Inclusive Research & Design

How can we build AI that works for everyone?

Work with communities

Create accessible technology

Empower marginalized stakeholders

Address social inequality

AI has the potential to both increase and reduce social inequality. To ensure AI generates more social good than harm, the people affected by this technology must be engaged in its development and deployment. Partnership on AI’s Inclusive Research and Design Program provides practical resources for how AI can be created with communities — not just for them.

These tools and recommendations are based on insights offered by AI’s wide range of stakeholders, including practitioners, business leaders, ethics researchers, users, and people who are affected by AI deployments. With this work, we also examine PAI’s own research practices to ensure all Programs consistently demonstrate equity and inclusivity.

Our Inclusive Research & Design Work

In 2022, PAI published “Making AI Inclusive,” a white paper identifying important challenges and opportunities for engaging people who are not on AI development teams. Providing four guiding principles and three recommendations for ethical engagement, this paper was derived from discussions with industry experts, a multidisciplinary review of existing research on stakeholder and public engagement, and more than 70 individual interviews with AI practitioners.

That same year, PAI published four recommendations for how organizations can make their AI teams more inclusive, attract and retain talent, and make good on their commitments to diversity. Drawn from in-depth interviews with minoritized AI workers and others, this guidance was designed to be ready for implementation and effective in practice.

To establish practical approaches for integrating stakeholder feedback into the AI development process, PAI has launched the Global Task Force for Inclusive AI. This initiative will drive partnerships between technology developer teams and community-based organizations as a way to identify and address algorithmic discrimination and other social harms that may result from the use of AI-enabled products, services, and systems.