People Powered Algorithms for Desirable Social Outcomes

Algorithms increasingly govern interactions between state and citizen and as the 'digital by default' model of government-citizen interaction spreads this will increase. This increase, combined with the value of data science and how AI and machine learning is embraced as a way to achieve efficiency and carry out public policy we need to consider how algorithms mediate real-world relationships between the state and individuals.

Without confidence in the legitimacy and credibility of the algorithms the trust between government and citizens will dramatically degrade. Our research will therefore focus on algorithmic interactions between the citizen and the state and examine how we form productive and trusted relationships between those designing, deploying and using the algorithmic interactions and the communities affected by the decisions.

We will examine three key public policy areas where algorithmic decision-making is used for aspects of policy deployment: refugee resettlement, welfare and healthcare provision. These three areas have been selected as they are at the forefront of services that developed as part of digital by default, where issues of cost are addressed, in part, by algorithmic decision making to evaluate legitimate service access and use. Additionally, these are areas of significant public spending where the intended users of these services are more likely feel excluded and disenfranchised from mainstream society. Our research will examine how the re-designing of the system interactions and the communication of the political and economic logic will enhance the security and well-being of individuals, protects the security of the state and increases the confidence in digital service design.

Our proposed research will synthesise the outputs of market design research with information security research and, by visualising and abstracting the outputs, facilitate new dialogues across a range of stakeholders from individuals through to policy makers. The resulting dialogues will:
1. Promote discussions within communities about fairness and legitimacy in data-driven decision making;
2. Facilitate inter-community conversations between system designers, policy makers and communities that discuss the impact of informal information flows and the conceptual models on which systems are built;
3. Diversify the security dialogue so that a more nuanced discussion can be had about the connection between personal security, state security and technical security.
4. Allow us to engage with market design researchers to explore how an understanding of informal information flows might impact on their research.

We will drive impact in four beneficiary groups: User communities; Government Policy makers; Data scientists, system designers and security architects and finally academia.

User communities: This societal impact will ensure that our research not only involves the user communities but also genuinely supports the increased well being of these communities. This will be achieved through the improved social outcomes from better algorithmic policy making and through the increased agency and awareness from discussing these important topics. We will work across a range of policy domains to reach particular communities. For example our work with algorithmically implemented refugee policy will reach Refugees, Hosting communities, Communities in zones of first asylum and Communities in zones of transit. While in the UK our research in healthcare and welfare will consider a number of community groups and local government in Sunderland (see letter of support), communities with which members of the team have already engaged.

Government policy makers: It is intended that this work will assist in supporting and developing algorithm design at a national level as well as a local government level. Note that all members of the team have been active in supporting policy development at government (see also letter of support from GCHQ). In the specific policy domains our research will benefit multiples stakeholders. In the domain of refugee policy the following government beneficiaries will be reached: State ministries (e.g. UKHO, German BAMF, etc) Intergovernmental agencies involved in coordinating resettlement (e.g. EASO, IOM, UNHCR resettlement office), Local government involved in meeting resettlement needs (councils, municipalities, quangos such as JOMAST), Humanitarian workers and CSOs and Migration management ministries and border. In the domain of welfare policy, the following government beneficiaries will be reached: Department of Work and Pensions both centrally and regionally.

Data scientists, systems designers and security architects: There is a significant increase in the use of data-led decision-making both in government and industry. Driving awareness and of the issues raised in this research in these practitioners through their education and skills pipeline will ensure that our research will have a long-lasting impact on their professional practice, not only in their current posts but also their future influence.

Academia:Our inter-university consortium will support the training of highly skilled researchers and facilitate the generation and transfer of new methods of research synthesis. This will be supplemented by a network of visiting academics from fields including Political Science, Economics, Computer Science and Cyber-Psychology - this will result in an energetic and vibrant community. Further engagement with projects such as DAPM, UnBias and Ox-Chain in addition to the Orbit and TIPS1 funded projects will ensure that the exciting research is disseminated widely amongst the UK and International communities.