AI & Biases: the Road to Algorithmic Fairness

Programme Description

With the growing adoption of artificial intelligence (AI) in various areas of our personal and social lives, it has become increasingly important to understand the implications of biases in algorithms, and how they can impact the fairness and accuracy of the decisions made by AI systems. This three-day training will provide the necessary knowledge and skills to understand the impacts of biases in algorithms and how to implement AI systems in a fair and inclusive manner. The training will focus on the potential amplification of biases in contexts mediated by technology such as policymaking, decision-making, and the workplace.

The course is designed around lectures, case studies, and hands-on exercises to illustrate the technical details and applications of bias mitigation in AI. Participants will have the opportunity to apply these techniques to real-world scenarios and discuss potential solutions with their peers.

The first part of the training (day one) will set the scene and provide an introductory overview of the European perspective on the impacts of AI in social systems. Participants will learn the basic foundations of AI, identify existing and potential biases in their use, and delve into the risks of implementing biased algorithms.

The second part (days two and three) is more specific and practice-oriented for particular contexts (public sector/industry/civil society). During these two days, participants will explore different mitigation strategies for preserving fairness and diversity in increasingly technology-mediated environments, exchange experiences, and jointly chart the way towards a fairer and more inclusive AI.

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Learning methods

• Interactive sessions and group discussions with the instructors;
• Case studies based on actual examples of biased algorithms and their impact;
• Role-playing exercises to help participants understand the perspectives of different stakeholders and how they might be affected by biased algorithms;
• Peer-to-peer learning and project work. Individual or group projects to work on, where participants will apply the concepts learned during the seminar to real-world problems.

Learning outcomes

By the end of this programme, the participants will be able to:

• Understand the basics of AI, including how algorithms work, the types of biases that can exist in AI systems, and their implications in various contexts;
• Develop, explain, and communicate strategies and tools for promoting algorithmic fairness;
• Implement the knowledge and skills to identify and mitigate biases in their own organisations;
• Identify best practices for implementing AI systems in a fair and inclusive manner, and develop strategies to preserve fairness and diversity in increasingly technology-mediated environments.

Information for applicants

• The programme is fully funded by the Chair in Artificial Intelligence and Democracy (AI&DEM).
• The lunches and coffee breaks during the programme will be provided by the EUI. The fee does not cover travel and accommodation. Participants are responsible for organising their own travel and accommodation.
• We encourage early registration as places are limited and given on a rolling basis. Applicants will be informed about the final outcome of the selection by the end of July.
• The training course will take place in person on 16, 17, and 18 October 2023. Selected participants will be expected to be present on the EUI campus in Florence, Italy, on the days of the training.
• The programme comprises approximately 22 hours of in-session training not including lunches or coffee breaks.
• Participants will be enrolled in the EUI’s Virtual Learning Environment (Brightspace) in order to access the materials of the course.
• Accepted participants that successfully complete the training course will receive a Certificate of Attendance from the EUI School of Transnational Governance.
  
  

Who should attend

• Professionals from the public, private, and third sectors who are interested in developing an in-depth understanding of the main challenges posed by AI;
• Professionals from the public, private, and third sectors who are beginning to implement algorithmic systems in their work contexts or are already working with them;
• Public managers responsible for the development of regulatory proposals in local, national or regional administrations;
• Evaluators of existing laws and regulations, in government or private.