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How State Politics Is Playing a Huge Role in Artificial Intelligence: Eye on A.I.

August 13, 2019, 3:04 PM UTC

New York Gov. Andrew Cuomo signed legislation in late July to create a temporary state commission that will examine how artificial intelligence impacts his state.

In doing so, New York joined Vermont, Alabama, and Washington in establishing an A.I. task force that will examine the cutting-edge technology and then make recommendations about how it should be regulated. The groups vary in their mission, but the general message is the same: companies pushing A.I., the brains behind innovation like robotics and facial recognition software, can’t necessarily be trusted to do what’s in the best interest of state residents.

Brandie Nonnecke, founding director of University of California’s Center for Information Technology Research in the Interest of Society Policy Lab, says that task forces could help keep state lawmakers up to date about the technology. The end result, she says, will be better-written bills that don’t get stuck in legislative purgatory.

“I think it’s important that the states engage in these task forces,” Nonnecke says. “It allows them better identify the needs and to gather expert feedback.”

The tasks forces are typically filled by industry experts, politicians, and academics who periodically meet and create reports intended to educate lawmakers about A.I. policy.

In New York, the new A.I. task force must present a final report to Gov. Cuomo and other state leaders by the end of 2020 detailing A.I.’s impact on data privacy, how to regulate A.I., and the potential impact of regulation on the tech industry. Meanwhile, in Washington, the focus is very narrow: The impact of A.I. on employment in the state.

At the federal level since Nov. 2018, members of Congress have introduced eight A.I.-related bills, according to Nonnecke. They include the Artificial Intelligence Initiative Act that would increase funding for A.I. research, and the Commercial Facial Recognition Privacy Act that would require certain organizations to get consent from users to scan their faces.

None have actually passed.

States, in contrast, and are more likely to enact A.I.-related policies, Nonnecke wrote in May. Additionally, she believes that state A.I. task forces could have more sway with lawmakers and are able to put the topic in front of them more often, she told Fortune.  

If California had an A.I. task force, Nonnecke said, it may have led to a better law that prohibit bots— software that runs automated tasks—from influencing voters with false information during elections, among other things. That law, which she said includes several gaping holes, went into effect in July.

“The intent of the law is great—we shouldn’t deceive people,” Nonnecke says. But the bill lacks important details, she added, like who is supposed to monitor bots on social media services, where disinformation runs rampant, while also including a convoluted definition of bots.

One thing is certain: Expect lawmakers to introducing more A.I.-related bills, even if they lack nuance and specifics. Those rules will have a huge impact, good and bad, on all kinds of industries as well as on a public that must live with the data collection, tracking, and upheaval in employment that the technology will inevitably bring.

Jonathan Vanian

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Story updated Aug. 19 to include Alabama as a state that has created an A.I. commission.


Predicting crime. NBC News published a big report detailing how Amazon Web Services is selling A.I. technology like facial recognition software to law enforcement across the U.S. Among the report’s highlights is the description of transcription technology that law enforcement in Jefferson County, Al. use to “to sift through millions of jail calls a year ─ all legally recorded ─ flagging conversations with keywords that may provide indications of trouble,” the report said.

Facebook’s facial fail. Facebook was a dealt a setback in its attempt to overturn a class action lawsuit against the company for allegedly collecting biometric data from users without their consent to feed into its facial recognition technology, Reuters reported. The report said, that “The 3-0 decision from the 9th U.S. Circuit Court of Appeals in San Francisco over Facebook’s facial recognition technology exposes the company to billions of dollars in potential damages to the Illinois users who brought the case.”

What should you wear today? Nike said it acquired the data-crunching startup Celect, and would use its technology to help the apparel giant better predict what styles of footwear and clothing shoppers may be interested in. Terms of the deal were not disclosed.

Greece’s A.I. scene. Ernst & Young plans to create an A.I. research center in Greece, according to the Kathimerini newspaper in Athens. The Demokritos National Center for Scientific Research will help the consulting firm create the new outpost, which will employ 20 researchers in its first year.


Michael Stonebraker, a database expert and co-founder of data management startup Tamr, discussed machine learning’s benefits with tech publication SiliconANGLE. Machine learning can help reduce the number of complicated “rules” corporate database managers have to create to accesses and interpret data, he explained. “You’re going to have to write a huge number of rules that no one can possibly understand,” Stonebraker told the publication. “If you don’t use machine learning, you’re absolutely toast.”


Healthcare startup Ro hired Todd Levy to be its chief technology officer, TechCrunch reported. Levy was previously the CTO of Buzzfeed and was the co-founder and CTO of

Healthcare company Oncology Analytics picked David Fusari to be its CTO. Fusari was previously CTO and co-founder of healthcare firm TriNetX.


Deep mapping. Researchers from the Digital Earth Science, Institute of Remote Sensing and Digital Earth at the Chinese Academy of Sciences published a paper about using deep learning to identify objects in physical maps. The paper shows how the researcher’s A.I. system could accurately classify “roads,” “forest land,” “agricultural facilities,” and “residential area” on a land-use map for China’s Guangdong province.

Deep corrosion. Researchers from Monash University and The Australian National University published a paper about using deep learning to automatically detect corrosion in buildings, pipes, and oil rigs. The researchers created a website that included photos of buildings and industrial equipment, and invited people to indicate whether they saw any corrosion on them. The researchers then used that data to train a neural network—software that learns—to recognize corrosion.


‘You’re Pretty Stupid.’ What Can Happen to Your Business When A.I. Goes Awry – By Anne Fisher

Twitter May Have Shared User Data Without Permission – By Chris Morris

How Amazon, Apple, Google, and Microsoft Created an Eavesdropping Explosion – By Jonathan Vanian


Deep Losses. The Financial Times examines the finances of DeepMind, the A.I. research company that Google-parent Alphabet bought in 2014 for over $400 million. The newspaper reported that DeepMind lost $571 million last year, which was a whopping 55% increase from the previous year. The paper reports that DeepMind sells its technology exclusively to Alphabet, which logs the sales “as technical service fees.” Google has used DeepMind’s technology in its data centers to automatically calibrate cooling settings to more efficiently save power costs, among other uses. DeepMind’s big spending underscores how much money it takes for companies to research the latest cutting-edge A.I. techniques. The Times also notes that DeepMind’s “heavy spending reflects the rising cost of talent as big tech companies race against each other to develop AI technology.”