Who else is doing this work?

Organizations

AI Now Institute

The AI Now Institute, housed within New York University, is an interdisciplinary research center analyzing the social implications of artificial intelligence. They focus on four core domains: rights and liberties, labor and automation, bias and inclusion, and safety and critical infrastructure. They currently host workshops and their website includes their various publications.

AI Now Institute. (n.d.). https://ainowinstitute.org/

Algorithmic Justice League

The Algorithmic Justice League is a collective that aims to: highlight algorithmic bias, provide space for people to voice concerns and experiences with coded bias, and develop practices for accountability during the design, development, and deployment of coded systems.

Algorithmic Justice League. (n.d.). https://www.ajlunited.org/

Data & Society, the Health and Data Initiative

The Health and Data research initiative examines the space for positivity and the risks of health-related technologies and data practices. Specifically, the Initiative claims that “through empirical investigation [they] seek to understand the evolving and complex interdependence of our health and technology practices, including precision medicine, algorithmic decision-making in clinical care, bias in genome databases, ethical collection of data, healthy interactions with tech platforms and mobile devices, and the spread of health misinformation online.” Their various research tracks are included on their website for further exploration.

Waller, A. (n.d.). Health and Data Initiative. https://datasociety.net/research/health-and-data

Data Feminism

Data Feminism houses a community review site for folks to easily access their work and contribute their knowledge to the project. The Project uses experienced based testimonies as well as contributions from scholars and students from an array of fields. Currently, the Data Feminism community review site has eight chapters, an introduction, conclusion, and various other readings that discuss the impacts of data bias. 

D’Ignazio, C., & Klein, L. (n.d.). Data Feminism · MIT Press Open. https://bookbook.pubpub.org/data-feminism

Data for Black Lives

Yeshimabeit Milner, our keynote speaker for the 2019 Bias in Big Data event is the co-founder of Data for Black Lives. They describe themselves “as a group of activists, organizers, and mathematicians committed to the mission of using data science to create concrete and measurable change in the lives of Black people. Data for Black Lives seeks to mobilize scientists around racial justice issues.” 

About Data for Black Lives. (n.d.). http://d4bl.org/about.html

Fairness, Accountability, and Transparency in Machine Learning

FAT/ML is an organization that has hosted various events in the past five years discussing the impacts and practices surrounding bias in big data. Their website includes recommended principles and best practices, the schedule of their planned events, and information about the current projects their organizers are working on to push fairness, accountability, and transparency in data science and machine learning.

https://www.fatml.org/

The Fenway Institute – LGBT Population Health Program

The Fenway Institute of Fenway Health in Boston houses the LGBT Population Health Program. The Program works to develop and support collaborative research and education programs to understand and improve the health of sexual and gender minorities. The Program includes findings and more details on the work they have been doing on their website. 

LGBT Population Health Program. (n.d.). https://fenwayhealth.org/the-fenway-institute/education/the-center-for-population-research-in-lgbt-health/

National LGBTQ Task Force

“We’re building a future where everyone is free to be themselves in every aspect of their lives. Today, despite all the progress we’ve made to end discrimination, millions of LGBTQ people face barriers in every aspect of their lives: in housing, employment, healthcare, retirement, and basic human rights. These barriers must go. That’s why the Task Force is training and mobilizing millions of activists across our nation to deliver a world where you can be you.”

https://www.thetaskforce.org/about/mission-history.html

The Williams Institute – Census and LGBT Demographic Studies

The Williams Institute of the UCLA School of Law houses a plethora of studies on their website pertaining to a variety of topics within the LGBT community. Their research discusses LGBT health, data collection, legislation impacts, incarceration rates, hunger, and socioeconomic wellbeing among the LGBT community. 

Census & LGBT Demographic Studies Archives. (n.d.). https://williamsinstitute.law.ucla.edu/category/research/census-lgbt-demographics-studies/

People

Sasha Costanza-Chock, (they/them or she/her)

Sasha Costanza-Chock is a scholar, activist, and media-maker, and currently Associate Professor of Civic Media at MIT. They are a Faculty Associate at the Berkman-Klein Center for Internet & Society at Harvard University, Faculty Affiliate with the MIT Open Documentary Lab and the MIT Center for Civic Media, and creator of the MIT Codesign Studio. Their work focuses on social movements, transformative media organizing, and design justice. Sasha’s first book, Out of the Shadows, Into the Streets: Transmedia Organizing and the Immigrant Rights Movement was published by the MIT Press in 2014. They are a board member of Allied Media Projects (AMP); AMP convenes the annual Allied Media Conference and cultivates media strategies for a more just, creative and collaborative world.

Costanza-Schock, S. (n.d.). Sasha Costanza-Chock. http://schock.cc/category/writing/

Virginia Eubanks, PhD., (she/her)

Virginia Eubanks is an Associate Professor of Political Science at the University at Albany, SUNY, and author of Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor.
Eubanks investigates the impact of data mining, predictive risk models and their place in America’s justice system, and the influence algorithms on policy. Her book provides detailed context for many of the important questions that impede the idea of unbiased data.

Eubanks, V. (n.d). Virginia Eubanks. https://virginia-eubanks.com/

Momin Malik, M.S., Ph.D., (he/him)

Scholar Momin Malik describes his work as, “understanding statistics, machine learning, and data science from critical and constructivist perspectives, on ethical and policy implications of predictive modeling, and on understanding and communicating foundational problems in statistical models of social networks.” Malik’s website houses his current research projects, previous work, reports, and presentations, the majority of which include accessible links for further exploration.

Malik, M. M. (n.d.). Momin M. Malik: Research works. https://www.mominmalik.com/

Sofiya Umoja Noble, PhD., (she/her)

Sofiya Umoja Noble is an Associate Professor at UCLA and author of the book Algorithms of Oppression: How Search Engines Reinforce Racism, which was developed from six years of academic research on Google search algorithms. Noble articulates the dangers of portraying algorithms as unbiased when they can mirror the racism, bias, and values of the people who create them.

Noble, S.U. (n.d.). Sofiya Umoja Noble. https://safiyaunoble.com/

Cathy O’Neil, PhD., (she/her)

Cathy O’Neil is mathematician, data scientist, and author of several books on data science, including Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. In Weapons of Math Destruction, O’Neil discusses the era of algorithms and how pertinent they are in our everyday lives. She illustrates the unregulated nature of these algorithmic models and how they have further perpetuated discrimination. She includes a call to action to both modelers, to address their algorithmic faults, and to policymakers, to regulate these developmental practices. O’Neil also has a TED talk calling for “The Era of Blind Faith in Big Data Must End” that is worth watching, https://www.ted.com/talks/cathy_o_neil_the_era_of_blind_faith_in_big_data_must_end.

O’Neil, C. (n.d.) Cathy O’Neil. https://mathbabe.org/