GOALS & IMPACT

At DIVERSIFAIR, we aim to tackle intersectional bias in Artificial Intelligence (AI) by addressing systemic discrimination. Our goal is to promote fairer, more inclusive AI systems that work equitably for everyone, particularly those from marginalised communities.

A young black man looks into the camera. He is wearing a dressing gown and has a towel around his neck. He applies a cotton pad to his face and wears a ring on his right hand. a list of words and numbers describe the man’s expression. Happiness 4.185, neutral 0.901, surprise 89.864, sadness 0.01, disgust 0.01, anger 5.021 and fear 0.01.

OUR APPROACH

DIVERSIFAIR focuses on two critical challenges in AI development:

Bridging the expertise gap: there is a shortage of professionals trained to recognise and mitigate discrimination in AI. We equip both technical and non-technical stakeholders with the necessary skills to tackle unfairness effectively.
Embedding an intersectional approach: traditional methods often address fairness and bias in AI from a single-axis perspective (e.g., gender or race alone). DIVERSIFAIR ensures AI systems account for multiple overlapping identities to prevent compounded discrimination.

WHAT WE DO

DEVELOPING KNOWLEDGE AND TOOLS

- Building a comprehensive knowledge base on intersectional fairness and bias in AI, combining academic research and practical insights.
- Developing educational AI tools and techniques to help integrate intersectional thinking throughout the AI lifecycle, including how to detect and mitigate bias.

RAISING AWARENESS

- Educating organisations and the public through workshops, training programmes, and outreach campaigns on AI fairness.

EMPOWERING KEY SECTORS

- Enhancing the AI literacy and overall digital skills of SMEs, educational institutions, and enforcement agencies through targeted training and advisory support.
- Promoting bias detection and prevention methods, particularly in hiring and recruitment.
- Fostering collaboration between public and private sectors to contribute to more EU-wide AI policy and governance.

KEY OUTCOMES

Educational kits

Already available

- Easy-to-understand resources explaining intersectional bias and fairness
- Designed for anyone— no technical background required
- Practical case studies showing real-world examples.

Explore the toolkits

Mapping of the AI regulation landscape

Already available

- Maps AI-related regulations across Europe and beyond.
- Helps users navigate AI fairness and compliance.
- Supports policymakers, students and researchers in studying how regulations address AI fairness, intersectionality or bias.

Explore the visualisation tool

Training for AI practitioners

Already available

- Three expert-led modules covering bias detection, inclusive AI design, and ethical AI practices.
- Hands-on tools to apply intersectional fairness principles in AI projects.
- Soft skills training to navigate AI ethics discussions.

Find out more

Actionable recommendations for the intersectional approach

ETA: 2025

- Guidelines for AI professionals to identify and address intersectional bias.
- Expert-driven insights to make AI development more inclusive.
- Practical strategies that can be implemented in real-world AI projects.

Stay updated!

Fair AI Scrum methodology

ETA: September 2025

- A step-by-step framework to integrate intersectional fairness into AI development.
- Practical tools to assess and mitigate intersectional bias at every stage.
- Designed for AI teams working on ethical, responsible AI.

Stay updated!

Typology of AI harms

ETA: November 2025

- Identifies different types of AI-related harm.
- Links AI fairness and bias to real-world consequences.
- Connects users to available redress mechanisms.

Stay updated!

DIVERSIFAIR is dedicated to promoting the fairer, more inclusive and accountable use of AI.

Want to get involved or learn more? Join us in shaping more responsible approaches to AI!

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This project has received funding from the European Education and Culture Executive Agency (EACEA) in the framework of Erasmus+, EU solidarity Corps A.2 – Skills and Innovation under grant agreement 101107969.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Culture Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.