Awesome, not awesome.
“Motorola announced today that it will work with AI company Neurala to develop intelligent cameras for public safety users. The goal is to enable police officers to more efficiently search for objects or persons of interest, such as missing children and suspects… imagine if the parent showed the child’s photo to a nearby police officer on patrol. The officer’s body-worn camera sees the photo, the AI engine ‘learns’ what the child looks like and deploys an engine to the body-worn cameras of nearby officers, quickly creating a team searching for the child.” — Paul Steinberg, Chief Technology OfficerLearn More on Motorola Solutions >
“One of the big risks is that these machine learning algorithms can have implicit biases and they can be very hard to detect or correct…and it’s especially important because they don’t have the kind of explicit rules that earlier waves of technology had. It’s unlikely to have a rule that says, you know, don’t give loans to black people or whatever, but it may implicitly have its thumb on the scale in one way or the other if the training data were biased…. And you know, maybe nobody explicitly says that they were biased, but it sort of shows up in other subtle ways based on the, you know, the zip code that someone’s coming from or their last name or their first name…” — Erik Brynjolfsson, Professor Learn More on Harvard Business Review >
What we’re reading.
1/ We can’t say for sure which professions are most vulnerable to AI-enabled automation, but we do know one thing — managers who aren’t willing to experiment with AI-enabled technologies will be replaced by those who are. Learn More on Harvard Business Review >
2/ As the US cuts back on science spending, China lays out its plan to become the world leader in AI by 2030. Learn More on The New York Times >
3/ Elon Musk freaks out a bunch of politicians in Rhode Island last week when he spoke about AI’s potential ability to “shut down whole parts of our cities, the ability to create such damage by turning off the electricity, or making sure there’s no water…” Learn More on NPR >
4/ In an effort to position themselves as a place where serious machine learning work happens, Apple launches a blog to showcase the ML research and breakthroughs that come out of the company. Learn More on TechCrunch >
5/ Lyft opens a self-driving research facility in Silicon Valley, and doubles down on its bet to build the software that automakers use to power their autonomous vehicles. Learn More on The New York Times >
6/ By making way for tools of war like drones that possess bird-like agility and software that crafts fake videos of world leaders, AI might revolutionize warfare more than nuclear weapons did. Learn More on WIRED >
7/ The best way to prevent AI powered cyberattacks from wreaking major havoc is to create AI systems that identify and exploit the simple patterns they rely on. Learn More on MIT Technology Review >
Links from the community.
“The next wave of AI in the enterprise will not be sexy, but the impact will be massive” by Indranil (Indy) Guha. Learn More on Machine Learnings >
“Human-Centered Machine Learning” submitted by Avi Eisenberger. Learn More on Medium >
“The AI-First Business Model” submitted by Simon Hudson. Learn More on Medium >
“Glasswing Ventures Leads $ 8M Series A In Talla’s A.I. Driven Service Desk” submitted by Samiur Rahman. Learn More on GlobeNewswire >
“Artificial Intelligence Experts Respond to Elon Musk’s Dire Warning for U.S. Governors” submitted by Suneet Bhatt (@a_suneet). Learn More on Discover >
“How Intuit’s Customers Have Benefited From Machine Learning” submitted by Anna Kohnen. Learn More on Forbes >
“Please Prove You’re Not a Robot.” submitted by Jake Hart. Learn More on The New York Times >
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