Getting into tech
If you are based in the UK, the following organisations offer free or cheap coding classes to women. Outside of the UK, and particularly within the United States, the list is much longer. Check out this blog post for an introduction to some of the available programmes, or read about free online learn-to-code resources here. Also, stay tuned to events run by Women in Tech networks such as AnitaB.org, Black Women in Computing, Code Like a Girl, DevelopHer, Lesbians Who Tech, ResearcHers Code, and Women in Tech UK.
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A coding school for women and non-binary people based in London. |
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A global non-profit initiative that facilitates the growth of a diverse tech community by running regular programming workshops. |
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An organisation delivering free and paid for in-person coding courses for women, as well as for companies across the UK and Ireland. |
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An international non-profit organisation working to close the gender gap in technology by teaching girls computer science. |
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Free tech training courses for women, run by Sky. |
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An organisation that trains women in key technology areas to allow them to enter a new career path and gain confidence regarding returning to employment or setting up their own businesses. |
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A programme that takes 100 women from the Midlands and North of England, particularly from underrepresented communities, with degrees or experience in any subject area, retrains them in technology and then gives them the opportunity to interview with a company for an internship/apprenticeship/job. |
Building your data science or AI career
Within data science and AI, a number of professional networks exist to help women and other under-represented groups build and advance their careers. A selection of such organisations is listed below, and it may be possible to find further local events near you through the website Meetup.
There are many free online resources for improving your data science skills, a selection of which are listed here, and you can keep your skills up-to-date by following online platforms such as Towards Data Science and KDnuggets. To gain data science experience, you can participate in online challenges through sites such as Kaggle and DrivenData, or volunteer your skills to non-profit organisations such as DataKind, Data for Democracy, and Data for a Cause.
AI4All and AI for Good offer summer programs and mentorship for underrepresented groups to get into AI, and Data Science for Social Good programs (DSSG) provide a route into the field for current or recent students with technical backgrounds.
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A place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence. |
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A global community-driven initiative to increase female representation and participation in AI, bringing empowerment, knowledge and active collaboration via education, research, events, and blogging. |
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A forum to strengthen the diversity of the field of big data, with global chapters. |
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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. |
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A technical workshop for women to present their research in machine learning. |
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An organisation whose aim is to support and promote women and gender minorities who are practicing, studying or are interested in the fields of machine learning and data science, with global chapters. |
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A global ‘think tank’ for women in AI that aims to address the bias that can occur within algorithms due to a lack of diversity and inclusivity within the field of artificial intelligence. |
Creating equitable AI
One of the motivations for increasing the proportion of women in data science and AI is to ensure that we have a voice in the creation of AI services, and to help mitigate gender bias exhibited by AI. The following organisations offer research and guidance about building fair, accountable, transparent, and ethical AI.
The Turing's full guide on AI ethics and safety can be downloaded here. You can read an overview of approaches to algorithmic de-biasing here, and find IBM's open source AI fairness toolkit here. However, we would like to emphasise that ensuring equitable AI involves more than just the technical de-biasing of algorithms; questions of who is building AI systems, how society and the environment is affected by their use, and whether these systems should be developed at all, are important to ask before and during the AI design process. A directory of women in AI ethics is available here.
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An independent research and deliberative body with a mission to ensure data and AI work for people and society. |
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An interdisciplinary research centre at New York University dedicated to understanding the social implications of artificial intelligence. |
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A non-profit research and advocacy organisation that aims to evaluate and shed light on algorithmic decision making processes that have a social relevance. |
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A collective that aims to highlight algorithmic bias, provide space for people to voice concerns and experience with coded bias, and develop practices for accountability. |
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A Harvard-based research centre whose mission is to explore and understand cyberspace; to study its development, dynamics, norms, and standards; and to assess the need or lack thereof for laws and sanctions. |
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A centre tasked by the Government to connect policymakers, industry, civil society, and the public to develop the right governance regime for data-driven technologies. |
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An interdisciplinary community of researchers the the goal of working together to ensure that "we humans make the best of the opportunities of artificial intelligence as it develops over coming decades". |
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An independent non-profit research institute that advances public understanding of the social implications of data-centric technologies and automation. |
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A research lab the examines the intricate relationship between datafication and social justice, highlighting the politics and impacts of data-driven processes and big data. |
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An organisation that champions responsible technology for a fairer future. |
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An initiative focused on correcting and preventing unconscious bias in the development of artificial intelligence, and ensuring equal representation in the creation of AI. |
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A growing community of researchers and practitioners concerned with fairness, accountability, and transparency in machine learning. |
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A partnership of for-profit and non-profit organisations that was established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society. |
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A Stanford-based research institute that works to advance AI research, education, policy, and practice to improve the human condition. |
Keep reading
To find out more about topics concerning Women in Data Science and AI, visit our Mendeley group covering the history of women in tech, the current experiences of women in data science, and emerging issues of gender bias in artificial intelligence.
If you know of a relevant resource that is not listed here, please get in touch via our contact form.