Periodic Reporting for period 4 - DATAJUSTICE (Data Justice: Understanding datafication in relation to social justice)
Période du rapport: 2022-07-01 au 2023-12-31
The use of data and algorithmic processes for decision-making are a growing part of social life. Digitally monitoring, tracking, profiling as well as predicting human behaviour and social activities is at the core of the information order often described as surveillance capitalism. Increasingly, it also determines decisions that are central to our ability to participate in society, such as welfare, education, crime, work, and if we can cross borders. How can we grasp what is at stake in such developments?
Whilst much debate on this datafication of society has focused on the need for efficient and supposedly more objective responses to social problems on the one hand and a concern with individual privacy and the protection of personal data on the other, it is becoming increasingly clear that we need a broader framework for understanding these developments. This is one that can account for the disparities in how different people might be implicated and that recognises that the shift to a datafied society is not merely technical but has implications for social justice. Such a framework, referred to here as ‘data justice’, pays particular attention to the ways in which data processes are uneven, can and do discriminate, create new social stratifications of ‘have’ and ‘have nots’, and advance a particular politics based on a logic of prediction and preemption that caters to certain interests over others.
In this project, we have taken stock of these concerns, and drawn on a number of different case studies across contentious areas of governance and control, including work, law enforcement, and migration that look at the implementation of algorithmic processes in practice. In analysing these case studies, the project has explored how practices are changing with the implementation of data-driven systems and with what implications for the lives of different communities, the protection of social and economic rights, and the advancement of social justice. The overall objective has been to advance conceptual and empirical research on the relationship between social justice and datafication, with a view to enhance public understanding of data developments, broaden the debate on data collection, minimise data harms, and find ways to mobilise civil society around data justice.
Whilst much debate on this datafication of society has focused on the need for efficient and supposedly more objective responses to social problems on the one hand and a concern with individual privacy and the protection of personal data on the other, it is becoming increasingly clear that we need a broader framework for understanding these developments. This is one that can account for the disparities in how different people might be implicated and that recognises that the shift to a datafied society is not merely technical but has implications for social justice. Such a framework, referred to here as ‘data justice’, pays particular attention to the ways in which data processes are uneven, can and do discriminate, create new social stratifications of ‘have’ and ‘have nots’, and advance a particular politics based on a logic of prediction and preemption that caters to certain interests over others.
In this project, we have taken stock of these concerns, and drawn on a number of different case studies across contentious areas of governance and control, including work, law enforcement, and migration that look at the implementation of algorithmic processes in practice. In analysing these case studies, the project has explored how practices are changing with the implementation of data-driven systems and with what implications for the lives of different communities, the protection of social and economic rights, and the advancement of social justice. The overall objective has been to advance conceptual and empirical research on the relationship between social justice and datafication, with a view to enhance public understanding of data developments, broaden the debate on data collection, minimise data harms, and find ways to mobilise civil society around data justice.
Work performed includes:
- Extensive review of literature and public debate on the relationship between datafication and social justice
- Fieldwork on the role of data-extractive technologies in the asylum process in the UK and Greece and within the EU more widely, with a particular focus on fingerprinting and EURODAC and everyday technologies such as mobile phones and cash cards.
- Fieldwork on the implementation of data-driven systems in policing in the Netherlands, Belgium and the UK, with a particular focus on risk assessment tools and recognition technologies, including speaker identification systems.
- Fieldwork on the development and uses of data-driven systems in the workplace in Greece, the Netherlands and the UK, with a particular focus on automated hiring systems and algorithmic management in call centres and postal work.
- Technical analysis of key data systems used in migration, law enforcement and work.
- Policy analysis and fieldwork on the policy process, looking at how social rights feature in EU's digital policies.
Results have shown a growing trend in relying on data collection for decision-making and organisational processes across the areas of migration, law enforcement and work. Importantly, this trend derives from a number of contextual factors that emphasises the situated nature of data-driven systems within different institutions and that also highlights the negotiations and tensions that surround the implementation of new technologies. In most of our case studies, data collection and use is closely linked to institutional and historical contexts, policy agendas and different economic interests. In the systems we analysed, there are significant contentious assumptions about not just the nature of data and the relationship between people and data, but a clear politics present concerning wider questions of governance and control that are significant for social justice.
Moreover, the project found that the widespread use of data-driven systems is often experienced as particularly harmful amongst marginalised and disadvantaged groups. However, often experiences of injustice are bound up with wider social contexts that shape not only the uses of data but how they may be negotiated or resisted. At the same time, in discussions about social justice relating to data driven technologies, we found that the focus tends to be on individual political or consumer rights such as freedom of expression and privacy. Meanwhile, collective and socioeconomic rights are sidelined, often linked to specific technological features like algorithmic bias or lack of transparency, seen as having technical and bureaucratic solutions. This is an issue in light of the infrastructural power that technology companies now wield, creating significant dependencies on their systems, not only by monitoring and regulating human behavior but also shaping how we access services and resources, understand and act on social issues, determine what counts as expertise and knowledge, and decide who is advantaged and disadvantaged. More questions therefore have to be asked about the role that data systems should play in society and how we can empower those communities most impacted by them.
- Extensive review of literature and public debate on the relationship between datafication and social justice
- Fieldwork on the role of data-extractive technologies in the asylum process in the UK and Greece and within the EU more widely, with a particular focus on fingerprinting and EURODAC and everyday technologies such as mobile phones and cash cards.
- Fieldwork on the implementation of data-driven systems in policing in the Netherlands, Belgium and the UK, with a particular focus on risk assessment tools and recognition technologies, including speaker identification systems.
- Fieldwork on the development and uses of data-driven systems in the workplace in Greece, the Netherlands and the UK, with a particular focus on automated hiring systems and algorithmic management in call centres and postal work.
- Technical analysis of key data systems used in migration, law enforcement and work.
- Policy analysis and fieldwork on the policy process, looking at how social rights feature in EU's digital policies.
Results have shown a growing trend in relying on data collection for decision-making and organisational processes across the areas of migration, law enforcement and work. Importantly, this trend derives from a number of contextual factors that emphasises the situated nature of data-driven systems within different institutions and that also highlights the negotiations and tensions that surround the implementation of new technologies. In most of our case studies, data collection and use is closely linked to institutional and historical contexts, policy agendas and different economic interests. In the systems we analysed, there are significant contentious assumptions about not just the nature of data and the relationship between people and data, but a clear politics present concerning wider questions of governance and control that are significant for social justice.
Moreover, the project found that the widespread use of data-driven systems is often experienced as particularly harmful amongst marginalised and disadvantaged groups. However, often experiences of injustice are bound up with wider social contexts that shape not only the uses of data but how they may be negotiated or resisted. At the same time, in discussions about social justice relating to data driven technologies, we found that the focus tends to be on individual political or consumer rights such as freedom of expression and privacy. Meanwhile, collective and socioeconomic rights are sidelined, often linked to specific technological features like algorithmic bias or lack of transparency, seen as having technical and bureaucratic solutions. This is an issue in light of the infrastructural power that technology companies now wield, creating significant dependencies on their systems, not only by monitoring and regulating human behavior but also shaping how we access services and resources, understand and act on social issues, determine what counts as expertise and knowledge, and decide who is advantaged and disadvantaged. More questions therefore have to be asked about the role that data systems should play in society and how we can empower those communities most impacted by them.
Since the start of the project scholarly research and public debate on datafication within Europe has shifted notably. The aftermath of the Snowden leaks that revealed the nature of digital surveillance programmes across a number of Western democracies focused much of the discussion and research on concerns about privacy and the protection of personal data. More recently, we have seen a growing engagement with issues of discrimination, bias and fairness in relation to data-driven systems. These concerns have often formed part of a rapidly burgeoning field oriented towards data ethics and AI ethics.
The project has engaged with these fields of inquiry, but has sought to advance a more critical approach to studying data-driven systems by placing an emphasis on the wider contexts in which technologies are being developed, used and experienced, seeking to explore the politics of data in relation to existing social practices and historical context. By privileging a concern with social justice, the project has contributed to establishing data justice as a field that analyses data with an explicit focus on structural inequality, highlighting the unevenness of implications of data across different groups and communities in society. It has also moved the discussion on the governance of data-driven systems to consider not just questions of privacy and data protection, but human rights more widely and particularly social and economic rights.
Findings from the case studies have provided key insights into the features of data-driven systems, how they are used, and how they impact on people's lives, which have formed the basis of policy debate, particularly with regards to social and economic rights. They have also informed civil society campaigning that has sought to integrate data issues into wider social justice agendas, such as those focused on workers' rights or anti-discrimination.
The project has engaged with these fields of inquiry, but has sought to advance a more critical approach to studying data-driven systems by placing an emphasis on the wider contexts in which technologies are being developed, used and experienced, seeking to explore the politics of data in relation to existing social practices and historical context. By privileging a concern with social justice, the project has contributed to establishing data justice as a field that analyses data with an explicit focus on structural inequality, highlighting the unevenness of implications of data across different groups and communities in society. It has also moved the discussion on the governance of data-driven systems to consider not just questions of privacy and data protection, but human rights more widely and particularly social and economic rights.
Findings from the case studies have provided key insights into the features of data-driven systems, how they are used, and how they impact on people's lives, which have formed the basis of policy debate, particularly with regards to social and economic rights. They have also informed civil society campaigning that has sought to integrate data issues into wider social justice agendas, such as those focused on workers' rights or anti-discrimination.