Mini Briefs

Amazon Says It Will Retrain Workers It’s Automating Out of Jobs. But Does ‘Upskilling’ Even Work?

A piece evaluating Amazon’s ‘Upskilling 2025’ initiative, which involves investing $700 million to retrain one-third of its U.S. workforce (100,000 employees) to have needed skills as other jobs become automated. According to The Wall Stree Journal,

“Amazon said it would retrain 100,000 workers in total by expanding existing training programs and rolling out new ones meant to help its employees move into more-advanced jobs inside the company or find new careers outside of it. The training is voluntary and mostly free for employees and won’t obligate participants to remain at Amazon, the Seattle-based company said.”

The articles notes several articles have covered the failings of retraining programs in the past, but also covers reasons for why Amazon’s effort may work better: the company is retraining its own workers for jobs it knows will exist, and can direct its training efforts more intelligently. It’s also not a charitable effort, but rather a calculated investment in its own operations. Still, the lack of participation of the workers themselves in creating this program is problematic. The article concludes:

“Retraining will likely indeed work for some—but probably not many, and probably not those who need the jobs the most. Which is precisely why the only reasonably satisfactory path forward involves giving workers a seat at the table.”

How YouTube is failing children, and what it means for designing AI-moderated experiences

As covered in multiple recent articles, YouTube’s recommendation algorithm has been leading to children viewing often disturbing content:

“If your child uses YouTube without supervision, they have probably watched an animated video with Peppa Pig weeping as a dentist shoves a needle into her mouth, and then screaming as he extracts her teeth. Or the one where she is attacked by zombies, in the dark. Or the one where Frozen’s Elsa is burned alive. Or the one where a demon makes one of the Paw Patrol commit suicide.”

Google has attempted to address the problem, but its sheer scale has made it impossible to fully resolve. The article’s basic thesis is that YouTube’s basic mission to keep us addicted to consuming more and more content make these sorts of abuses of the system inevitable. We must decide to reject content addiction, rather than hope for algorithms or moderation to make it safe:

“We won’t solve it with an algorithm, or with an extra 2,700 content reviewers clogging up YouTube’s break-rooms. Any real solution will need to pursue a vision that is based on the aspirations and values we hold as a society, rather than being at the mercy of an “Up Next” list of videos developed using set of values that, as a society, we never granted license to.”

Advances & Business

• Boston Dynamics robots are preparing to leave the lab — is the world ready? - Not many robotics companies can boast legions of fans online, but not many robotics companies make robots quite like Boston Dynamics. Each time the firm shares new footage of its machines, they cause a sensation.

• How a Robot Named Moxie is Helping Nurses Spend More Time with Patients - If you’re tired of completing routine tasks on the hospital floor, such as running errands, dropping off specimens at the lab, and bringing supplies to new patients, a new robot named Moxie is here to help.

• Walmart Is Using AI to Prevent Checkout Theft - In a bid to cut down on theft and mistakes, Walmart is using artificial intelligence hooked up to cameras monitoring checkouts to ensure every item in your cart is scanned and paid for. This is already happening at over 1,000 Walmart stores.

• Machine learning has been used to automatically translate long-lost languages - In 1886, the British archaeologist Arthur Evans came across an ancient stone bearing a curious set of inscriptions in an unknown language. The stone came from the Mediterranean island of Crete, and Evans immediately traveled there to hunt for more evidence.

• DeepMind’s AI learns to generate realistic videos by watching YouTube clips - Perhaps you’ve heard of FaceApp, the mobile app that taps AI to transform selfies, or This Person Does Not Exist, which surfaces computer-generated photos of fictional people.

Concerns & Hype

• Facial Recognition Tech Is Growing Stronger, Thanks to Your Face - Dozens of databases of people’s faces are being compiled without their knowledge by companies and researchers, with many of the images then being shared around the world, in what has become a vast ecosystem fueling the spread of facial recognition technology.

• Elon Musk’s quest to stop the ‘AI apocalypse’ by merging man with machines - If you can’t beat them, join them. Or if you’re Elon Musk, the billionaire boss of private rocket outfit SpaceX and electric vehicle firm Tesla, why not just become them? 

Analysis & Policy

• How artificial intelligence can tackle climate change - Climate change is the biggest challenge facing the planet. It will need every solution possible, including technology like artificial intelligence (AI).

• Hype and reality in Chinese artificial intelligence - In MIT Technology Review, Jeff Ding shares five takeaways from his experience writing about and translating Chinese-language writing about artificial intelligence (AI) research in China.

• If you can identify what’s in these images, you’re smarter than AI - Computer vision has improved massively in recent years, but it’s still capable of making serious errors. So much so that there’s a whole field of research dedicated to studying pictures that are routinely misidentified by AI, known as “adversarial images.

Expert Opinions & Discussion within the field

• Moralizing AI: Can We Make Machines That Reason Ethically? - A commonly cited doomsday scenario when talking about runaway artificial intelligence is that it won’t know when to quit.

• Yes, there will be Robots - It’s just what some people might want to do in five years time when, according to this year’s feel-good report on Artificial Intelligence (AI), a fifth of jobs are predicted to be over-taken by computers.

• How the Transformers broke NLP leaderboards - This post summarizes some of the recent XLNet-prompted discussions on Twitter and offline. Idea credits go to Yoav Goldberg, Sam Bowman, Jason Weston, Alexis Conneau, Ted Pedersen, fellow members of Text Machine Lab, and many others. Any misconfiguration of those ideas is my own.

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