Why Diversity is Necessary for Effective and Future-Orientated Data Management

Why Diversity is Necessary for Effective and Future-Orientated Data Management
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Relying on biased information undermines the effectiveness of both product development in the private sector and of elaboration and implementation of policies in the public sector. In business, specifically, and if big data is shaping the world, we first need to ask: Who is responsible for shaping this data? Data scientists, data analysts, and professionals working in technology and STEM jobs are crucial in making business decisions that influence nearly every industry. And companies — and governments — can no longer afford to make decisions that are biased. Biased decisions do not serve the public interest nor the need for competitiveness in a global borderless market. 

According to data from the International Telecommunications Union, the proportion of women using the internet globally amounts to 48 percent, compared to 55 percent of men. This means that the global internet use gender gap stands at 12.5 percent. Worst, and perhaps as one of the consequences of this tech access asynchronicity, is that most of the world’s data scientists — i.e., the people who collect, organize, analyze data, and make decisions — are white men.

In the U.S., for instance, a report found that only 18% of data science roles in 2019 were occupied by females, and 11% of data teams don’t have any women on them at all. Other data show this number at over 20%, while also presenting a pay gap of 10% on average. Additionally, only 33% of data researchers globally are women, and they are awarded less research funding than men, and are less likely to be promoted. This is not acceptable, particularly in a marketthat is growing rapidly and thus demands more and more data scientists. 

Taking on the greatest challenges currently facing the global community will mean harnessing all talent. And so will developing new services because consumer preferences are diverse.

Below, we point to some examples of initiatives supporting women working in data and encouraging more inclusive practices around data governance. As a CDO, you and your company should take a look and consider actively supporting them: 

Women in Data Science

The Women in Data Science (WiDS) initiative aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. WiDS started as a one-day technical conference at Stanford in November 2015, and has grown to thousands of women around the world who also serve as ambassadors to support women in data science. 

Women in Data

Women in Data is a movement and a force for change in the realm of data science and analytics. They provide a platform for female and gender diverse data professionals to share their technical knowledge and experiences, and to encourage more diverse representation in the industry.

Africa Women in Data Science Event

The “Africa Women in Data Science” event aims to increase African women’s participation in the 4th Industrial Revolution (4IR) to build a prosperous, resilient Africa of the future. The integral role of African women for the 4IR will be discussed and various opportunities will be showcased for young women hoping to get into the field of data science.

Women in Data

Women in Data aims to increase diversity in data careers. The organization seeks to provide a welcoming and empowering community to inspire change and thought leadership across the industry.

Data + Feminism Lab

The Data + Feminism Lab uses data and computational methods to work toward gender and racial equity, particularly as they relate to space and place.

Body & Data

Established in 2017, Body & Data works to enhance understanding and access to information on digital rights among women, queer people, and marginalized groups where they are able to exercise their rights in a safe and just digital space.

Data Feminist Network

The Data Feminist Network is a community of individuals who are passionate about leveraging data for gender equality, and for those who are keen to learn more. Their aim is to work together to bridge the gap between data and intersectional feminism.

The Datasphere Initiative is mapping organizations working on data and actively shaping the data governance ecosystem. The above are just a few examples of the types of initiatives we are mapping to raise awareness and share knowledge of the diverse activities taking shape. 

If you have interesting examples of organizations working on data, please share with us at info@thedatasphere.org

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