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Coded Bias - What you need to know about the new Netflix documentary

It's timely that a week after the publication of the Sewell report comes Coded Bias a new Netflix documentary directed by Shalini Kantayya


If one is impossible to swallow, divisive and backward looking the other takes us into the heart of the future, with a deep dive on big data and facial recognition software, and all its current bias.


Weapons of Math Destruction - Cathy O'Neil

So what is Coded Bias and what do you need to know about it?


"This documentary investigates the bias in algorithms after M.I.T. Media Lab researcher Joy Buolamwini uncovered flaws in facial recognition technology" - Coded Bias, Netflix


The Aspire Mirror


The documentary starts with MIT Media Lab researcher Joy Buolamwini talking about her project, the aspire mirror.


She wanted to create a holographic type programme that would show different aspirational faces to the wearer. She mentions Michelle Obama and Serena Williams.


Only her mirror would not work with black faces. The computer recognition software she was using would only work when she put on a white mask.

The Aspire Mirror - Joy Buolamwini

AI is flawed because of who created it


Meredith Broussard - Data journalism professor at the Arthur L. Carter Journalism Institute at New York University then takes up the story.


She explains that AI started in 1956 at Dartmouth Math Department


The faculty at that time was 100% white. This group of white male academics created the systems that exist to this day, that are now responsible for the widespread facial recognition technology.


People embed unconscious biases into technology.


If we are using data sets to train machines that are largely using white faces then we are educating biases into our machines.


Author Cathy O'Neil who published latest book ' Weapons of Math Destruction' talks about the need to end blind faith in data pointing out:


"Who owns the code? The people who own the code hold the power"



Big Brother Watch


Silkie Carlo director of Big Brother Watch since 2018 is shown in Coded Bias handing out flyers at Leicester Square tube station.


She is trying to warn people about the police surveillance cameras in operation that day in the area.


Big Brother Watch is a UK civil liberties campaign group fighting for a free future. We’re determined to reclaim our privacy and defend freedoms at this time of enormous technological change. And we fight to win. - Bigbrotherwatch.org.uk

During the course of the documentary, Silkie speaks to a man who has tried to obscure his face to avoid being photographed by the survelliance operation, and been given an on the spot fine by the police.


Big Brother Watch disagree so strongly with the use of facial recognition for biometric profiling because of the way these systems are established.


These cameras get it wrong, often. The ability for machines taught to recognise white faces by the people who programmed it, means this is yet another way for anyone non white to be picked up and targeted.


Even the policeman included in the documentary comments to say that he knows the match system is often wrong.


As Silkie Carlo puts it


"We have Chinese style surveillance for the first time in London"

Summary


Coded Bias demonstrates a clear need to hold technology companies to account. From the way that systems used to facially recognise us are programmed, to their future creation.


Ask yourself whether you would have signed up for a Facebook account back in 2006-2008 if you'd known what it would become? We are making decisions without all of the data required for real understanding.


We need to ask more questions of the systems that we already have in place.


Do we want to live in a country that screens its citizens to detain until such time as they prove they are innocent?


This film should be a red flag for anyone who cares about equality for all.




About Me

Shona Chambers is a Marketing Consultant based in SE London.

Specialising in helping Small Business Owners and Freelancers with their Marketing.

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