Machine Learnings
We are facilitating casual 1:1 conversations between readers of Machine Learnings! Would you like to meet someone from the community? Click this link to arrange a 30 minute Zoom call between yourself and a match.

Awesome, not awesome.

"Researchers at MIT and elsewhere launched a research project to identify and tackle machine learning usability challenges in child welfare screening. In collaboration with a child welfare department in Colorado, the researchers studied how call screeners assess cases, with and without the help of machine learning predictions. Based on feedback from the call screeners, they designed a visual analytics tool that uses bar graphs to show how specific factors of a case contribute to the predicted risk that a child will be removed from their home within two years.

The researchers found that screeners are more interested in seeing how each factor, like the child’s age, influences a prediction, rather than understanding the computational basis of how the model works. Their results also show that even a simple model can cause confusion if its features are not described with straightforward language.

These findings could be applied to other high-risk fields where humans use machine learning models to help them make decisions, but lack data science experience, says senior author Kalyan Veeramachaneni, principal research scientist in the Laboratory for Information and Decision Systems (LIDS) and senior author of the paper." - Adam Zewe, Writer Learn More from MIT News >

#Not Awesome
"A scientist who wrote a leading textbook on artificial intelligence has said experts are “spooked” by their own success in the field, comparing the advance of AI to the development of the atom bomb.

Prof Stuart Russell, the founder of the Center for Human-Compatible Artificial Intelligence at the University of California, Berkeley, said most experts believed that machines more intelligent than humans would be developed this century, and he called for international treaties to regulate the development of the technology." - Nicola Davis, Science Correspondent Learn More from The Guardian >

What we're reading.

1/ Facebook changes corporate name to "Meta" as it continues to expand from a social network into a "metaverse", a world of endless interconnected virtual communities. Learn More from Axios >

2/ Walmart has partnered with Facebook to launch an augmented reality experience that will read customer's emotions via facial recognition as they are shown gift ideas. They then plan to direct users to the products that seemed to "spark joy". Learn More from Winsight Grocery Business >

3/ A recent survey of 7,000 patients indicates that over 70% are "very" or "somewhat" concerned about data privacy in relation to facial recognition. Learn More from HealthITSecurity >

4/ An automated robot is being piloted at restaurants like White Castle and Buffalo Wild Wings to help counter the labor shortage and provide faster food to customers. Learn More from CNBC >

5/ McDonald's and IBM have partnered to develop artificial intelligence that will help automate drive thru lanes. Learn More from CNBC >

6/ Delta Air Lines is set to test facial recognition software at Atlanta and Detroit airports this holiday season in an attempt to eliminate the need for boarding passes. Learn More from Big News Network >

7/ [Opinion Piece] “A.I. is imprecise, which means that it can be unreliable as a partner,” Eric Schmidt, former CEO of Google says. Learn More from The New York Times >

If you’re interested in following along in realtime, seeing the articles we read throughout the week, and chatting about the implications of artificial intelligence and machine learning…join our slack community! (we'll be chatting in the #automation channel. Come say hi!) 🤖
31/10/21 View this email in your browser
Copyright © 2021 Machine Learnings, All rights reserved.

Done learning about AI?
Opt out of emails