Digital

Unlocking the Value of Data for Equality

April 26, 2023 by No Comments | Category Data, Digital, Digital Scotland

Guest blog by Carol Young, Coalition for Racial Equality and Rights

My organisation, the Coalition for Racial Equality and Rights (CRER), welcomed the chance to be involved in Scottish Government’s work on Unlocking the Value of Public Sector Data for Public Benefit. Through membership of the Independent Expert Group (IEG), I was able to bring a strong equality perspective drawn from our own extensive use of public sector data, as well as our campaigning on data improvement. The work of the IEG has now drawn to a close, and our concerns turn towards what comes next for equality in the data sharing arena. As a strategic anti-racist organisation with a focus on evidence based policy, CRER believes that data disaggregated by ethnicity should be central to all policy, service and product development.

Whether in the public sector or the private sector, effective use of ethnicity data is crucial. This allows organisations to develop a clearer picture of the potential implications of their work for Black and minority ethnic people. It’s of vital importance, because we know that scarcity or misuse of ethnicity data actively creates and maintains racial inequalities.

Looking at private sector data use, there’s a host of evidence on how data gaps disadvantage people. For instance, the data that underlies artificial intelligence development has created entrenched bias within AI systems, negatively impacting Black and minority ethnic groups. This affects BME women worst of all – facial recognition software is inherently racially biased and performs worst of all for darker-skinned women, with average error rates of 35%.

How data is used is really important, but so is how data and its implications are shared with the public. Anecdotally, one of the reasons for COVID-19 vaccine hesitancy in Scotland amongst Black and minority ethnic people was a belief that drug companies had tested them largely on white people and hadn’t considered whether they worked for, or indeed could harm, people from Black and minority ethnic backgrounds.

In fact, data from testing showed similar levels of safety and efficacy for everyone, but this wasn’t adequately publicised in Scotland. Studies suggest that white people were around three times more likely to state their intention to be vaccinated in Scotland, entrenching the risks for Black and minority ethnic individuals (many from communities already facing disproportionate severity and mortality risks). Better publicity of the testing data might have mitigated this.

Scotland’s Expert Reference Group on COVID-19 and Ethnicity uncovered a range of data failings which risked causing active harm. Their findings demonstrate that the failure to secure and use data disaggregated by ethnicity is, in itself, a symptom of structural racism.

Scottish Government has committed to improving its own use of equality data. However, across the public sector, our work on issues such as racially motivated bullying and public sector equality duty performance has shown that the availability and use of this data is patchy at best.

Once the public sector has its own house in order, there may be opportunities through data sharing to improve how the private sector considers the implications of their work for Black and minority ethnic people – where, of course, the public benefit can be robustly identified.

Within the IEG, much thought was given to how data provided to the private sector can create public benefit. Throughout this, two questions recurred – who are the public we’re referring to, and within that, who can realistically benefit? If groups who are often disadvantaged, marginalised or left behind by new innovations aren’t central to this, existing inequalities will worsen.

The IEG’s work identified a need for more systematic approaches to resolve the inherent challenges posed by sharing data with the private sector. Its recommendations and findings are only the beginning of a wider conversation about unlocking the value of public sector data for public benefit. This will encompass data holders and users across sectors, and of course, the public themselves. It’s clear that at all levels of that conversation, equality has to be front and centre.


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