EDUCATE is committed to ensuring Black lives matter and supports #ScholarStrike, https://www.scholarstrike.com.
Research on teaching and learning with technology has long recognized that technology is not neutral. In this moment of reckoning with racial inequity, we must name how technologies are continuing to perpetuate anti-Blackness. Just a few ways anti-Blackness continues to be perpetuated in technology:
- Racialized algorithms that affect housing, health care, credit, prison sentencing, and even more (Noble, 2018; O’Neil, 2016)
- Unregulated, controversial facial recognition software used for policing (https://www.perpetuallineup.org/)
- Defaulting to white supremacy and whiteness-as-normal in the ubiquitous design of technologies such as soap dispensers not recognizing Black hands, emojis with whiteness as default, or “shirley cards” representing whiteness as the norm in photography (https://www.mic.com/articles/124899/the-reason-this-racist-soap-dispenser-doesn-t-work-on-black-skin; https://www.nytimes.com/2019/04/25/lens/sarah-lewis-racial-bias-photography.html)
Designers and users of technologies for learning we need to do better. We need to ask ourselves how have we implicitly and explicitly reproduced anti-Blackness? In what ways, if at all, have we invited diversity into our designs? What assumptions do we carry forward with our designs? Reflection alone is not enough.
Further Reading:
White Supremacy and Artificial Intelligence by Ruha Benjamin: https://www.yesmagazine.org/social-justice/2019/08/29/technology-racism-artificial-intelligence-white-supremacy/
Books:
Race After Technology: Abolitionist Tools for the New Jim Code by Ruha Benjamin
Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble
Dark Matters: On the Surveillance of Blackness by Simone Browne