The scale and intimacy of sensitive data gathered about us, combined with powerful algorithms, allows to study human lives and societal patterns in ways previously unimaginable. Tech platforms and digital services use this data to shape our choices, relationships, and interactions. The potential for tangible harms, from privacy violations to algorithmic discrimination, is immense. Independent researchers and journalists are not equipped with the tools to monitor these harms in opaque and complex digital infrastructures.

How to ensure researchers have secure, privacy-preserving, and equitable access to “research-grade” data to best study algorithms? How can they measure the real-world impact of algorithms when direct access is denied or limited?

How can we make sure AI models are developed in ways that protect people’s privacy, ensure fairness, and prevent unintended harm, especially when sharing AI models or the information they produce? How can we build public interest technology that truly benefits everyone, and give people and community groups a stronger voice in creating a fairer future?

We advance human-centred computing research to study the impact of data and algorithms on society. Our research guides the development of algorithms and infrastructures that are sustainable, safe, and serve the public interest, helping to ensure that the power of digital technologies is accountable to everyone. Our research is built on three core areas.

• Improving researcher data access with privacy-enhancing technologies.Facilitating data access while protecting sensitive data is a significant challenge for public interest research. Some privacy-enhancing techniques—such as injecting noise into data or creating ‘synthetic’ datasets—can fundamentally distort data in unknown and potentially harmful ways. For example, rare diseases may be suppressed in synthetic data, or vulnerable communities may be further marginalised.
• Investigating algorithms in online platforms.Automated algorithms set prices for consumers in online markets, match humans in dating apps, and recommend posts on social media feeds. Many of these algorithms are often opaque, not just to the public but to researchers and regulators as well.
• Evaluating interactions between humans and machines.To understand how technology impacts society, we must look beyond the algorithms themselves and consider how humans interact with them.