How white engineers built racist code – and why it's dangerous for black people | Technology | The Guardian


13 bookmarks. First posted by dcolanduno december 2017.


Experts such as Joy Buolamwini, a researcher at the MIT Media Lab, think that facial recognition software has problems recognizing black faces because its algorithms are usually written by white engineers who dominate the technology sector. These engineers build on pre-existing code libraries, typically written by other white engineers.

As the coder constructs the algorithms, they focus on facial features that may be more visible in one race, but not another. These considerations can stem from previous research on facial recognition techniques and practices, which may have its own biases, or the engineer’s own experiences and understanding. The code that results is geared to focus on white faces, and mostly tested on white subjects.
by:AliBreland  from:TheGuardian  JoyBuolamwini  FacialRecognition  biometrics  racism  technology  surveillance 
december 2017 by owenblacker
RT : I wrote about the implicit racial biases baked into code and how that hurts communities of color:
from twitter
december 2017 by nureineide
As facial recognition tools plays a bigger role in fighting crime, inbuilt racial biases raise troubling questions about the systems that create them
algorithms  racism  ethics  surveillance  law 
december 2017 by SimonHurtz
As facial recognition tools play a bigger role in fighting crime, inbuilt racial biases raise troubling questions about the systems that create them 04.00 EST Last modified on Monday 4 December 2017 11.01 EST “You good?” a man asked two narcotics detectives late in the summer of 2015. via Pocket
IFTTT  Pocket 
december 2017 by kubia
How white engineers built racist code – and why it's dangerous for black people
from twitter_favs
december 2017 by skome
As facial recognition tools plays a bigger role in fighting crime, inbuilt racial biases raise troubling questions about the systems that create them
digitalart  digital  facerecognition  artscience  postMA 
december 2017 by SarahHolyfield