1 big thing: AI hubris
For the better part of a decade, artificial intelligence has been propelled by a rocket fuel in seemingly endless supply. Deep learning, a method that allows machines to identify hidden patterns in data, has powered commercial applications like autonomous vehicles and voice assistants, and it's potentially worth trillions of dollars a year, Kaveh reports.
But the rosy portrait of unstoppable progress belies a fear among some AI luminaries that things are not on the right path. In a new sort of resource curse, they say that deep learning has sucked energy away from other strains of inquiry without which AI may never approach even a child's intellectual capabilities.
The big picture: For the past 5 years, Elon Musk and others have warned of a future disaster resulting from unchecked superintelligent AI. But today, much of the field is caught in a rather more elementary tug-of-war over which avenue will imbue AI even with the capacity for basic understanding.
- "This is a struggle that goes back decades and is at the heart of the field," says Pedro Domingos, a University of Washington professor and the head of machine learning at D.E. Shaw, an investment firm. "People on either side of it think the others are crazy."
- "The field has gotten ahead of its skis," argues NYU's Gary Marcus, a dogged critic of the field's obsession with deep learning. "We think that if people don't change course, it's going to be destructive."
Since the field took shape in the 1950s, artificial intelligence has advanced in fits and starts, with various tribes claiming the vanguard at different points. The current period began in the early 2010s, when a trio of researchers in Canada brought AI out of a decadeslong funk by reviving deep learning, aided by new and powerful hardware.
Now, some of those same pioneers are warning against leaning too heavily on their contributions, and researchers with one foot in adjacent fields are sounding an increasingly insistent alarm about AI’s trajectory.
- "We are telling the young generation to not take our words for the gospel — because some do, unfortunately — and explore new things, because this is how science progresses," says the University of Montreal's Yoshua Bengio, who this year shared the Turing Award, the highest accolade in computing, with Yann LeCun and Geoffrey Hinton for reinventing deep learning.
- "The field has become a little too focused on deep learning, which means a lot of other things that should be explored aren't being explored," Domingos says. New students are "very seduced by deep learning," he says. "Everybody wants to do it."
- Next month, Marcus will publish a book with his NYU colleague Ernest Davis called "Rebooting AI," laying out in excruciating detail where deep learning falls short.
What's missing is common sense. Without it, argues Marcus, machines will never be able to actually comprehend a passage of fiction or navigate a cluttered home to tidy up before guests arrive.
- Deep learning systems are built on statistics and patterns, but don't have background knowledge outside the data they've been fed. By contrast, humans bring decades of understanding about the world into every single interaction.
- Marcus and others want to build these crucial foundations, or “priors,” into AI systems. That will likely require borrowing from other approaches to AI — especially symbolic reasoning, now sometimes called “good old-fashioned AI,” which explicitly spells out relationships between things.
But, but, but: If indeed the field is headed for a dead end, the impasse certainly isn't around the next bend. "The data at this point supports continuing success," says Oren Etzioni, CEO of the Allen Institute for AI. "But it's impossible to tell how far that goes."
2. The disinformation industry
Yesterday we reported on the expectation that Russia will mount a new cyber operation around the 2020 U.S. elections. But while foreign meddling is illegal, no law prevents candidates or anyone else from launching a political disinformation campaign inside the U.S., as long as no foreign money is involved, reports Axios' Joe Uchill.
It is similar globally.
- A Philippine-based firm claims to be manipulating social media for political clients around the world, including Great Britain; Mexican campaigns for city and national offices use social media chicanery; and researchers at Google's altruistic technology outpost Jigsaw recently rented a Moscow-based outfit to run a disinformation campaign to test how its campaigns worked.
- Campaigns have also been spotted in Israel, Macedonia and throughout South America.
"These tactics have been used by candidates all over the world," said Camille François of the social media analysis firm Graphika.
3. Surprising stat: The 40-year pay gap
The rise of salary inequality has been a primary issue at least since 2014, when Thomas Piketty published the English translation of his landmark, "Capital in the Twenty-First Century." Still, the statistics can startle.
Average CEO pay in the U.S. in 1978 was $1.7 million. Adjusted for inflation, it was $17 million last year, a 10x increase, according to a new report by Lawrence Mishel and Julia Wolfe at the Economic Policy Institute (h/t Ian Bremmer).
The average private-sector worker was paid $50,000 in 1978 and $60,000 last year — just 12% higher.
4. Worthy of your time
AI and the importance of the double-take (Kevin Hartnett — Quanta)
Iran's spree of cyberattacks (Robert Mogielnicki — Axios)
The physics of Simone Biles' triple-double (Rhett Allain — Wired)
A high-tech hunt for Amelia Earhart (Rachel Hartigan Shea — National Geo) (h/t Don Van Natta)
The flash from a black hole (Hannah Osborne — Newsweek) (h/t Azeem Azhar)
5. 1 senior thing: The gray entrepreneur
Among the big U.S. workplace trends are aging workers and a yawning need for skilled employees. Enter Senior Planet, a Manhattan community center meant to harness the entrepreneurial spirit of folks 60 and older.
It's run by Tom Kamber, and it's filled with senior citizens boning up on their tech skills so they can start digital businesses, reports Lauren Smiley of MIT Tech Review.
- The center is based on a Catch-22: Companies desperately need workers, and older employees are far more loyal than younger ones. But the same companies are often ageist, and they don't picture older workers in their open slots.
- Kamber has one big aim: To prep "seniors to hack their way through a world conspiring to keep them sidelined," Smiley writes.
Thanks for reading!