What can AI learn from Human intelligence?

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At HAI’s fall conference, scholars discussed novel ways AI can learn from human intelligence – and vice versa.

Can we teach robots to generalize their learning? How can algorithms become more commonsensical? Can a child’s learning style influence AI?

Stanford Institute for Human-Centered Artificial Intelligence’s fall conference considered those and other questions to understand how to mutually improve and better understand artificial and human intelligence. The event featured the theme of “triangulating intelligence” among the fields of AI, neuroscience, and psychology to develop research and applications for large-scale impact.

HAI faculty associate directors Christopher Manning, a Stanford professor of machine learning, linguistics, and computer science, and Surya Ganguli, a Stanford associate professor of neurobiology, served as hosts and panel moderators for the conference, which was co-sponsored by Stanford’s Wu-Tsai Neurosciences Institute, Department of Psychology, and Symbolic Systems program.

Speakers described cutting-edge approaches—some established, some new—to create a two-way flow of insights between research on human and machine-based intelligence, for powerful application. Here are some of their key takeaways.

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The most fundamental skill: Intentional learning and the career advantage

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Learning itself is a skill. Unlocking the mindsets and skills to develop it can boost personal and professional lives and deliver a competitive edge.

The call for individuals and organizations alike to invest in learning and development has never been more insistent. The World Economic Forum recently declared a reskilling emergency as the world faces more than one billion jobs transformed by technology. Even before COVID-19 emerged, the world of stable lifetime employment had faded in the rearview mirror, replaced by the expectation that both executives and employees must continually refresh their skills. The pandemic has only heightened the urgency of doubling down on skill building, either to keep up with the speed of transformation now underway or to manage the particulars of working in new ways.

Despite this context—and the nearly constant refrain for people to adapt to it by becoming lifelong learners—many companies struggle to meet their reskilling goals, and many individuals struggle to learn new and unfamiliar topics effectively. We believe that an underlying cause is the fact that so few adults have been trained in the core skills and mindsets of effective learners. Learning itself is a skill, and developing it is a critical driver of long-term career success. People who have mastered the mindsets and skills of effective learning can grow faster than their peers and gain more of the benefits from all the learning opportunities that come their way.

This article, supported by research and our decades of experience working as talent and learning professionals, explores the core mindsets and skills of effective learners. People who master these mindsets and skills become what we call intentional learners: possessors of what we believe might be the most fundamental skill for professionals to cultivate in the coming decades. In the process they will unlock tremendous value both for themselves and for those they manage in the organizations where they work.

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The surprising upsides of worrying

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Anxiety can be exhausting, but there is often a reason for it – and there are some surprising benefits to certain kinds of worrying.

“I’m a near-professional worrier,” admits Kate Sweeny ruefully. She’s struggled for much of her life with anxiety over things she can’t entirely control – including, these days, whether her parents are following social-distancing guidance during the Covid-19 pandemic.

A constant hum of low-grade worry affects many people, but what’s distinct about Sweeny is that it partly motivated her career choices. As a health psychologist at the University of California, Riverside, she specialises in understanding worry and stress.

“Not everybody uses their own life as fodder for research,” she laughs, but she’s found inspiration in her own experiences. One of her surprising findings has been that worrying can be beneficial in a variety of situations, from waiting for exam results to safeguarding health.

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A.I. can tell if you’re a good surgeon just by scanning your brain

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Could a brain scan be the best way to tell a top-notch surgeon? Well, kind of. Researchers at Rensselaer Polytechnic Institute and the University at Buffalo have developed Brain-NET, a deep learning A.I. tool that can accurately predict a surgeon’s certification scores based on their neuroimaging data.

This certification score, known as the Fundamentals of Laparoscopic Surgery program (FLS), is currently calculated manually using a formula that is extremely time and labor-consuming. The idea behind it is to give an objective assessment of surgical skills, thereby demonstrating effective training.

“The Fundamental of Laparoscopic Surgery program has been adopted nationally for surgical residents, fellows and practicing physicians to learn and practice laparoscopic skills to have the opportunity to definitely measure and document those skills,” Xavier Intes, a professor of biomedical engineering at Rensselaer, told Digital Trends. “One key aspect of such [a] program is a scoring metric that is computed based on the time of the surgical task execution, as well as error estimation.”

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High-speed microscope captures fleeting brain signals

When a neuron fires, calcium flows into the cell in a wave that sweeps along the cell body. Images of this infragranular neuron were obtained three times per second by two-dimensional scanning with a Bessel focus. Redder structures are deeper in the mouse cortex. (UC Berkeley images by Na Ji)

Electrical and chemical signals flash through our brains constantly as we move through the world, but it would take a high-speed camera and a window into the brain to capture their fleeting paths.

University of California, Berkeley, investigators have now built such a camera: a microscope that can image the brain of an alert mouse 1,000 times a second, recording for the first time the passage of millisecond electrical pulses through neurons.

“This is really exciting, because we are now able to do something that people really weren’t able to do before,” said lead researcher Na Ji, a UC Berkeley associate professor of physics and of molecular and cell biology.

The new imaging technique combines two-photon fluorescence microscopy and all-optical laser scanning in a state-of-the-art microscope that can image a two-dimensional slice through the neocortex of the mouse brain up to 3,000 times per second. That’s fast enough to trace electrical signals flowing through brain circuits.

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The major discoveries that could transform the world in the next decade

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Here’s what scientists are really excited about.

The last decade ushered in some truly revolutionary advances in science, from the discovery of the Higgs boson to the use of CRISPR for Sci-Fi esque gene editing. But what are some of the biggest breakthroughs still to come? Live Science asked several experts in their field what discoveries, techniques and developments they’re most excited to see emerge in the 2020s.

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Mini brains grown in the laboratory produce brainwaves. Now what?

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It’s hard to study the human brain. It is the most complex in the animal kingdom with its massive collection of neurons, 80-100 billion to be exact, three times more than chimpanzees. Research relating our brains to the brains of mice and monkeys can only go so far. And because of this complexity, scientists often came up short when studying diseases such as schizophrenia, autism, and Alzheimer’s in the brains of monkeys and mice.

Enter minibrains.

Minibrains are small clusters of human brain cells that can be grown in a Petri dish. Floating through the agar, these small gray lumps don’t look particularly impressive, but they are allowing scientists to study actual living human brain tissue in ways they couldn’t before.

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Why you should try micro mastery

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The wellness case for learning new skills

In the summer of 2016 I was very unhappy. I was coming up on my year anniversary of living in London, where we had moved from Brooklyn for my husband’s job, but I still felt pitifully lonely and poorly adjusted to the culture. I reentered therapy, tried to socialize often, started volunteering, and focused on doing things for pleasure rather than out of obligation.

But there was one thing that alleviated my sadness more than others: I learned to drive a stick shift.

In Europe, automatics were more expensive to rent, so it was in my best interest to try to overcome any manual driving anxiety head-on. My husband and I decided to spend two weeks in France, and I spent much of that vacation stalling out on country roads, navigating dreaded traffic circles, and ultimately speeding down the highways. When I returned to London I told people about the beaches and baguettes in France, but I mostly wanted to talk about how I could now officially drive stick.

I had discovered the beauty of “micromastery”: working to develop competence in a single, concrete skill. The term was coined by the writers Tahir Shah and Robert Twigger; Twigger later published his 2017 book, Micromastery: Learn Small, Learn Fast, and Unlock Your Potential to Achieve Anything, which contains instructions for laying a brick wall, making sushi, and brewing beer. In the introduction, Twigger writes that he was stymied by the idea that he had to work for years to acquire any truly valuable skill, but that he still wanted to learn and create, so he decided to focus on making the perfect omelet: his first micromastery.

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Why the 8-hour workday doesn’t work

 

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The eight-hour workday is an outdated and ineffective approach to work. If you want to be as productive as possible, you need to let go of this relic and find a new approach.

The eight-hour workday was created during the industrial revolution as an effort to cut down on the number of hours of manual labor that workers were forced to endure on the factory floor. This breakthrough was a more humane approach to work 200 years ago, yet it possesses little relevance for us today.

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Striking study reveals how dietary fats enter the brain and cause depression

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A new study demonstrates how fatty acids can enter the brain and disrupt signaling pathways that lead to depression

An intriguing new study, led by scientists from the University of Glasgow, suggests there is a direct causative link between eating a high-fat diet and the development of depression. The new research demonstrates how certain dietary fats can enter the brain, disrupt specific signaling pathways in the hypothalamus, and subsequently induce signs of depression.

Scientists have long observed a strong correlation between obesity and depression and, while it may seem like the two are simply interlinked through obvious psychological associations, some studies are starting to suggest the connection may actually be underpinned by biological mechanisms.

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The importance of foresight : Why intuition and imagination will be critical in the future of work

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In his book Thinking Fast and Slow, Daniel Kahneman refers to the parts of our brain, where he suggests there are two competing intelligence at play.

He specifies one area affiliated to “system 1” which is known to be an area relying on speed in decision making and on emotion in information perceiving. System 1 is based largely on our instinct and intuition unconsciously stored by past experiences that are often rapidly available to memory. The second area is affiliated to “system 2” which is known to be an area for slow and deliberate decision making and more rational in information perceiving. This area takes in information based on our conscious appraisal of current events, and our stored episodic long-term memories, which are slowly available to memory. Why do we care?

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Can we stop AI outsmarting humanity?

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The spectre of superintelligent machines doing us harm is not just science fiction, technologists say – so how can we ensure AI remains ‘friendly’ to its makers?

It began three and a half billion years ago in a pool of muck, when a molecule made a copy of itself and so became the ultimate ancestor of all earthly life. It began four million years ago, when brain volumes began climbing rapidly in the hominid line.

Fifty thousand years ago with the rise of Homo sapiens sapiens.

Ten thousand years ago with the invention of civilization.

Five hundred years ago with the invention of the printing press.

Fifty years ago with the invention of the computer.

In less than thirty years, it will end.

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