WiR redlist index: AI Ethics


Welcome to WikiProject Women in Red (WiR). Our objective is to turn red links into blue ones. Our scope is women's biographies, women's works, and women's issues, broadly construed.

This list of red links is intended to serve as a basis for creating new articles on the English Wikipedia. Please note however that the red links on this list may well not be suitable as the basis for an article. All new articles must satisfy Wikipedia's notability criteria with reliable independent sources.

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This is a list under development of missing articles on women who are (or have been) notable for their contribution to AI Ethics in academics, business, economics, politics, research, government or the social sector.

See also Requested articles for computer-related people

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This page is a list of women in AI ethics who either have no Wikipedia page, or could benefit from better coverage. Some are redlinks due to lack of third-party, independent coverage in media, books, or journals, in which case we could begin to collect those sources in parenthesis beside their name.

If you want to write an article on a living person (which seems very likely), please reference Wikipedia:Biographies of living persons for the appropriate guidance. If that is confusing, please see this guide from the Wiki Education Foundation. For academics, please reference Wikipedia:Notability (academics) to see if the person qualifies for entry.

Please note that even if a person doesn't meet the qualifications for notability right now, they might someday! You can still add their name to the list below and begin compiling resources. If there are any sources, include a link. When there are three, they may be ready for a Wikipedia article.

AI Ethics

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Ethics is an ideal. Today, it is, for the most part, theory especially as it relates to AI’s relentless path to become a pervasive technology. This is not something we can strap on the end like a bandaid and expect it to address and readily fix our existing systems. The role of ethics in technology will be a significant one as it will challenge current systems that have prevailed in perpetuating harms, however unintended, for many years. This will continue unless we address these and develop solutions to fix them before AI gets a hold of them. This also means that in the nascent environment of AI, brimming with ideas, experiments and optimism, we need to be cautious of what we are building, especially when the foundations for inequality have already been baked, accepted and implemented. We should question our economics, the motivations of Big Tech, government and leaders in our organization. Mindsets need shifting as well as infrastructure, policy and regulation. But it has to be a path that scales and gains significant adoption otherwise humanity will lose.

Technology is progressing at a rapid pace and it’s infiltrating every aspect of our lives, our personal space, our work and how we do business. What’s apparent is the speed of progress that creates consequences and implications that conflict with our social norms. Policy and legislation continue to lag. While increased data usage will set the groundwork for vastly giving us the things we want when we want them, the same technologies have the ability to cause greater individual and societal harm. The issues that need to be addressed today - hatred, racism, free speech, bias, fairness, data privacy, surveillance - require inclusive culture within organizations that will progress with the increased use of DATA. The very issues companies have not faced before will be illuminated as time goes on. And the ethical consumer, more aware of the misuse of their data today will look to the law and society and trusted organizations to protect their freedoms and ensure their safety. The future of AI means embedding Ethics, Diversity and Inclusion in the heart of our organizations and our systems.

Women in AI Ethics Initiative

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Women in AI Ethics is a global initiative founded by Mia Dand, CEO, Lighthouse3 to connect talented women from different backgrounds working on AI Ethics worldwide with the mission to recognize, encourage, and empower brilliant women in the space of AI Ethics by their location and expertise[1]. Inspired by the 100 Women (BBC) initiative, with a list of missing notable women created by the Wikiproject Women in Red.[2], each year Women in AI Ethics project[3] is publishes the “100 Women in AI Ethics™” list (2020 list can be found here). 31% only of women from the current list have Wikipedia articles. The goal of WAIE is to increase the visibility of women in Wikipedia and create more pages on notable women working on AI ethics.

A Gender Bias on Wikipedia still exists, men write the biggest part of the Wikipedia content, where most of the biographies are also about men.[4]. In 2014 only 15.53% of English Wikipedia's women biographies. In May 2020 the number of biographies in English has reached 18.39%, still, a lot of works need to be done[5].

Biographies score

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Improved:
Aimee Van Wynsberghe. Julie Carpenter
Created:
Laurence Devillers, Lavina Ramkissoon, Ajung Moon,Anja Kaspersen, Fatmah Baothman, Aleksandra Mojsilovic, Deborah Raji, Abeba Birhane, Virginia Eubanks, Latifa Al-Abdulkarim, Kanta Dihal, Christina Colclough, Kay Firth-Butterfield, Margot Kaminski, Tess Posner

Who should be here?

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This is a collection of women who are working in AI ethics and/or policy. As noted above, each person should ideally have at least three sources from reliable, third-party coverage such as newspapers, journal articles, awards, etc.

Who are you?

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If you are interested in this project please leave your Wikipedia username below in the bullet list! If you are an experienced Wikipedia or new, leave your name below so we can offer support.

This initiative is currently headed by:

Past participants/volunteers:

References

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  1. ^ "100 Brilliant Women in AI Ethics for 2020". Lighthouse3.com.
  2. ^ [www.womeninred.org Women in Red WikiProject]
  3. ^ "Open directory of Women in AI Ethics™". Lighthouse3.
  4. ^ Eduardo Graells-Garrido, Mounia Lalmas, Filippo Menczer. ""First Women, Second Sex: Gender Bias in Wikipedia"" (PDF). arxiv.org.{{cite web}}: CS1 maint: multiple names: authors list (link)
  5. ^ Noor, Poppy. "Wikipedia Biases". Theguardian.com. The Guardian.