Start with schools to reduce bias in algorithms and open doors for minorities in tech

May 29, 2018 Sam DeBrule

Source

Awesome, not awesome.

#Awesome
“…Using the tagged threads, [researchers] then trained a [machine-learning] system to predict from the first comment if a [online] conversation was going to go south…An AI that predicts a conversation’s trajectory could help companies (cough, Twitter, cough) build tools that stop a fight or salvage online dialogue.” — Jackie Snow, Editor Learn More from MIT Technology Review >

#Not Awesome
“The biggest danger AI poses today… [is] the potential to scale bias and racism to the size of the internet. The latest example of this is… a new algorithm which promises to accurately look at images of people and determine their ethnic background… Ethnicity recognition is a step even further past the ACLU’s line in the sand. Making it far easier for anyone with access to surveillance cameras, whether it be police or private entities like airlines or sporting arenas, to flag people based on ethnicity, would encourage overt racial profiling without even the guise of assisting police investigations. — Dave Gershgorn, Reporter Learn More from Quartz >

What we’re reading.

1/ Introducing basic coding curriculum into all junior high and high schools may be the best way to offer more seats at the table for women and minorities at tech companies — and to reduce bias in algorithms. Learn More from The Atlantic >

2/ People living in low-income countries are most vulnerable to the downsides of AI, because the algorithms built there may be built on data that “compound[s] histories of ethnic conflict or systemic exclusion.” Learn More from TechCrunch >

3/ A pioneer of machine learning predicts that we’ll know AI is capable of committing evil when “it is obvious to us that there are software components that the robot ignores, consistently ignores. When it appears that the robot follows the advice of some software components and not others…” Learn More from The Atlantic >

4/ In a bit of simultaneously impressive and terrifying news, Chinese authorities use an AI-powered facial recognition system to arrest a man accused of stealing potatoes. Learn More from NPR >

5/ On the bright side, the introduction of autonomous vehicles in will lead to a spike in the number of parks and other natural features in our cities. Learn More from WIRED >

6/ News of Apple’s intentions to build a self-driving appear in the news every few months but it’s unclear if real progress is being made. The latest headlines point to an autonomous shuttle that they’re woking on alongside Volkswagen. Learn More from The New York Times >

7/ We’re already starting to see examples of governments using machine learning algorithms to censor valuable content on the internet — and we should only assume this trend will continue. Learn More from The Financial Times >

Links from the community.

“The AI In Your Autonomous Car” submitted by Dakota McKenzie (Dakota). Learn More from TechCrunch >

“Future of Work #4 — Enterprise Knowledge Management 2.0 + AI-Powered Search & Discovery = Team Intelligence” submitted by Jessica Lin (Jessica Lin). Learn More from Medium >

“Uber’s Self-Driving Car Didn’t Malfunction, It Was Just Bad” submitted by Avi Eisenberger (Avi Eisenberger). Learn More from The Atlantic >


Start with schools to reduce bias in algorithms and open doors for minorities in tech was originally published in Machine Learnings on Medium, where people are continuing the conversation by highlighting and responding to this story.

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