Really, really awesome.
“Take a work environment that’s hostile to women. Suppose that you define success as the fact that someone holds a job for two to three years and gets a promotion. Then your predictor — based on the historical data — will accurately predict that it’s not a good idea to hire women. What’s interesting here is that we’re not talking about historical hiring decisions. Even if the hiring decisions were totally unbiased, the reality — the real discrimination in the hostile environment — persists. It’s deeper, more structural, more ingrained and harder to overcome.
I believe the great use for machine learning and AI will be in conjunction with really knowledgeable people who know history and sociology and psychology to figure out who should be treated similarly to whom.” — Cynthia Dwork, Harvard Computer Scientist Learn More on MIT Technology Review >
What we’re reading.
1/ There are reportedly only 10,000 people in the world who possess the skills necessary to do AI research, and large companies are shelling out startling sums of cash to attract them. Learn More on The New York Times >
2/ Mass automation of jobs is one of the largest challenges facing humanity — if we’re incapable of measured long-term thinking, our future will be an awful one. Learn More on Mother Jones >
3/ If AI systems use past data to determine legal rulings, credit checks, and loan approvals, we must put checks in place to avoid “repeating[ing] the injustices of the past.” Learn More on Slate >
4/ The world’s largest tech companies lay out principles for developing ethical AI systems — and show their commitment to mitigating bias in algorithms. Learn More on Axios >
5/ If our capacity to build massively powerful technologies (like AI and nuclear weapons) outpaces our wisdom for managing it, we’re in serious trouble. Learn More on Motherboard >
6/ Companies and government agencies alike are under pressure to explain the input information and subsequent decisions of their AI algorithms. Learn More on Slate >
7/ In a future that’s not very far off, every digital experience could be controlled by our neurons. Learn More on The Atlantic >
What we’re building.
If you’ve followed along with Machine Learnings, you know that AI algorithms are pervasive, influencing everything from the movie recommendations you see on Netflix to defendants sentenced to jail in some courtrooms.
These algorithms aren’t built in vacuums. They’re built by technologists and honed with behavioral data captured by the products and services we’ve come to love and use habitually.
The team behind Machine Learnings and Journal is building a new blog and newsletter — called Noteworthy — to help you better understand the people and ideas that shape the products you use everyday.
If you’re interested in seeing what we have cooking, check out the blog and sign up to get the weekly Noteworthy newsletter.
If you enjoy Machine Learnings, we promise you’ll enjoy Noteworthy too :)
Where we’re going.
Highlight from “AI and Patient Centric Healthcare”
“Moving to a more proactive model of healthcare, which focuses on prevention rather than treatment, will be key to improving outcomes and reducing the cost of chronic disease.
To get to this point presents a challenge for the existing healthcare system, particularly given the shortage of health workers.
The strains on the healthcare system could be eased by consumers taking more ownership of their health but, currently, few are capable of managing their health without insight & support from medical professionals and the cost that incurs.
By bringing that insight and support to users’ smartphones, AI has the potential to both significantly improve and streamline the management of chronic disease.”
Links from the community.
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