(Graphic: John McCann/M&G)
Being involved in the inaugural Women in Data Science (WiDS) Africa conference struck me as an opportunity to try to give credence to literary theorist and feminist critic Gayatri Chakravorty Spivak’s famous essay on colonialism and allow the “subaltern to speak”.
As a feminist ally, I passed the mic to some phenomenal women who are generally underpaid, underrepresented and unseen in the world of data science which, especially in Africa, is male-dominated.
Data has been referred to as the new oil because it is a valuable asset that has the potential to transform the way society operates. Data science is the interdisciplinary, complex employment of big data, artificial intelligence and advanced analytics and is a fast-growing field of science. It is increasingly being used to inform policy and decision-making in both government and the private sectors, but representation in the field remains unequal.
According to recent statistics, women make up a measly 15% of all data scientists globally and the World Economic Forum 2020 report found that only 26% of professionals employed in data and artificial intelligence in Africa are women.
Equal representation is crucial, however, because data is used to harness important information, often about people. Data has the potential to perpetuate harmful and oppressive biases; machines and robots are susceptible to learning and regurgitating human weaknesses and whims. As such, diversity, in terms of race, class, gender, sexuality, ability and other identity markers, is critical to the fair advancement of the field.
The tumultuous history that the world, and Africa in particular, has with science will only be changed from within. Inequality, expressed as racism, sexism and more has invariably been endorsed and promoted by scientists. For example, the myth that some racial groups are superior has propped up colonialism, apartheid, eugenics and genocide.
Science is often touted as an apolitical and ahistorical search for “objective knowledge” and understanding of our world. It follows a systematic methodology that is based on evidence. Even though organisations such as the Science Council provide quality assurance for scientists all over the world based on criteria such as objectivity and critical analysis, other scientists such as Keith Punch have argued that human beings are incapable of being objective — which means that science performed by any human is subjective.
And, regardless of the claims by many who want to continue to pretend otherwise, science is political, because it is in constant conversation with power in all spheres of society.
Furthermore, science is an organised knowledge community which has authority to affect lives whether positively or otherwise. Therefore this “neutral” science is, in Gramscian terms, propagated through hegemonic power and is normalised as common sense to uphold the status quo.
It is thus urgent that more women of colour cement themselves in this realm. The urgency with which data science needs transformation was echoed by women speakers and data scientists at the WiDS Africa conference, especially held on International Women’s Day, 8 March.
International Women’s Day commemorates the scientific, cultural, political, historical and socioeconomic achievements of women. It is also a focal point in the women’s rights movement, bringing crucial attention to issues such as gender inequality, encapsulated in the pay gap and the dearth of women in fields such as data science — issues that were highlighted at the much-referenced Beijing World Conference on Women in 1995.
But, 26 years later, not much has changed and researchers report that it could still take 163 years before gender equality is achieved.
WiDS Africa is part of the annual WiDS Worldwide conference organised by Stanford University, where about 150 events were hosted, featuring outstanding women doing outstanding work and which also aim to “encourage secondary school students to consider careers in data science, artificial intelligence, and related fields”.
I was tasked by Nicola Mulder, principal investigator at the Pan African Bioinformatics Network for H3Africa, to bring mainly women collaborators together for the local event.
According to the 2021 Women in Data Science report, women face myriad blockages in joining science, technology, engineering and mathematics fields, which include the absence of role models and mentors to encourage them to take these subjects and careers in these fields, as well as limited scholarships and finances to continue professional development.
In the WiDs Africa panel discussion on how the Covid-19 pandemic has affected their lives, Verena Ras, Chenai Chair, Rahab Wangari, Ruthbetha Kateule and Dominique Anderson echoed these views.
University of Cape Town vice-chancellor Mamokgethi Phakeng’s keynote speech addressed the relevance of women in data science.
I implore other men and feminist allies to give up their seat at the table, to stop being gatekeepers and actively create opportunities for women to join the science fraternity. We should all be feminists who dismantle patriarchal science through affirmative action, which, according to Ugandan author and lawyer Sylvia Tamale, “is a means of assuring substantive representation of a special group”, in this case women, and particularly black women.
We need to interrogate and highlight the limited representation of African women in data science (and other scientific fields) and resolve it soon before the rest of the world leaves us behind. Women’s views, nuanced experiences and knowledge are important additions to science to enrich and advance all humanity.