Research

I research data, AI, policy and society at the Ada Lovelace Institute.

My current focus areas are:

Methods, policy and capacity building for auditing/inspecting algorithmic systems
Algorithmic impact assessments and approaches to increase consideration and mitigation of risks in software development and data science
Transparency and accountability for of AI in the public sector

Beyond my main research, I'm also interested in the power dynamics of data infrastructure, the environmental impact of AI and existential risk.

I've previously worked on research into policymaking for future generations and unconscious bias, particularly in recruitment and online platforms.

Recent publications

Algorithmic impact assessment: a case study in healthcare, 2022, Ada Lovelace Institute
Technical methods for regulatory inspection of algorithmic systems, 2021, Ada Lovelace Institute
Algorithmic accountability for the public sector: Learning from the first wave of policy implementation, 2021, Ada Lovelace Institute, AI Now and Open Government Partnership
Inspecting algorithms in social media platforms, 2021, Ada Lovelace Institute and Reset
Examining the black box: tools for assessing algorithmic systems, 2020, Ada Lovelace Institute
Beyond face value: public attitudes to facial recognition technology, 2019, Ada Lovelace Institute

Press, media, blogs

Why Ofcom needs clear powers to audit Big Tech's algorithms - written for The New Statesman
The U.K.'s new AI transparency standard is a step closer to accountable AI - written for VentureBeat
Getting under the hood of Big Tech - on auditing in the EU Digital Services Act with Alex Circuimaru for the Ada Lovelace Institute blog
Algorithms in social media platforms: realistic routes to regulatory inspection - on the Ada Lovelace Institute blog
Understanding the impact of algorithms - co-authored with DataKind UK CEO Giselle Cory for Charity Digital News
Facial recognition: defining terms to clarify challenges - on the Ada Lovelace Institute blog