1 big thing: The trouble with work
For the last several years, some of the world's leading thinkers have fretted over robots and artificial intelligence, with one particular worry — whether jobs across the U.S. and the rest of the advanced economies are going to be wiped out.
The big picture: As of now, no one truly knows what will happen, but everyone agrees on one point — that something is substantially broken when it comes to work. Most Americans have not received a real wage increase in decades, one-third of working-age people are not part of the labor force at all, and the education system seems divorced from the future economy.
So fraught has the subject become that radical solutions are now getting mainstream attention.
Oren Cass, Mitt Romney's former domestic policy adviser and a fellow at the Manhattan Institute, argues that the problem is so profound that it will only be solved by essentially throwing out the long-standing economic policies of both parties.
His new book, "The Once and Future Worker," rejects the usual explanations — that the problem is robots and automation. Rather, he says, public policy has pushed many workers away from physical labor, to which most are suited, and meanwhile taken whacks at the industrial economy, including extraction industries, that might employ these workers.
Cass told me that the entire economic system should be reordered away from a worship of greater GDP and toward wage growth, higher participation of workers in the labor force and a higher savings rate. The focus of policy should not be on supporting college for everyone, but on skills education. "What we want for society is more than just a larger economic pie," he says.
- Evidence that the system has failed, he argues, is that, although GDP has tripled since 1975 and spending on lower-income families has quadrupled, poverty has risen and wages have been flat.
- As a remedy, Cass, like Trump, takes a gigantic step away from decades of orthodoxy, urging an abandonment of both Great Society anti-poverty programs and supply-side tax cuts, arguing that both have resulted in the swath of Americans left behind.
- Public policy ought to attend primarily not to the health of companies nor the support of poor people, but specifically to workers — building a system in which people of all abilities can obtain a productive job. He calls this "productive pluralism."
The bottom line: The problems and the solutions that Cass proposes are neither Republican nor Democratic. The strength of the book is in striking a much-needed challenge to business as usual. But Cass is conspicuously attempting to give an intellectual foundation to Trump's off-the-cuff policymaking and to influence White House policy and 2020 candidates. In that sense, his book is a political screed. But he is asking the right questions and proposing what is probably needed — an upside-down change to economic policy.
2. Theft in China
With the flourish of a significant concession, China said today that it will punish companies and individuals who steal intellectual property, a primary U.S. complaint. But China hands are skeptical, Axios’ Erica Pandey writes.
"What they’ve done in the past is fail to enforce or, when they have to enforce, find somebody they don’t like, blame them, and then say to the Americans, 'See?'"— Jim Lewis of the Center for Strategic and International Studies
Background: Over the years, China has routinely batted away allegations of government-backed IP theft as hearsay, even when among the things stolen were plans for the F-35 fighter jet and a supersonic U.S. undersea missile.
- In 2015, Chinese President Xi Jinping — without admitting anything — pledged to halt cyber theft of IP, and the pilfering dropped dramatically.
The Xi-Obama agreement was good as far as it went, but it did not go far enough, says Samm Sacks, a cyber policy fellow at New America, a think tank.
- One major omission: The deal omitted a separate issue — forced technology transfers through which Beijing compels U.S. companies to share secrets with Chinese partners in order to gain access to China's massive market.
- Sacks expresses doubts that the transfers will stop.
- "I have not seen any indication from the Chinese side that this is an issue that they have any plans to address," Sacks says.
3. The great AI feud
A years-long feud between two famously quarrelsome AI experts has erupted anew on Twitter, leaving some embarrassed members of the field attempting to ignore the slinging of insults, and others taking sides.
Axios' Kaveh Waddell writes: The combatants — well-known to the AI community but not so much to the world at large — are Yann LeCun, Facebook’s chief AI scientist and an NYU professor, and Gary Marcus, a cognitive psychologist who also teaches at NYU.
Background: Last week, we wrote about the personal fault lines that have surfaced in artificial intelligence, which is oddly both an old and a new field. While AI was invented in the 1950s, it has only come into its own in the last six years, as fast computers have enabled long-gestating technology to work.
- Among the field's central debates is this arcane but prickly question: Is deep learning, the reigning AI technique, powerful enough to create human-like machine intelligence on its own?
In January, Marcus, who has been a critic of deep learning for years, stirred up a stormy debate with an article that fundamentally questioned deep learning as a long-term answer to machine intelligence.
Now, Marcus has published a new article on Medium, with more arguments. He wrote:
"What I hate is this: The notion that deep learning is without demonstrable limits and might, all by itself, get us to general intelligence, if we just give it a little more time and a little more data."
LeCun, who developed foundational technologies that power deep learning today, couldn't resist responding:
"This totally self-serving piece is so egregiously disconnected from reality that it doesn't deserve a response. Past exchanges have shown that writing a response would be a waste of time. We have better things to do with our time. Like actually doing research on AI."
One of their highest-profile bouts of sparring was videotaped at an NYU panel in 2017. Yet despite the hostility, the two seemed in reluctant agreement on the question at the elusive heart of the debate:
- Deep learning alone is insufficient to create an intelligent machine, they both acknowledged.
Instead, as in much of science's great squabbles, the biggest question may be simply who gets the last word.
4. Worthy of your time
How to measure innovation (Andrew Van Dam — WashPost)
Americans still won't move (Stef Kight — Axios)
Amazon's insider real estate trading (Josh Barbanel — WSJ)
Alibaba voice assistant is far better than Google's (Karen Hao — MIT Tech Review)
Singapore has Southeast Asia's biggest reskilling problem (Justina Lee — Nikkei Asian Review)
5. 1 Himalayan thing: Ginger, the robot waiter
One of the latest restaurants to replace waiters with machines has three robots, all named Ginger, who glide from the kitchen to the tables, cracking jokes for diners.
But it's not in China, Japan or the U.S. — the main venues for robot experimentation. It's in Nepal, writes Erica.
The big picture: Nepal is far from being an innovation center. It has a GDP of around $25 billion — 1/500 the size of China's and 1/800 of the United States'. And it graduates just 10,000 technologists a year. But a handful of startups are working to bring cutting-edge tech to the small Himalayan nation.
- One startup is Paaila Technology. This group of 25 engineers — none over the age of 27 — designed and built three "Gingers" and installed them at Naulo, a restaurant they opened in one of Kathmandu's poshest neighborhoods, reports the Economic Times of India. The restaurant's name roughly translates to "new."
- Much of Naulo is automated — customers order via a digitalized screen at their table, choosing from full-color photographs of pizza, Nepali dumplings and other dishes.
Fun fact: The Gingers themselves are very much handmade — they are painted, for instance, by a local mechanic.