The Journey of the DDI ‘Women in Data’ Campaign

I arrived at Data Driven Innovation in January 2019 to lead on the Women in Data project. With a small team, we got to work with a rough spec and fairly straightforward aim of capturing the professional contributions of women in data science, tech and innovation work in Edinburgh. We had an approximate idea of how many we would interview, beginning with a very reasonable 15-25.

Eight months on, we now have a volume, breadth and depth our imagination didn’t stretch to – CEOs, MSPs, students, managers, teenagers, mothers, and scientists, junior through to senior. The project has unfolded as a snapshot of the universe of women in Scotland’s booming data and STEM fields. 

These women are not just surviving against the odds of their industries being stacked against them, but thriving, some using equipment and technologies so advanced most people don’t even know they’re being used, and inventing, innovating, changing the world every-day in the four walls of their offices, labs and homes.

My inbox became unmanageable – which I’m sure anyone working in the university sector appreciates – but this was for the right reasons. Working at maximum capacity, we still only interviewed the tip-of-the-iceberg of women who were suggested. 

 

Core findings

What struck me in the interview recruitment process was the interconnectedness of women in workplaces, their willingness to lift up others and recommend them to be interviewed, and the genuine enthusiasm from both men and women to see their workplaces change. 

I was moved by the gender inequalities that women managed in their work, particularly when it came to the ‘motherhood penalty’ and the impact of sexism on participants’ perceptions of their skills and their confidence to talk about the profoundness of their work. 

I was intrigued by disparities between participants’ views of the ‘women in STEM issue’. This brought up damning views on the scale of sexism in our workplaces, alongside careers that were not particularly touched by gender equality matters.The participants’ closeness to feminist issues seemed to be shaped by many things: the level of support received from parents, peers and partners, their familiarity with being the only woman, the prestige of their education and how this shaped perceptions of their own skills, the representation of women in specific disciplines – biology and linguistics, for example, are sciences where women are better represented than physics or chemistry. 

Their feminist position would also fluctuate at different career stages, where inequalities could become visualised when women had a child or were made redundant. Some opted for a ‘get on with it’ attitude over a critical one  – two very different but equally understandable and legitimate approaches to operating in male-dominated environments. 

 

What’s the issue?

As the months I went on and the project evolved – I asked the question – what is the best way to describe and place the project? Is it research, is it journalism, is it an academic project?

I answered it by going back to the fundamental question: how do we create systemic change. Is it a representation issue, where we need to encourage women and girls to go in to STEM, or do we need STEM itself to change so the fields are fit for women? Whose issue is it exactly? Is discrimination towards women a ‘women’s issue’ or does the legwork rightfully lie elsewhere? Who and what needs to change? These issues can feel so complex and colossal to tackle that they are simply overwhelming and exhausting for anyone interested in tackling them. 

These are also profound and difficult questions on what we can meaningfully do when we standing next to the giants of institutional bias and discrimination. These giants are scary, strong and even more difficult to fight is their cryptic and invisisablised forms, as Caroline Criado-Perez addresses in her bestselling book Invisible Women: Exploring Data Bias in a World Design for Men, which was the basis of her keynote at our Women in Data campaign launch on September 10th 2019. 

 

Reflections from activism

The biggest challenge I have found as a feminist activist is not getting people to engage with gender equality agendas in the first place, but engage in ways where the stories and lived experiences of gender discrimination are centred and listened to in the dialogue on social problems, and are given proper platforms to be expressed and believed.

My experience tells me that people who dismiss or undermine feminist agendas aren’t groups of people failing to engage with issues of gender inequality or recognise the potential of feminist movements, which is the simplistic diagnosis we often give. The fact they are reacting so strongly is often testament to the fact they recognise its strength and truth. 

Their shortfalls, I argue, often come in not listening to and trusting other people’s narratives of the world. In saying ‘women don’t experience sexual harassment in the workplace because I don’t see or experience it’ is the same as saying ‘I don’t believe what they are saying about the workplace’.

If we want to design and deliver successful frameworks of inclusive innovation in the City Region Deal and beyond, I argue that we must start from the place of awarding the same authority of the lived experiences that we give to men’s experiences of the world and workplace, to women.

 

Sociology & data science

Many of the inequalities women face in data science, STEM and workplaces more generally can be explained by ‘epistemological’ inequality. Epistemology means ‘knowledge-creation’ and it refers to the different levels of privilege we have to claim knowledge and truths (got to squeeze in a posh-sounding sociological term somewhere). The authority your voice possesses is shaped by sociological characteristics like your age, race, gender and so on. 

This means that what women say is considered less important. Sexist tropes of women lying about sexual violence is one of the most common examples you’ll find of women’s experiences having little value awarded to them, and many women have experience of being dismissed as a manager or teacher, or being spoken over in meetings. 

When this inequality of voice becomes institutionalised, it can be identified in the poor representation of women at senior management level, it is found in male domination in jobs involving political and cultural design, such as policy and technology, it is evidenced in the gender pay gap (your time, labour and health are less important, as well as your voice).

This denial of marginalised voices, as Criado-Perez discusses in relation to medicine trials and crash dummies being based on male bodies, has violent and even fatal consequences by benchmarking men as the norm. 

Some sociologists label this exclusion of voice and experience as a form of violence, called ‘epistemic violence’ by Indian feminist Gayatri Chakravorty Spivak. 

This is perhaps, where the importance of sociology comes in, for those of you who may wonder what the relevance is of a sociologist leading a project on data science. It is with sociological approaches that we can identify hidden biases and understand how inequalities in data and STEM relate to wider inequalities and social hierarchy. 

Professor Wright Mills defined sociology as a discipline that ‘makes the familiar strange’. It is with that critical distance that we can pause and deconstruct the mundane in the world around us, like hidden gender biases and discrimination in workplace practices, data sets and technologies. We can take things every day, decode them and understand how things that are taken as ‘objective’ are actually social processes.

The usefulness of this sociological framework is to understand the world better – but also hope for better. 

Sociology taught me to stay constantly curious. It tells me that if the rules and design of the social world were made-up and made-up by certain groups of people, it means that it is perfectly possible for the constructed to be deconstructed, reconstructed and other groups of people to join in the knowledge and culture-creating processes.

 

Sociological approaches to the Fourth Industrial Revolution

Women in Data is more important now than ever as technology and data became more intimately intertwined with our cultural and social worlds – technology and data are culture and culture is technology and data. If we exclude women’s voices from this, we are preserving the historical exclusion of women from cultural design that we have relegated to the past, but this is at risk of rearing its head again as we enter the fourth industrial revolution. 

This is why we must practice with the very basic principle of legitimising and pulling in other people’s narratives and experiences of the world as we scientifically and technologically innovate the world.

This is not just about opening the door for women for the sake of political correctness – it is ridiculously well-evidenced that incorporating women’s skills and experiences is essential for all forms of design innovation that is sustainable and successful. 

As awareness grows around the extent of sex, gender, neurological and other forms of diversity, and as we reshape the narratives around disability, we must also intersect these learnings with the fourth industrial revolution. It is with the integration of the social sciences and STEM that we can bring these conversations together.

Looking forward, I’m so excited and impatient to see how we can create better technologies, data sets and urban or workplace infrastructures that meaningfully include not just women, but capture the needs of people with disabilities or transgender, gender fluid and intersex people, acknolwedging them as truly legitimate ways of being in the world. We have a clear corporate, ethical and political responsibility to create design that recognises multiple ways of being in the world apart from being an able-bodied man – this is just one way of being in the world that has become over-generalised.

This vision is not only urgent and exciting, but it is one that contributes towards an inclusiveness which ultimately reduces violence, harm and suffering. That is truly, cutting-edge innovation.

 

Our campaign

In September 2019, we launched our Women in Data campaign, which involves batches of our interviews being released on a weekly basis. I encourage you to read, enjoy, reflect and share this eclectic mix of stories from women about their work, across a rich diversity of innovative roles working with data and technology. To those who took part: thank you for being so candid and for sharing your tales of home life, motherhood and work highs and lows.

Finally, to answer the question I posed earlier – the Women in Data project is, at the moment, a storytelling project. It tells the professional and personal observations, achievements, politics, concerns and hopes of women across the data innovation landscape.

If you at any point, despair about the laborious fight for change or about how small you feel next to the obstacles inhibiting change, and think ‘what can I do’, remember that we need women’s stories to be valued and legitimised, and this is something absolutely within your remit of choice and personal power.

Believe and listen to women and then, we can “Do Data Right”. 

@DataCapitalEd #WomeninData