MIT AI model is ‘significantly’ better at predicting breast cancer

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The model can find breast cancer earlier and eliminates racial disparities in screening.

MIT researchers have invented a new AI-driven way of looking at mammograms that can help detect breast cancer in women up to five years in advance. A deep learning model created by a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital can predict — based on just a mammogram — whether a woman will develop breast cancer in the future. And unlike older methods, it works just as well on black patients as it does on white patients.

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The new digital divide is between people who opt out of algorithms and people who don’t

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Every aspect of life can be guided by artificial intelligence algorithms—from choosing what route to take for your morning commute, to deciding whom to take on a date, to complex legal and judicial matters such as predictive policing.

Big tech companies like Google and Facebook use AI to obtain insights on their gargantuan trove of detailed customer data. This allows them to monetize users’ collective preferences through practices such as micro-targeting, a strategy used by advertisers to narrowly target specific sets of users.

In parallel, many people now trust platforms and algorithms more than their own governments and civic society. An October 2018 study suggested that people demonstrate “algorithm appreciation,” to the extent that they would rely on advice more when they think it is from an algorithm than from a human.

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AI Ethics: Seven Traps

 

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The question of how to ensure that technological innovation in machine learning and artificial intelligence leads to ethically desirable—or, more minimally, ethically defensible—impacts on society has generated much public debate in recent years. Most of these discussions have been accompanied by a strong sense of urgency: as more and more studies about algorithmic bias have shown, the risk that emerging technologies will not only reflect, but also exacerbate structural injustice in society is significant.

So which ethical principles ought to govern machine learning systems in order to prevent morally and politically objectionable outcomes? In other words: what is AI Ethics? And indeed, “is ethical AI even possible?”, as a recent New York Times article asks?

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Very risky business: the pros and cons of insurance companies embracing artificial intelligence

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The enabling technology for insurers to use AI is the ‘ecosystem’ of sensors known as the internet of things.

It’s a new day not very far in the future. You wake up; your wristwatch has recorded how long you’ve slept, and monitored your heartbeat and breathing. You drive to work; car sensors track your speed and braking. You pick up some breakfast on your way, paying electronically; the transaction and the calorie content of your meal are recorded.

Then you have a car accident. You phone your insurance company. Your call is answered immediately. The voice on the other end knows your name and amiably chats to you about your pet cat and how your favourite football team did on the weekend.

You’re talking to a chat-bot. The reason it “knows” so much about you is because the insurance company is using artificial intelligence to scrape information about you from social media. It knows a lot more besides, because you’ve agreed to let it monitor your personal devices in exchange for cheaper insurance premiums.

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AI brought a 60-year old music-making machine to life

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Sound artist Yuri Suzuki used AI to complete Raymond Scott’s Electronium vision.

If you’ve seen Looney Tunes or The Simpsons, you’ve probably heard Raymond Scott’s music — which was adapted for those and other cartoons. But there’s a good chance you haven’t heard of Scott himself. A musician and inventor, Scott was ahead of his time. As early as the 1950s, he began working on the Electronium, a kind of music synthesizer that he hoped would perform and compose music simultaneously. While Scott invested $1 million and more than a decade in Electronium, he died before it was complete. Now, Fast Company reports, Pentagram partner and sound artist Yuri Suzuki has picked up where Scott left off.

Suzuki worked in partnership with the design studio Counterpoint and used Google’s Magenta AI to generate music the way Scott envisioned. Like the Electronium, Suzuki’s version has three panels. First, a player taps a melody, or even a few notes, on the center panel. Then, the AI uses that to compose music, which is shown on the right. And finally, the player can use the panel on the left to manipulate the music by adding effects or beats. It’s the kind of human-computer collaboration Scott dreamed of but didn’t have the digital technology to complete.

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AI : The future of photography ?

 

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How machine learning and artificially generated images might replace photography as we know it.

When hearing the words ‘AI’, ‘Machine Learning’ or ‘bot’ most people tend to visualize a walking, talking android robot which looks like something out of a Sci-Fi movie and immediately assume about a time far away in the future.

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Forget about artificial intelligence, extended intelligence is the future

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Last year, I participated in a discussion of The Human Use of Human Beings, Norbert Weiner’s groundbreaking book on cybernetics theory. Out of that grew what I now consider a manifesto against the growing singularity movement, which posits that artificial intelligence, or AI, will supersede and eventually displace us humans.

The notion of singularity – which includes the idea that AI will supercede humans with its exponential growth, making everything we humans have done and will do insignificant – is a religion created mostly by people who have designed and successfully deployed computation to solve problems previously considered impossibly complex for machines.

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What the rest of the world doesn’t know about Chinese AI

 

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ChinAI Jeff Ding’s weekly newsletter reporting on the Chinese AI scene; on the occasion of the newsletter’s first anniversary, Ding has posted a roundup of things about the Chinese AI scene that the rest of the world doesn’t know about, or harbors incorrect beliefs about.

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Is artificial intelligence, intelligent? How machine learning has developed.

Artificial intelligence has been around for decades. Is it smart enough now to predict Alzheimer’s? (Brian Monroe/The Washington Post)

What makes artificial intelligence intelligent? Is it able to learn from errors or recognize, say, the letters of the alphabet in a set of random shapes like a human can?

These are some of the questions developers of AI ask. What began as sluggish programs on hulking machines has taken the form of code that anyone in a particular field could test out and manipulate to suit their needs.

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A robot has figured out how to use tools

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In a startling demonstration, the machine drew on experimentation, data, and observation of humans to learn how simple implements could help it achieve a task.

Learning to use tools played a crucial role in the evolution of human intelligence. It may yet prove vital to the emergence of smarter, more capable robots, too.

New research shows that robots can figure out at least the rudiments of tool use, through a combination of experimenting and observing people.

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