Measuring and Mitigating Risks of AI-driven Information Targeting
This project aims to assess the risks of AI-driven information targeting on individuals, algorithms, and platforms, and propose protective measures through innovative measurement methodologies.
Projectdetails
Introduction
We are witnessing a massive shift in the way people consume information. In the past, people had an active role in selecting the news they read. More recently, the information started to appear on people's social media feeds as a byproduct of one's social relations.
Current Trends
At present, we see a new shift brought by the emergence of online advertising platforms where third parties can pay ad platforms to show specific information to particular groups of people through paid targeted ads. These targeting technologies are powered by AI-driven algorithms.
Risks of Information Targeting
Using these technologies to promote information, rather than promote products as they have been initially designed for, opens the way for self-interested groups to use users' personal data to manipulate them. European Institutions recognize the risks, and many fear a weaponization of the technology to engineer polarization or manipulate voters.
Project Goals
The goal of this project is to study the risks with AI-driven information targeting at three levels:
- Human-level: In which conditions targeted information can influence an individual's beliefs.
- Algorithmic-level: In which conditions AI-driven targeting algorithms can exploit people's vulnerabilities.
- Platform-level: Are targeting technologies leading to biases in the quality of information different groups of people receive and assimilate.
Then, we will use this understanding to propose protection mechanisms for platforms, regulators, and users.
Methodology
This proposal's key asset is the novel measurement methodology I propose that will allow for a rigorous and realistic evaluation of risks by enabling randomized controlled trials in social media. The measurement methodology builds on advances in multiple disciplines and takes advantage of our recent breakthrough in designing independent auditing systems for social media advertising.
Conclusion
Successful execution will provide a solid foundation for sustainable targeting technologies that ensure healthy information targeting.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.499.953 |
Totale projectbegroting | € 1.499.953 |
Tijdlijn
Startdatum | 1-10-2022 |
Einddatum | 30-9-2027 |
Subsidiejaar | 2022 |
Partners & Locaties
Projectpartners
- INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUEpenvoerder
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Land(en)
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Designing Social Media Recommendation Algorithms for Societal Good
The project aims to enhance social media algorithms by integrating civic discourse values to reduce risks to social cohesion while balancing freedom of expression through participatory design and risk assessment.
Social Media: Measuring Effects and Mitigating Downsides
This project aims to investigate the causal effects of social media on political engagement and mental health, while evaluating interventions to mitigate its negative impacts on users and society.
Human Ads: Towards Fair Advertising in Content Monetization on Social Media
HUMANads aims to establish a European legal framework for fair advertising by human ads on social media, addressing transparency issues in commercial and political communications through interdisciplinary research.
Enhancing Protections through the Collective Auditing of Algorithmic Personalization
The project aims to develop mathematical foundations for auditing algorithmic personalization systems while ensuring privacy, autonomy, and positive social impact.
VIrtual GuardIan AngeLs for the post-truth Information Age
The VIGILIA project aims to develop AI-driven tools to detect cognitive biases in information processing, mitigating the effects of misinformation and enhancing trust in society.
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