Data is integral to our society: it underpins operations, policy, and decision-making across government, businesses, and civil society, and so plays an essential role in our day-to-day lives. Access to high-quality data also makes new kinds of products, services, and activities specific to data – such as advanced data analytics and digital technology like artificial intelligence (AI) – possible. So it is important that major national data assets, such as the government’s official statistics, are representative of our society and accessible by all as a public good.
On 3 March 2021 the Open Data Institute (ODI) convened the ‘Inclusive data roundtable’ in partnership with the Ada Lovelace Institute and the Centre for Public Data, bringing together representatives from government, academia, funders, civil society and community organisations.
The aim of the roundtable was to catalyse discussion and creative thinking as we prepare the ODI’s response to the ONS Inclusive Data Taskforce consultation, so the meeting was structured around a series of provocations. These provocations are included below with the speakers’ permission, and we encourage you to explore them and consider some of the key questions that they prompted for us.
We’re also publishing here our report ‘Inclusive data: perspectives from a roundtable discussion’, which includes a case study provided by the Romani Cultural and Arts Company, and an ‘Inclusive data resource list’ as a ‘living document’ that anyone can contribute to. You can email us suggesting additional resources until Monday 22 March. We hope you find it useful and share it with others. And in the meantime check out this introduction to the ONS Inclusive Data Taskforce, including ways to engage with them.
The below audio clips were recorded remotely.
Provocation 1: How we think and talk about inclusive data – Dr Mahlet (“Milly”) Zimeta, Head of Public Policy, ODI
Hello, my name is Mahlet Zimeta, or Milly for short, and I’m head of public policy at the Open Data Institute. I’ll be talking briefly about ideas and language. Well, it’s a real honour to be gathered today to talk about inclusive data. And it will be exciting to see the directions that the discussion goes in. As we were putting this event together, we face some interesting questions about scope. Why this? Why now? What has changed in society or in technology in the last five years to make inclusive data such an important and timely topic? And what could change in the next five years? When we talked about it as a team, we will have very different responses. And why here? What is the scope of inclusive data? Should we be considering global equity in data? Or just considering the country we are in? How you answer that question might depend on what you see is the important changes in the last five years. And the important changes that lie ahead. Preparing for this event has been mostly exciting, but in some ways, also humbling to encounter the limitations of my knowledge and experience. Data gaps exist not just in national statistics, but in my own understanding concepts and vocabulary. This might be true for others here too. So if during the discussion, you observed these sorts of data gaps, I encourage you to let us know. Related, thinking about some of the topics we are going to discuss prompted me to reflect on understanding concepts and vocabulary in general. And I thought to myself, how might my perceptions change if instead of talking about inclusive practice being complex and challenging, I thought about it as being rich and sophisticated. Or instead of it being difficult, I thought about it being not-necessarily-easy-at-first, or not-necessarily-easy-all-the-time. Finally, I thought about whether there’s any area of my life or my career, where I comfortably think, yes, I have fully mastered that. And the answer is no. In fact, some of the most rewarding things I am involved in are activities or areas where I continue to learn and where the subject itself is not fixed and is continuing to develop. So I like to see inclusive practice in those terms. And these discussions about inclusive data as part of that exciting learning.
Some key questions
- What has changed in the last five years? And what could change in the next five years?
- Can ‘inclusive data’ be bound by national borders? Should it be?
- Is there a difference between how we talk and feel about complexity and uncertainty in a subject like physics, compared with equality, diversity and inclusion? If so, why? And what are some of the practical consequences?
Provocation 2: ‘You can stuff your data’: the currency of experience and the goals of inclusive data – Tracey Brown OBE, Director, Sense about Science
Hi, thank you. Thanks, Milly, this, it’s great to be joining you. So I come at this as director of Sense about Science from the other end of the telescope, which is people engaging with the outputs of government research and statistics, and work with communities who are concerned about things like weather, air pollution is affecting the rates of disease in their area, thinking about people who want to question whether hospitals statistics are made up to fit with government’s Covid plans, or can they be trusted, and that kind of thing. So we work with people in different communities and try to engage them in using the outputs of government research and statistics to reflect on their experiences and to express their own concerns and what they need. And the kind of premise of that is that statistics are the currency of public life, they enable us to describe the way the world is, and also the way we think it should be. So they’re enabling, and in ways that we find people rarely think about when they’re thinking about issues like national statistics. So good to give you an example of that, you know, people who want to reflect on whether or not working in agriculture is reasonably safe compared to other sections of industry, you can actually look at what the safety record is in agriculture, compared to manufacturing, and so on.
This is the way historically there’s a long and noble tradition of statisticians providing people with that currency to express their position in the world and what they think is right or wrong with that. And the sorts of things that we’ve done, therefore, are about bringing people much more into that kind of relationship with power and decision making. So we run evidence week in Parliament, which is opened by people with those kinds of concerns, asking questions to Parliament about whether in fact, they’re using the best available evidence to look at the experience of policies across the UK and how they’re falling on people. An example of that was in 2019, with the former National Statistician, we ran a question or a conversation with the National Statistician. And I’m mentioning those because they were incredibly surprising to everybody concerned, I mean, to our decision makers and legislators, and also, I think, to some people in the world of the analytical professionals in government, which is that people have concerns and questions that are actually posing interesting questions for gathering statistics. And we need to be hearing more of that. And I mean, they included things like a guy from Kendal, asking about employment retention of people with learning disabilities. Included young fishermen from the Medway, asking about whether government actually measures any of the things that they do by way of marine conservation, or you know, whether it’s something that’s totally ignored at a national level. Someone on a zero hours contract, not surprisingly, wondering how things were going to change in terms of accounting for their experience in national statistics. All sorts of really, really interesting questions that show that people are concerned to have that currency, and to have those means to express, you know, what their experiences are. And so in part, engaging people in this way is about tools and access and knowing where to look and knowing what to look for. And obviously, we at Sense About Science spend a lot of time helping different communities to find that. But it’s also about motivation. And a key part of that motivation is understanding that there’s independence, that they aren’t being fed a line, that they can find a way of describing their experience and having it noticed, you know, in a way that they feel confident that there are people out to bat for the importance of those statistics and being reliable.
So in my view, there are two aspects to whether data and statistics are inclusive. And those are both what’s counted, and what counts. And I think they’re a bit different to what’s counted, the taskforce has opened up some really important questions. And I think many civil society organisations are raising things that no one had actually thought about before, about the way that the information is gathered, and who gets included in that and which experiences get included in that. And clearly, there are sections of the population that are missed.
But in our response to those, we need to think about, you know, the questions that were posing and what counts in responding to them. So I would really highlight the fact that there was a kind of culture change that was brought about by the former National Statistician, I think was incredibly important in the analytics professionals in government, which is to understand that what you’re in the business of is not to produce data and statistics, but to answer questions. And that for us chimes very much with the public – if they understand that then they understand the need to gather certain information. And in fact, they see value in contributing that information about themselves, rather than an abstract question of trust. And there are though– I think it’s a great development, I think it’s one that, you know, must continue to be pushed. And I hope that that cultural shift of understanding that that’s what we’re doing – we’re trying to answer questions, and therefore asking ‘are people missing or experiences missing in the way that we answer those questions?’ I really hope that that is something that is carried through. But in doing that, I think to bring to a final point, I think that there is still a majoritarian approach to numbers that needs to be thought about. And I see it in things like the Government Digital Service’s approach to engagement and public engagement on the different departmental websites, for example, where, when they did an analysis, they looked at the fact that people mostly went onto government websites to get passports and driving licences sorted out. And because of those big numbers, they therefore reorganise the whole of that interface with government, for the population as providing those services. So as service users– but you know, there are times when a very small amount of engagement is incredibly important, you know, you could say, what’s the point of DEFRA publishing it’s flood mitigation statistics when only six people look at them. But if those six people are farmers who represent the largest share of the UK beet crop and flood lands, then that really counts in terms of answering the questions or raising issues that maybe haven’t been incorporated. So I think there is this approach culturally, to the way that government information is put out more generally, that I think ONS and others need to deal with.
There are a lot of concerns that have come from people we work with about the fact that people are counted – in the sense that they are a number, they are sort of in the resident population, they do get picked up in it in the sort of simple question of another number, another one – but that the difference is in their experiences are hidden by the way the data is used because of this kind of majoritarian approach. To give you an example of that, you know, a social worker from Lancaster – one of the questions put to the National Statistician, previously was about the fact that national statistics on Adult Social Care actually represent a huge diversity within them. And that that doesn’t come across by producing these kind of national level statistics. So there are many, many examples of that about the way that the data that we already collect is masking differences in experience. You know, the ageing skills of the workforce, for example, the four nation stuff that Dawn’s already alluded to, which is that, you know, whether experiences are sort of squashed. And big regional differences are squashed as well, by putting things together in these numbers. And I think we get over that by asking– by making clear that we focus on what are the questions that people want answers to, and therefore what do we need to gather in response to those. And I think this is the pathway – a kind of hand-in-hand sort of pathway – using the opportunity of talking about inclusion in this way to address something that many of you may remember back in the Brexit days when Anand Menon who’s a professor at Kings was giving a talk on Brexit and leaving the EU, and sort of was invoking economics and the likely plunge in the UK’s GDP. And he said this to the audience and a woman yells back, that’s your bloody GDP, not ours. And I do think that while people might not relate to that statement, a lot of people in the country do when they look at national statistics, and I think this is an opportunity for us to reiterate that it’s not about producing a number. It’s about asking– answering a question and working out what counts in answering that question.
Some key questions
- What’s the difference between producing data and statistics, and answering questions?
- What are the questions that count right now? And what can help us ask the right questions?
- What are the questions that we should be asking? And what data do we need to answer them?
Provocation 3: ‘…walk softly so as not awake the sleeping ones’: invisible men, trust, personal safety and the ‘downlow’ – Dr Rob Berkeley MBE, Managing Editor, BlkOut UK
I’m an invisible man, but a man of substance, of flesh and bone, fiber liquids – and I might even be said to possess a mind. I’m invisible, understand, simply because people refuse to see me. When they approach me, they see only my surroundings, themselves, or figments of their imagination – indeed, everything and anything except me.
That’s Invisible Man by Ralph Ellison, written in 1952.
I’m Rob Berkeley, Founder and Managing Editor of BlkOut UK. BlkOut UK brings together bi, gay and trans men of African descent in the UK, and mobilises them to build corrective responses to the challenges that we face. Our work is relationship-centred and focuses on unleashing the benefits of community. For example, resilience support, information networks, self esteem and reciprocal ties for those who identify with unnecessarily contested categories of black, queer and male. We started in 2016 as a web platform, seeking to amplify our voices, to marshal conversations between us about our lives, our dreams and aspirations. Conversations for which we have no infrastructure, despite at least 40 years of organising. We describe this early phase as coming out of the quiet. We were never voiceless. Rather, we were unheard. We were invisible men squeezed into others’ narratives because of our invisibility. In mainstream media, we are exotic, but hard-done-by niche minority, perfect for the soap opera cliffhanger. Stuck-in-the-tunnel, guess-who’s-coming-to-dinner moment, a dramatic device rather than three-dimensional human.
To back media outlets, we were fodder for the shock jocks, proof of migrant cultural bereavement, grist to the mill for attention seeking controversialist, whether in the newspaper column, from the church pulpit, or set to a reggae dancehall beat. to LGBTQ media, we will tolerated, but unloved. Maybe because the pink pound missed us. Maybe because we are a reminder of our society’s and their newsroom’s need for a long overdue reckoning with racism.
We began a conversation where we could define ourselves rather than be defined by others. We were therefore never BAME, and were able to acknowledge the different trajectories and drivers organising and community building between black lesbian, bi and trans women, and bi, gay and trans men. Very quickly, we began unearthing stories of young men lost, for want of companionship, a friendly ear, someone who understands what they’re going through. Men lost seeking the solace of one more party, the ‘chill out’ with no chill, too often with tragic and sometimes fatal consequences. Not counted or discounted. These stories rarely came to wider public consciousness. So we became determined to intentionally build our futures together to make space for us – space in which we could acknowledge each other, to reclaim and reframe the idea of community, building on the examples of our forebears who embrace their invisibility to survive. Indeed, invisibility is our habit, a habit that may well be our superpower, if it enables us to see what others do not, to face up to the reality of a modern society in which there are overlapping, interdependent, porous and fluid publics, rather than a single contested public space.
The concept of a single public only delivered so-called ‘respectability politics’ that excluded us further. The challenge for us in 2021, however, is not to be respectable, but rather to be our authentic selves in a society that learns to live with and value difference. The conversations we had have started to show us that black bi, gay and trans men needed each other, far more than I and my co-editors had initially realised. In November 2020, we published results of our community-led participatory research project, In The Picture. We found that as younger men, we’re more likely than other black men – an already disadvantaged group in comparison to white men – to be homeless, suffer poor mental health, and experienced severe alienation. Much more likely when compared to other bi, gay or trans men to be living with HIV. Our findings suggested that we are more likely to be in precarious employment or underemployed, to misuse drugs or alcohol to cope, and with weaker networks, fewer friends or family to turn to when in need, and made more vulnerable to exploitation. As older men, we are more likely to be alone, often feeling unseen and lonely, in part as a result of losing so many to HIV/AIDS in the 1980s – as Channel Four’s ‘It’s a Sin’ has reminded us so powerfully recently.
Almost every statistic that we could unearth pointed to the negative. Almost worse, it seems as if no one had been able to do much more than pick up the pieces afterwards, to administer sticking plasters, dole out the antiretrovirals or contract the next of kin. Unheard back queer man have been seen as a thing to be saved, incapable of taking control of our own lives – a further contribution in the long term, to alienation and dependency, reinforcing our invisibility. There have been numerous occasions when I disclose my sexuality to be met with looks of pity. ‘Wow, black and gay, there must be doubly hard.’ It doesn’t have to be that way. However, we are under no illusion that the collection of data will be the magic bullet to solve all these problems.
Quentin Crisp once wrote, ‘It’s no good running a pig farm badly for 30 years, while saying, ‘really I was meant to be a ballet dancer’. By then, pigs will be your style.’ For those who’ve been invisible, they can become a style. Visibility after all, does not automatically mean inclusion. Indeed, it can mean increased vulnerability. Justin Fashanu, the first top flight footballer to come out 30 years ago will have celebrated his 60th birthday last week, had he not taken his own life in 1998, hounded by accusations of sexual misconduct. In 2004, Oprah Winfrey wasn’t winding up Buckingham Palace with royal tittle-tattle. Instead, she was seeking to expose the ‘down low’, claiming – in language which is insensitive but still current – that AIDs was a leading cause of death by African Americans aged 25 to 44. ‘That is startling,’ Oprah says. ‘All of my alarms went off. Women, college students and people over the age of 50 are at greater risk than ever before.’ ‘And,’ as Oprah discovers, ‘men living on the ‘down low’ may be one reason why’. So, given the creativity and confounding nature of work with black queer men since 2004, we witnessed a number of men adopt the ‘down low’ label as a badge of honour, the visibility somehow seen as a benefit. Over the past couple of weeks, we’ve seen the triumph of LGBT rights in Ghana and their organising being undone by the conservative campaign between Catholic bishops, tabloid media and politicians unwilling to rock the boat in an election year. Their community-built support centre was raided by the police and the staff are currently in hiding. Visibility can feel like losing one community that offers resilience against racism, with no guarantee, and more-than-enough focus the experience of racism [unclear] to LGBTQ communities in bars, clubs or digital apps. The question is whether visibility is a risk worth taking.
Now I don’t tend to subscribe to Afro-pessimism – there can and will be progress. However, we recognise and work daily with the contradictions and negotiations of a fluid and dynamic identity. We are seeking to engage the estimated 15 to 20,000 black queer men in the UK in our work, or certainly to get to a tipping point where we can influence each other positively, and build balanced support. The initial stage of this work requires us to build trust in each other, and to change the habit of invisibility, to habits of solidarity.
And just to finish with a quote from Ralph Ellison again. ‘I remember that I’m invisible and walk softly so it’s not to awaken the sleeping ones. Sometimes it’s best not to awaken them. There are a few things in this world as dangerous as sleepwalking.’
Some key questions
- What are the habits of invisibility? And when might they be preferable to visibility?
- What changes when the observer becomes the observed? What might those who are considered invisible by a society be able to ‘see’?
- How might data practices strengthen community solidarity?
Provocation 4: Protected characteristics and unintended consequences – Dr Jeni Tennison OBE, VP and Chief Strategy Adviser, ODI
Thanks very much, Milly. I’m Jeni Tennison. I’m Vice President and Chief Strategy Advisor at the ODI. And I’m going to talk about some work that we did on monitoring equality in digital public services. This was work that we completed at the start of 2020. It was funded by the Legal Education Foundation, and Natalie, who is on the call today. And led by Renate Samson and Edafe Onerhime, who actually did the work. So I’m reporting on their work. So the the thing that we were looking at is that as more public services become digital, and we’ve seen that really accelerated over the past year, the providers of those public services still need to satisfy their public sector equality duty, so make sure that there isn’t discrimination in the public services that they provide. And of course, there are multiple kind of sources where there could be discrimination in digital public services – from digital exclusion, just accessibility of websites, the accuracy of text, so particularly voice and facial recognition, things like algorithmic bias that we know are problematic. So all of those different ways in which there can be discrimination. But how do we know whether a particular digital public service is discriminating? Of course, in order to understand that and assess it, you need to collect data about the protected characteristics that you need to be monitoring equality around and ask questions like, who is actually accessing the service? What kind of experience do they have with it? Is there any differences there? What kind of outcomes are there from the engagement with the service as well. And it’s interesting, at the height of the kind of Black Lives Matter stuff in 2020, there were a bunch of claims that you couldn’t collect that kind of information, in particular around race, because of GDPR, when in fact, that isn’t the case. As long as you have a clear purpose, informed consent, and you separate out the data that you’re collecting about people in order to assess the qualities of the service from what you’re collecting about them in order to deliver the service, then it’s fine, right. And we should be doing it in order to understand better how the services are working.
And so we had three recommendations out of that work. The first was simply that services should be collecting that kind of data. And we also think it’s important, you know, that that data collection is actually used to inform redesign of services, and is made public as much as that’s possible to do and particular statistics about the use of those services we think are important. The second set of recommendations was to develop some standards around it. So that can be about form components, what questions actually get asked when you’re monitoring those protected characteristics and around service delivery, what kind of publication formats might be used in order to publish data about who is using the service, and also standards about how to embed the actual collection of that data into the sequence of the service that you’re providing. You know, do you do it out front? Do you do it at the end? How do you make that work? How do you manage consent for the collection of that information? And then the third recommendation was that we really just need more research around this area And in particular– so we really recognise that there are limits about focusing on protected characteristics when there are other things that can cause issues or cause discrimination and other areas of disadvantage and privilege that could be and maybe should be captured. So more research about what is useful, or how to decide which things to be collecting for a given particular service. We also recommended that there was more focus on the impact of monitoring on users. Because of course being asked those questions may in itself put people off from using the public service or diminish trust in why it’s being collected and therefore in government and so on. So we need to have a better understanding about what that impact looks like so that we can understand, you know, is it worthwhile to do compared to that impact? And along the same kind of lines, we’re also interested in if there is distrust about how that data might be misused or reused, do people actually lie or give misleading information when you ask those kinds of questions. So not just not respond, but also actively give wrong information. So I think we have to recognise that data collection in and of itself affects people’s behaviour. It’s not just a neutral activity. And so we need to have more understanding about how that impacts people’s behaviour. So that’s it, that’s what we did, and I welcome discussion around any of this.
Some key questions
- Can an institution that isn’t equitable still have an equitable approach in its data and digital practices?
- Can inclusive data be achieved as a standalone in just one sector or domain, such as health or transport?
- Should there be an equivalent of the public sector equality duty for industry and civil society?
Provocation 5: Beyond protected characteristics – Anna Powell-Smith, Director, Centre for Public Data
‘Beyond protected characteristics’, Anna Powell-Smith, presentation slides
Some key questions
- Are there patterns around where and when data is ‘missing’?
- What is the difference between the ‘missing numbers’ of data that is available but not collected, data that is collected but rejected for inclusion, and data that is collected but not shared with others?
- How can the practicalities of collecting and managing data over time be more sustainable?
Provocation 6: Intersectional identities – Reema Patel, Head of Public Engagement, Ada Lovelace Institute
‘Intersectional identities – A lightning talk! How do intersectional identities interact with data systems?’, Reema Patel, presentation slides
I’m hoping everyone can see the slides I’m going to screen share.
It is a lightning talk. Five minutes, I’ve got to do this topic justice, so forgive me if I don’t do it justice. There’s a reason for that. So my question is how do intersectional identities interact with data systems, and I was desperately hoping maybe you would come in on Isaac’s point, because there’s so much there that overlaps with what I’m talking about, so I almost want to, to build out from that really interesting intervention.
So just to build on the theme of counting, this reminds me of a very famous quote, from sociologist William Bruce Cameron, ‘Not everything that counts can be counted, and not everything that can be counted, counts.’ And the reason this is really interesting, and really important to that intersectionality, it strikes me is it’s one of those quite complex issues that datafication and data really resist. And there is a really important question, which is that do we do we need to, or do we want to go that far? And what are the implications and, and challenges around that? So there’s a really interesting dynamic here, which is that on the one hand, there’s the need to divide– need to capture in order to understand issues of inequality. But also, it’s going to be difficult to do this, if we want to do issues like inequality, justice. So that’s an opening gambit, and very much in line– in keeping with Milly’s approach to being a bit of a devil’s advocates here.
Why do inclusive approaches to data matter? Well, simply because I think that if we get this right, if we make sure that we haven’t got missing data or missing numbers, then that would be a sign that we’ve got an awful lot of other structural conditions right. And that would be a sign that people feel a strong sense of confidence and trust in the way their data is being used, it will be a sign that there are fairer equitable systems, and those equitable assessments are engendering societal outcomes, and mitigating risk and harm. And that would deal an increased mandate for and support and active participation in governing data. So this is why I think it matters, but I’m keen to hear your views as well.
And just on that timeless classic Alice in Wonderland, this question of intersectional identity, there was this moment where the caterpillar asked Alice, who are you? And Lewis Carroll writes, you know, this was not an encouraging opening for a conversation. And Alice said, I don’t really know, I knew who I was when I got up this morning, but I think I must have changed several times since then. And again, a challenge for datafication. Can we really capture the fluid nature of who a person is, in this way?
So what’s the working definition of intersectionalities, I’m quite influenced by some of the thinking in the US in this space. And the NCCJ define this as the interconnected nature of social categorisation such as race, class, and gender as they apply to a given individual or group, regarded as creating overlapping and interdependent systems of discrimination or disadvantage. And on the right, you can see that there’s an awful lot there. And also, as I will hopefully expand upon more to think about than just this definition, but it’s a working definition.
And so some, some of my own reflections on this definition. The first is that definition relates to disadvantage, but there’s also the thorny question of privilege. So some of us may simultaneously experience privilege and oppression. So I’m the daughter of two migrants who came to the UK, but I also am a Cambridge-educated philosopher. And, you know, there’s a really interesting, weird dynamic that I personally feel when I’m talking about these conversations. Identities and not just identity. And so remember Lewis Carroll’s ‘Who are you?’ question. You know, that identities are not always fixed, and they’re dynamic, and that that is challenging for this kind of question. Let’s try to understand or capture everything on a dataset. And this has come up a lot, the invisibility question of rights to refusal. So not everyone’s experience of privilege and oppression is visible. And invisiblity can be a safeguard so that – we’ve already heard this – you know, the idea of invisibility as a superpower. And so what is ethical here? Should we expect everyone to reveal themselves or are there less intrusive ways of getting at the issue? And then the last thing is that on the flip side, you know, visibility can be quite stigmatising, and I’ve already kind of indicated some of the ways in which that happened. You know, you think about eugenics, the Holocaust, mental health stigma, state responses, historically HIV and AIDS, the list is endless. So we need to be aware and design around that.
Identity is just one part of a picture, no person is an island. And so this wonderful rainbow that comes from the conversation and health inequalities illustrate, there’s not just a dynamic relationship between individual aspects of an individual’s identity but also between who it is personally and their relationship with the environment. And I go back to the Alice in Wonderland example. Perhaps Alice is quite confused about this question of who she is because she’s been through quite the washing-machine style journey, and in this process, you know, she’s found herself transported to a new environment, new world, and that caused her to ask some challenging questions about who she herself is.
And then just to land on a very practical note, I wanted to use the use case of the expansion of the shielded patient list and the QCovid algorithm to illustrate that, in the context of datafication and data, these questions are really difficult. They’re difficult because being on the shielded patient list can engender inequalities if you’re expected to not go to where– courts restrict your interaction, that itself can perpetuate inequalities. But also being off that list means you don’t have allocation– your prioritisation for vaccine. And these things are just not that simple or straightforward. They’re difficult decisions here. And we need to think about risk mitigation design and quite a nuanced approach. So I will end on that note, and just say, I have really enjoyed this conversation. I’m really keen to hear what people think about this.
Some key questions
- Can inclusive data exist without fair, equitable and inclusive systems?
- What are the opportunities around data and digital technology in social systems with inequalities and intersectionalities?
- What are the tools or approaches that would allow us to integrate emotional and political intelligence with statistical rigour in our data practices?
We’re planning to stay active in this area, to continue the conversation, and to bring in more voices. We’d love to hear your thoughts on what would be interesting or helpful – let us know on Twitter @ODIHQ or email firstname.lastname@example.org. And in the meantime we encourage you to engage with the ONS Inclusive Data Taskforce consultation – the deadline for consultation responses is Friday 26 March.
Think global, act local: highlights from our spring 2021 policy plans
- Data infrastructure
- Alan Walker
- Dr Mahlet (Milly) Zimeta
- Gavin Freeguard
- Jeni Tennison
- Mark Boyd