Using Artificial Intelligence in public services – does it breach people’s privacy?

By Ros Edwards, Sarah Gorin and Val Gillies

As part of our research, we recently asked parents what they thought about the use of data linkage and predictive analytics to identify families to target public services.

They told us that they didn’t trust these processes. This was particularly the case among marginalised social groups. In other words, the groups of parents who are most likely to be the focus of these AI identification practices are least likely to see them as legitimate. Now a new report by the United Nations High Commissioner of Human Rights, Michelle Bachelet highlights major concerns about the impact of artificial intelligence, including profiling, automated decision-making and machine-learning, upon individuals’ right to privacy. 

The report makes a number of recommendations, including a moratorium on the use of AI systems that pose a serious risk to human rights and the banning of social scoring of individuals by Governments or AI systems that categorise individuals into groups on discriminatory grounds.

The right to privacy in the digital age: report (2021) builds on two previous reports by the High Commissioner looking at the right to privacy in the digital age and incorporates views of international experts at a virtual seminar, as well as responses to the High Commissioners call for input into the report from member states, including the U.K.

It examines the impact of digital systems such as artificial intelligence in four sectors, including public services. Artificial intelligence is used in public services such as social care, health, police, social security and education in a range of ways, such as decision-making about welfare benefits and flagging families for visits by children’s social care services.

Concerns are expressed about the linking together for example of large health, education and social care data sets with other data held by private companies, such as social media companies or data brokers who, the report says, may gather information outside protective legal frameworks. The involvement of private companies in the construction, development and management of public sector data systems, also means they can gain access to data sets containing information about large parts of the population.

There are additional concerns about the potential inaccuracy of  historic data and the implications of that for future decision-making. The report states that these systems unequally “expose, survey and punish welfare beneficiaries” and that conditions are imposed on individuals that can undermine their autonomy and choice.

A digital welfare fraud detection system was banned by a court in the Netherlands, ruling that it infringed individuals’ right to privacy. The system provided central and local authorities with the power to share and analyse data that were previously kept separately, including on employment, housing, education, benefits and health insurance, as well as other forms of identifiable data. The tool targeted low-income and minority neighbourhoods, leading to de facto discrimination based on socioeconomic background.

The recommendations in the report include:

  • using a human rights based approach
  • ensuring legislation and regulation are in line with the risk to human rights, with sectors including social protection to be prioritised
  • development of sector specific regulation requirements
  • drastic improvements to efforts regarding transparency, including use of registers for AI that contain key information about AI tools and their use, informing affected individuals when decisions are being or have been made automatically or with the help of automation tools, and notifying individuals when the personal data they provide will become part of a data set used by an AI system.

With concerns about the risks to the human rights of individuals and families about the use of data linkage and predictive analytics, it is vital to pay heed to the UN High Commissioner’s call for a moratorium. Public authorities need to pay meaningful attention to the lack of social legitimacy for AI, as evidenced in our research, and to ask themselves if the risk of further distrust and disengagement from already marginalised social groups, and consequences for a cohesive and equal society, is worth it. 

Question marks over data analytics for family intervention

by Ros Edwards, Sarah Gorin and Val Gillies

The National Data Strategy encourages the UK’s central and local government to team up with the private sector to digitally share and join up records to inform and improve services. One example of this is the area of troublesome families, where it’s thought that the use of merged records and algorithms can help spot or pre-empt issues by intervening early. But there are questions over this approach and this is something our project has been looking into. In our first published journal article, we have been examining the rationales presented by the parties behind data analytics used in this context to see if they really do present solutions.  

The application of algorithmic tools is a form of technological solution; based on indicators in the routinely collected data, in an effort to draw out profiles, patterns and predictions that enable services to target and fix troublesome families.  But local authorities often need to turn to commercial data analytic companies to build the required digital systems and algorithms.

In our paper we analysed national and local government reports and statements, and the websites of data analytic companies, addressing data linkage and analytics in the family intervention field.  We looked in particular at rationales for and against data integration and analytics.  We use a ‘problem-solving’ analytic approach, which focuses on how issues are produced as particular sorts of problems that demand certain sorts of solutions to fix them.  This helps us to identify a double-faceted chain of problems and solutions.  

Seeking and targeting families

Families in need of intervention and costing public money are identified as a social problem and local authorities given the responsibility of fixing that problem. Local authorities need to seek out and target these families for intervention. And it is experts in data analytics that, in turn, will solve that identification problem for them.  In turn companies are reliant on citizens being turned into data (datafied) by local authorities and other public services.

We identified three main sorts of rationales in the data analytic companies promotion of their products that will solve local authorities’ problems: the power of superior knowledge, harnessing time, and economic efficiency.

Companies promote their automated data analytics products as powerful and transformational.  They hand control of superior, objective and accurate, knowledge to local authorities so that they can use profiling criteria to identify families where there are hidden risks, for intervention.  And their systems help local authority services such as social care and education collaborate with other services like health and the police, through data sharing and integration.

Data analytics is presented as harnessing time in the service of local authorities as an early warning system that enables them quickly to identify families as problems arise.  It is the provision of an holistic view based on existing past records that local authorities hold about families, and the inputting of ‘real time’ present administrative data on families as it comes in.  In turn, this provides foresight, helping local authorities into the future – predicting which families are likely to become risks in advance and acting to pre-empt this, planning ahead using accurate information.  

Another key selling point for data analytics companies is that their products allow economic efficiency.  Local authorities will know how much families cost them, and can make assured decisions about where to put or withdraw resources of finances and staffing.  Data analytic products produce data trails that cater for local authorities to prepare Government returns and respond to future central Government payment-by-results initiatives, maximising the income that can be secured for their constrained budgets.

Questions to be asked

But there are questions to be asked about whether or not data linkage and analytics does provide powerful and efficient solutions, which we consider in our article.  Concerns have been raised about the errors and bias in administrative records, resulting in unfair targeting of certain families. 

Particular groups of parents and families are disproportionately represented in social security, social care and criminal justice systems, leading to existing social divisions of class, race and gender built into the data sets.  For example, there is evidence that racial and gender profiling discriminations are built into the data, such as the inclusion of young Black men who have never been in trouble in the Metropolitan Police Gangs Matrix.  And automated modelling equates socio-economic disadvantage with risk of child maltreatment, meaning that families are more likely to be identified for early intervention just because they are poor.  On top of that, studies drawing on longitudinal data are showing that the success rates of predictive systems are worryingly low. 

All of which raise a more fundamental question of whether or not algorithms should be built and implemented for services that intervene in families’ lives.  In the next stage of our research, we will be asking parents about their views on this and on the way that information about families is collected and used by policy-makers and service providers.  

Problem-solving for Problem-solving: Data Analytics to Identify Families for Service Intervention

Presentation British Sociological Association Annual Conference 2021

Project PI Ros Edwards presented findings from our project at the British Sociological Association annual conference 2021.

The paper, Problem-solving for Problem-solving: Data Analytics to Identify Families for Service Intervention looks at the way that the promise of technological fixes in the family policy field has set up a set of dependencies between public services and data analytic companies, entrenching a focus on individual families as the source of social problems rather than social conditions.

Watch Ros’ presentation.

The paper that was the basis of Ros’s presentation has now been published in Critical Social Policy

Would you like to take part in our research?

We are looking for parents to take part in the project. We want to know your views and experiences of the way that information about families is collected and used by policy-makers and service providers. 

There are two ways you can take part:

  1. As part of a group discussion – If you are a parent (of at least one child aged 16 or under) you can take part in an online group discussion that will last about 45 minutes.
  2. In a one-to-one discussion -If you are a parent (of at a least one child aged 16 or under) and have had contact with family support services (this may be children’s social work services, early years or a voluntary organisation that supports families) you can take part in an individual discussion with us that will last about 45 minutes, either online or by phone.

All group and individual participants will receive a £25 e-voucher in thanks for their time and trouble, and we can provide a top-up voucher for participants using pay-as-you-go.

The research has ethical approval from the University of Southampton.

If you would like to receive further information or talk about the possibility of participating in the research, please contact Sarah Gorin, University of Southampton at s.j.gorin@soton.ac.uk

Running focus groups with parents in a Covid-19 setting – how will we do it?

In this second project blog, the research team reflect on how Covid-19 and the restrictions it has placed on all our lives, has led to methodological, ethical and practical challenges in working with focus groups on parental buy-in for linking and analysing data about families. They outline the challenges they face and how they’re adapting their approach. 

For the next stage of our project, we’re conducting focus groups to explore how particular social groups of parents understand and talk about their perspectives on data linkage and predictive analytics.  Back in early 2020, we were optimistic about the possibility of being able to conduct these groups face-to-face by the time we reached this stage of our research.  Now though, it’s clear we’ll need to move online, and we’ve been thinking about the issues we’ll face and how to deal with them.

Questions we’re grappling with include:

  • What might moving online mean for how we recruit participants? 
  • How can we best organise groups and engage parents with the project? 
  • How can we develop content for online groups that will firstly, encourage parents to contribute and enjoy the research process, and secondly, be relevant to our research endeavour?

What will moving online mean for recruiting participants?

Our intention was – and still is, to hold focus group discussions with homogenous groups of parents, to explore the consensus of views on what is and isn’t acceptable (social licence) in joining together and using parents’ administrative records.

We’re using the findings from our earlier probability-based survey of parents to identify social groups of parents whose views stand out. These include home-owning parents in professional and managerial occupations, who have stronger social licence, and mothers on low incomes, Black parents, and lone parents and parents in larger families living in rented accommodation, who tend to have weak or no social licence.

Our original plan was to recruit participants for our focus groups by contacting local community and interest groups, neighbourhood networks, services such as health centres and schools, workplaces and professional associations.  We still plan to do this, but we’re concerned that the pandemic is placing huge pressures on community groups, services for families and businesses and we may need to be prepared that helping us to identify parents to participate in research may not be a priority or, as with schools, appropriate.

So we’ve also been considering recruitment through online routes, such as advertising on relevant Facebook groups; using Twitter and putting advertisements on websites likely to be accessed by parents. It’ll be interesting to see if these general reach-outs get us anywhere.

An important aspect of recruitment to our study is how to include marginalised parents.  This can be a conundrum whether research is face-to-face or online.  Face-to-face we would have spent quite a bit of time establishing trust in person, which is not feasible now.  Finding ways to reach out and convince these parents to participate is going to be an additional challenge. Our ideas for trying to engage these parents include the use of advertising via foodbanks, neighbourhood support networks and housing organisations.

And there’s the additional problem for online methods, revealed in inequalities of online schooling, of parents who have limited or no online access. Further, Covid-19 is affecting parents living in poverty especially and we don’t want to add to any stress they’re likely to be under.

Enticing affluent parents working in professional and managerial occupations to participate may also be difficult under the current circumstances.  They may be juggling full-time jobs and (currently) home schooling and feeling under pressure.  Either way, marginalised or affluent, we think we’ll need to be flexible, offering group times in evenings and at weekends for example. 

How should we change the way we organise groups and engage parents with the project? 

We know from reading the literature that online groups can face higher drop-out rates than face-to-face.  Will the pandemic and its potential effect on parent’s’ physical and mental health mean that we face even higher drop-out rates?  One strategy we hope will help is establishing personal links, through contacting participants and chatting to them informally before the focus group takes place.

We’ve been mulling over using groups containing people who know each other, for example if they’re members of a community group or accessed through a workplace, and groups that bring together participants who are unknown to each other.  Because we’re feeling a bit unsure about recruitment and organisation, we’ve decided to go down both routes as and when opportunities present themselves.  We’ll need to be aware of this as an issue when we come to do the analysis though.

We’re also thinking to organise more groups and have fewer participants in each group than we would have done face-to-face (after all, we’re not going to be confined by our original travel and venue hire budget).  Even in our online research team meetings we can cut across and interrupt each other, and discussion doesn’t flow in quite the same way.  Reading  participants’ body language and non-verbal cues in an online focus group is going to be more difficult.  Smaller numbers in the group may help a bit, but it can still be difficult to see everyone if, for example, someone is using a mobile phone.  We’ll just have to see how this goes and how best to handle it.

There’s also a dilemma about how many of the project team to involve in the focus groups. We’ll need to have a team member to facilitate the group, but previous research shows it might be useful to have at least one other to monitor the chat and sort out any technical issues. But with a group as small as 4-6 participants will that seem off putting for parents? It’s all hard to know so may be a case of trying it in order to find out!

What should we consider in developing content that’s engaging for parents and relevant to our research?

What we’ll miss by holding our group discussions online is the settling in and chatting and putting us and our participants at ease – how are you, would you like a drink, there’s some biscuits if you want, let me introduce you to … and so on.  We don’t think that we can replicate this easily.  

But we’ve been pondering our opening icebreaker – should we ask something like….

‘If you could be anywhere else in the world where would you be?’

or

‘What would be the one thing you’d pack in a lockdown survival kit?’ 

And we’re also planning to use a couple of initial questions that use the online poll function.  Here’s an instance where we think there’s an advantage over in-person groups, because participants can vote in the poll anonymously. 

After that, we’ll be attempting to open up the discussion to focus on the issues that are at the heart of our research – what our participants feel is acceptable and what’s not in various scenarios about the uses of data linkage and predictive analytics.

Ensuring the well-being of parents after focus groups is always important, but with online groups may be harder if the participants are not identified through community groups in which there’s already access to support. We plan to contact people after groups via email but it’s hard to know if parents would let us know even if groups presented issues for them. We have also given some thought to whether we could use online noticeboards for participants to post any further comments they may have about social licence after they’ve had time to reflect, but do not know realistically if they would be used.

It’ll be interesting to see if the concerns we’ve discussed here are borne out in practice, and our hopeful means of addressing them work.  And also, what sort of challenges arise for our online focus group discussions that we haven’t thought of in advance!

If you have any ideas that might help us with our focus groups, please do get in touch with us via datalinkingproject@gmail.com

A murky picture – who uses data linkage and predictive analytics to intervene in families’ lives?

In the first of a series of blogs discussing key issues and challenges that arise from our project, Dr Sarah Gorin discusses the problems encountered by our team as we try to find out which local authorities in the UK are using data linkage and predictive analytics to help them make decisions about whether to intervene in the lives of families.

As background context to our project, it seemed important to establish how many local authorities are using data linkage and predictive analytics with personal data about families and in what ways. To us this seemed a straightforward question, and yet it has been surprisingly hard to gain an accurate picture. Six months into our project and we are still struggling to find out.

In order to get some answers, we have been reaching out to other interested parties and have had numerous people get in touch with us too: from academic research centres, local authorities, independent foundation research bodies, to government-initiated research and evaluation centres.  Even government linked initiatives are finding this difficult, not just us academic outsiders!

So what are the issues that have been making this so difficult for us and others?

No centralised system of recording

One of the biggest problems is finding information. There is currently no centralised way that local authorities routinely record their use of personal data about families for data linkage or predictive analytics. In 2018, the Guardian highlighted the development of the use of predictive analytics in child safeguarding and the associated concerns about ethics and data privacy. They wrote:

“There is no national oversight of predictive analytics systems by central government, resulting in vastly different approaches to transparency by different authorities.”

This means that it is very difficult for anyone to find out relevant information about what is being done in their own or other local authorities. Not only does this have ethical implications in terms of the transparency, openness and accountability of local authorities but also more importantly, means that families who experience interventions by services are unlikely to know how their data has been handled and what criteria has been used to identify them.

In several European cities they are trialling the use of a public register for mandatory reporting of the use of algorithmic decision-making systems. The best way to take this forward is being discussed here and in other countries.

Pace of change

Another issue is the pace of change. Searching the internet for information about which local authorities are linking families’ personal data and using it for predictive analytics is complicated by the lack of one common language to describe the issues. A myriad of terms are being used and they change over time…‘data linkage’; ‘data warehousing’; ‘risk or predictive analytics’; ‘artificial intelligence’ (AI); ‘machine learning’; ‘predictive algorithms’; ‘algorithmic or automated decision-making’ to name but a few.

The speed of change also means that whilst some local authorities who were developing systems several years ago, may have cancelled or paused their use of predictive analytics, others may have started to develop it.

The Cardiff University Data Justice Lab in partnership with the Carnegie UK Trust are undertaking a project to map where and why government departments and agencies in Europe, Australia, Canada, New Zealand and the United States have decided to pause or cancel their use of algorithmic and automated decision support systems.

General Data Protection Regulation (GDPR)

GDPR and the variation in the way in which it is being interpreted may be another significant problem that is preventing us getting to grips with what is going on. Under GDPR, individuals have the right to be informed about:

  • the collection and use of their personal data
  • information including the purposes for processing personal data
  • retention periods for data held
  • and with whom personal data will be shared

As part of their responsibilities under GDPR, local authorities should publish a privacy notice which includes the lawful basis for processing data as well as the purposes of the processing. However, the way that local authorities interpret this seems to vary, as does the quality, amount of detail given and level of transparency of information on privacy notices. Local authorities may only provide general statements about the deployment of predictive analytics and can lack transparency about exactly what data is being used and for what purpose.

Lack of transparency

This lack of transparency has been identified in a Review by the Committee on Standards in Public Life who published a report in February 2020 on Artificial Intelligence and Public Standards. In this report it highlighted that Government and public sector organisations are failing to be sufficiently open. It stated:

“Evidence submitted to this review suggests that at present the government and public bodies are not sufficiently transparent about their use of AI. Many contributors, including a number of academics, civil society groups and public officials said that it was too difficult to find out where the government is currently using AI. Even those working closely with the UK government on the development of AI policy, including staff at the Alan Turing Institute and the Centre for Data Ethics and Innovation, expressed frustration at their inability to find out which government departments were using these systems and how.” (p.18)

Whilst some local authorities seem less than forthcoming in divulging information, this is not the case for all. For example, in Essex, a Centre for Data Analytics has been formed as a partnership between Essex County Council, Essex Police and the University of Essex. They have developed a website and associated media that provides information about the predictive analytics projects they are undertaking using families’ data from a range of partners including the police and health services.

So what are we doing?

As part of our project on parental social licence for data linkage and analytics, our team are undertaking a process of gathering information through internet searching and snowballing to put together as much information as we can find and will continue to do so throughout the course of the project. So far, the most useful sources of information have included:

  • the Cardiff University Data Justice Lab report that examines the uses of data analytics in public services in the UK, through both Freedom of Information requests to all local authorities and interviews/workshops with stakeholders
  • the WhatDoTheyKnow website which allows you to search previous FOI requests
  • internet searches for relevant local authority documents, such as commissioning plans, community safety strategies and Local Government Association Digital Transformation Strategy reports
  • media reports
  • individual local authority and project websites

It would seem we have some way to go yet, but it is a work in progress!

If you are interested in this area we’d be pleased to know of others’ experiences or if you’d like to contribute a blog on this or a related topic, do get in touch via our email datalinkingproject@gmail.com

What do parents think about linking information for family interventions? What we know to date.

Our project team look at responses to a pilot survey of parents undertaken ahead of their new research.

National and local government departments and services collect and hold a range of information about parents and their children. These records include details of the taxes people pay, their medical records, school data and police files. But what do parents think about the idea of the data held on their children being linked with theirs, so that government services can identify families for possible interventions? A pilot survey leading up to a new research project indicates they’re not very keen on the idea. 

Data linkage is a hotly-debated topic with arguments about better targeted, more focused public services often counter-acted with concerns around privacy and lack of trust in the organisations collecting and using the data. 

When it comes to the use of linked data to identify families where it’s thought there may be heightened risk of things such as child abuse or neglect, or truancy and anti-social behaviour, there can be few more contentious areas. But real evidence on what parents think is thin on the ground and this is where our research project hopes to make some inroads and get a better handle on things. 

Pilot survey

A voluntary pilot survey of parents carried out via the Mumsnet website and Twitter received a total of 365 responses – mostly from white mothers from relatively well-off households. We might assume, this group might feel more secure about the linkage and use of records on them and their children and that they might generally be trusting of organisations such as government departments and local councils etc. So what did we find?

Only half the parents said they had heard about data linkage and how it worked. Less than half thought it acceptable to use it to improve the planning and delivery of family support services. Far fewer (around 15 percent) thought it should be used to identify specific families who might need intervention but hadn’t asked for support or to save public money by preventing or catching family problems early. 

Their concerns included: families’ right to privacy; increasing stigma; oversimplification of risk factors; discouraging families from seeking help and problems with data accuracy and safety. About 1 in 5 did agree that the more we know about families the more the nation’s wellbeing can be improved.

Question of trust

There was little trust in organisations who might link data for the above reasons, but specific distrust of private companies with only 4 parents saying they would definitely trust them and 309 saying they wouldn’t. One participant said:

Having algorithms produced by private companies, who are not transparent, making dubious links, which do correlate with truth, is a very dangerous tool. It will not benefit society but will only benefit private companies.” 

Parents were almost entirely against government accessing financial details such as bank details, credit cards, supermarket records, CCTV and social media posts as the following comments from participants show:

More detailed and personal information, PARTICULARLY medical records/social services reports/DLA info, should not be ‘joined up’ as this breaches personal privacy.”  

“It might be acceptable to link to credit records and food shopping records on an anonymous basis to produce aggregate information or statistics for research purposes e.g. a study looking at the possible relationships between children’s diets and school attainment, or the impact of debt on parents BUT this sort of data analysis should NEVER identify individuals.”

“Government surveillance of families, without knowledge or consent, is an extremely questionable approach. Government should focus on supporting families, providing public services, creating jobs, ensuring quality of housing, eliminating poverty and increasing community capacities of resilience, care, safety, cohesion and fun.”

Lack of acceptance

So among this group of parents, where we might have expected greater levels of support for the idea of linking data for the purposes of identifying and targeting service intervention, we find in fact a substantial lack of acceptance and trust around the idea of family data linkage.  

A web-based survey of this nature gives us some indication of what people are thinking, but it’s important to try to look at this more carefully. As part of our new research project, we’re commissioning a robustly-designed and -conducted survey of around 900 parents and carrying out a range of in-depth interviews with parents in families most likely to be the target of this type of data linkage and policies associated with it.