Screening
Coded Bias – Screening And Q&a
8 Mar 2021
Regular hours
- Mon, 08 Mar
- 15:00 – 17:45
Timezone: Europe/London
Online
- Language: English
- Join the event
Virtual Screening of Coded Bias, followed by Q&A with the film’s director Shalini Kantayya
About
NEoN is excited to present its first event to launch the start of this years programme and theme for 2021 - Under the theme, ‘Wired Women’ NEoN will invite female and nonbinary artists from across the world to investigate how we can bridge the digital gender divide in today’s world, how to better connect our communities and highlight the contribution of female and non-binary artists and technologists in shaping our digital and technology-driven lives. For International Women’s Day NEoN is presenting Coded Bias, which exposes how algorithms encode and propagate bias and how women are fighting to create a world with more ethical and inclusive technology.
Schedule for March 8, 2021
Watch the film from 3 pm – 4.30 pm GMT
Break 15 mins
Q&A with Filmmaker Shalini Kantayy at 4:45 pm GMT
Coded Bias Coded Bias explores the fallout of MIT Media Lab researcher Joy Buolamwini´s startling discovery that facial recognition does not see dark-skinned faces and women accurately and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all. Modern society sits at the intersection of two crucial questions: What does it mean when artificial intelligence (AI) increasingly governs our liberties? And what are the consequences for the people AI is biased against? When MIT Media Lab researcher Joy Buolamwini discovers the most facial-recognition software does not accurately identify darker-skinned faces and the faces of women, she delves into an investigation of widespread bias in algorithms. As it turns out, artificial intelligence is not neutral, and women are leading the charge to ensure our civil rights are protected.
SHALINI KANTAYYA - “What was terrifying to me while making @CodedBias was that A.I. not vetted for accuracy or bias are already being deployed at a massive scale to make important decisions about who gets hired, who gets health care, who gets into college or how long a prison sentence someone serves. That shook me out of my seat.”
