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RS 231 - Helen Toner on "Misconceptions about China and artificial intelligence"

Release date: April 15th, 2019

Helen Toner

Helen Toner, the director of strategy at Georgetown's Center for Security and Emerging Technology (CSET), shares her observations from the last few years of talking with AI scientists and policymakers in the US and China. Helen and Julia discuss, among other things:

  • How do the views of Chinese and American AI scientists differ?
  • How is media coverage of China misleading?
  • Why the notion of an "AI arms race" is flawed
  • Why measures of China's AI capabilities are overstated
  • Reasons for optimism and pessimism about international cooperation over AI


"Age of Ambition: Chasing Fortune, Truth, and Faith in the New China" by Evan Osnos

"The Beautiful Country and the Middle Kingdom: America and China, 1776 to the Present" by John Pomfret

Center for Security and Emerging Technology

A recent article co-authored by Helen, in Foreign Affairs: "Beyond the AI Arms Race: America, China, and the Dangers of Zero-Sum Thinking"

Follow Helen Toner on Twitter

Edited by Brent Silk

Music by Miracles of Modern Science

Full Transcripts 

Reader Comments (4)

Wow, that's what I was searching for, what a material!present here at this website, thanks admin of this web site.
Really great podcast. This issue definitely merits more public attention.

Good Foreign Affairs article. Innovation and Development will indeed have more impact than either (1) massive amounts of "big" data, (2) speculative investment, or (3) the combination of (1) and (2). Progress will come from primary research and new discoveries.

The Western News Media definitely did misrepresent and over dramatize the China Social Credit Score System (no real surprise though).

China aggressively manipulates its GDP numbers in order to meet the demands of government leadership. China also has entire vacant cities built in order to increase construction output.

One might seriously doubt that Chinese citizens actually have more acceptance of their government having their private data than corporations having that data. That seems like a statistic that the communist government itself either directly produced, or else procured the services of some news or analysis organization to produce.

Regulation of AI will probably ultimately come from the Federal Trade Commission (FTC) and other consumer protection agencies. Real rapid advances in AI applications will probably originate with the commercial sector. Most governments lack the adaptability, insight, and responsiveness to consumer demand necessary to create highly marketable products that can grow the industry.
April 16, 2019 | Unregistered CommenterJameson
Fundamental machine learning algorithms haven't evolved much in decades, but computing power and volume of data has increased. The U.S. collects a lot of data, but it's stovepiped. China's data may be more centralized.

Google invests a lot in AI and owes a lot to DARPA, but then refuses to develop AI for the U.S. military while opening an AI center in China. Microsoft and Amazon have been less treacherous so far, and there are plenty of other companies and labs that are happy to do U.S. defense work, as you can see in the DARPA AI Colloquium.

Of course after Google made its TensorFlow library open-source, anyone can use it including China and North Korea for that matter. And anyone can read publications and patents. To stay ahead of competitors, you have to keep information secret, but the U.S. has had a hard time doing that.

Autonomy is an important part of everyone's defense strategy, and you can compare who's ahead in developing and deploying unmanned systems. China is reportedly throwing a lot of money at it. Don't underestimate them the way we underestimated North Korea's nuclear program.
April 18, 2019 | Unregistered CommenterMax
Je vous aiderai à faire ce projet en cas de succès, laissez-moi l'essayer, merci
April 23, 2019 | Unregistered Commenterslither io

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