Projects
AI Equality by Design, Deliberation and Oversight
This project seeks to develop the theoretical foundations of ‘equality-by-design, deliberation and oversight’ (EbD) approaches to AI governance, striving to embed that knowledge into AI-standards in Europe and beyond.
When properly understood and implemented, EbD approaches to AI design and implementation entail on-going, situated and contextual assessment of the discrimination risks of specific AI-enabled socio-technical systems at every stage in the development and deployment process, entail meaningful participatory consultation with affected stakeholders, real-world testing, meaningful and effective provider and deployer oversight, are mandated by law, and overseen by independent properly resourced and empowered regulatory authorities.
Deciding about, by, and together with algorithmic decision-making systems
According to Alan Turing, Artificial intelligence (“AI”) is “the science and engineering of making intelligent machines, especially intelligent computer programs.” The most advanced AI systems employ complex “machine learning” techniques which use algorithms to deduce decision rules from input data and store them in, e.g., decision trees or neutral networks (algorithmic decision making, or “ADM”). Over time, the AI tool improves itself by learning from its past decisions, correct or incorrect.
The overarching ambition of this project is to examine whether there are limitations to this kind of ADM, within the range of AI systems used today. ADM systems are becoming increasingly popular among cash-strapped criminal justice systems.
AI ‘assurance’ via standardisation and certification systems
Robust technical standards will not deliver safe and secure AI in Europe unless and until they are embedded within legitimate and effective governance architectures that provide meaningful human oversight, demonstrably in accordance with core European values: namely, respect for democracy, human rights (including the protection of safety and security) and the rule of law. While EU policy-makers have produced several legal oversight regimes, including the GDPR, the EU Medical Device Regulation, and the proposed EU AI Act, whether the resulting governance architecture, and mechanisms through which compliance with these goals, will be achieved and assured remains unclear, untested and unknown.
The New Public Analytics: Investigating Digital Transformation in Government
The technology control dilemma: Can we satisfactorily regulate emerging technologies or will they control us?
The turn to data-driven approaches within public administration to inform (and even to automate) public sector decision-making can be understood as an emerging movement that I call ‘New Public Analytics’ (‘NPA’). Central to NPA is the use of data analytics a form of computational analysis with theoretical foundations in data science and statistics, involving the application of software algorithms (including but not limited to machine learning algorithms) to large data sets in order to identify patterns and correlations in the data capable of generating ‘actionable’ insight.
Digital Experimentation: Testing live facial recognition systems ‘in the wild’
Public sector organisations everywhere are embracing data-driven tools and systems inspired by their promised benefits, despite a dearth of evidence of social and economic benefits. As AI Watch reported in 2020, ‘most digital transformations in the public sector seem to be guided by hopes and dreams, rather than confirmed by empirical evidence.’
Blockchain for Healthcare
Blockchain technologies have the potential to radically reshape many industries, including healthcare. These technologies create a distributed database across a network of computers, using cryptographic methods to verify the consistency of digital records and transactions. This could enable secure, tamper-proof, transparent and trustworthy management of health-related data. But some doubt whether blockchain can deliver on this and others fear that it will deliver too much, providing efficiency and security without sufficient sensitivity.