus on SMEs (media sector, creative industries)
• speed up the uptake of cutting edge R&D
(experimentation)
• quick transfer to the market (new business models and
deployment)
• access to talent from IAIDA
Education and tech transfer in AI4Media