Are we really living in the age of a “cyber arms race” and an “information Iron Curtain?”
- Text by Katerina Patin
Are we really living in the age of a “cyber arms race” and an “information Iron Curtain?” Cold War vocabulary is back and leading the headlines. The escalating trade war between the U.S. and China has resurrected the metaphors as politicians and TV pundits try to draw meaningful parallels between the nuclear and the technology eras.
But the issue is these analogies have expired for a reason; they just don’t apply anymore and as Justin Sherman writes for Wired, it’s possible that militarized, Cold War language is producing “overly combative policies on emerging tech.”
There are a number of reasons why these metaphors are obsolete and our latest piece by Charles Rollet gets at what I think is the most telling difference — while the Cold War was defined by borders and competing political ideology, our tech age is more often borderless and apolitical. This is especially obvious when we look at collaborations between Western technologists and China.
Why did Anil K. Jain, a rockstar in biometrics research at Michigan State, present a paper in Xinjiang the same month that a UN human rights panel described the region as a “massive internment camp”? A 30-second Google search could have told Professor Jain — one of the world’s most influential computer scientists — that the ethnically Uyghur president of the university sponsoring the conference was arrested in 2017 and is facing imminent execution.
Here are a few more examples of some of those ties:
- For years the New York State and California State Teachers’ Retirement Systems have held millions of dollars in shares in Hikvision, the world’s largest supplier of surveillance equipment, nicknamed China’s “Big Brother firm.” Also, the agency administering retirement savings for federal employees and members of the armed services is shifting its investment plan in a change that would expose its $50 billion in retirement funds to investments in Chinese companies. Marco Rubio is one of the loudest critics, writing that the decision would “effectively fund the Chinese government.”
- Two years after U.S. sanctions outlawed Russian antivirus software, Kaspersky Lab’s tools are still installed on U.S. government military networks and other government defense contractors. The reason? It’s just too complicated to remove it. The ban came out of fear that the Kremlin has influence over the company and can weaponize the software for surveillance. The Department of Homeland Security said that all the software was removed this spring, but a Forbes investigation revealed that was not the case.
- In a similar case, it seems that Chinese-made surveillance cameras are also so integrated into U.S. security infrastructure that it’s essentially impossible to comply with the recent Congressional ban on the technology.
Buy the Apple Watch or…Die? The Wall Street Journal’s Joanna Stern writes that she has some “really mixed reactions” to Apple’s fear-based marketing strategy to sell its latest Apple Watch. I’m happy to pile on here. The video Tim Cook presented during last week’s keynote featured stories of people who have had their lives literally saved by their watch: an Apple Watch alerts its pregnant owner that her heart rate was abnormal, prompting her to see a doctor and have an emergency C section. Another watch automatically called 911 when an elderly Apple consumer fell down. “Not only is that a bit of an icky place to be when selling gadgets, it could also become a liability if the Watch is ever unable to save someone’s life,” writes Stern in her live coverage of the keynote.
When it comes to carbon emissions, 1 AI model = 5 cars. Some impressive research from the University of Massachusetts, Amherst looking at the carbon footprint of deep learning. Turns out, an AI model emits nearly the same amount of carbon as the lifetime of five average American cars, including the manufacture of the car. What’s also surprising is how surprised scientist were by the figures, yet another example of how research around AI lags behind the development of the tech itself.