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After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says Tom Standage

AI excites fear and enthusiasm in equal measure, and raises a lot of questions.
Others fear that AI poses an existential threat to humanity, because superintelligent computers might not share mankind’s goals and could turn on their creators.
Technologists, economists and philosophers are now debating the implications of artificial intelligence (AI), a fast-moving technology that enables machines to perform tasks that could previously be done only by humans.
In 2015 a record $8.5 billion was spent on AI companies, nearly four times as much as in 2010, according to Quid, a data-analysis company.
Technology giants are buying AI startups and competing to attract the best researchers from academia.

Read the full article, click here.

@EricTopol: “A brainy, upbeat special report on Artificial Intelligence @TheEconomist @tomstandage #AI”

After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says…

After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says Tom Standage

43 New External Machine Learning Resources and Updated Articles

A Complete Tutorial to learn Data Science in R from Scratch
How William Cleveland Turned Data Visualization Into a Science *
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Massive innovations in data science to come
Former Facebook Data Scientist Shares How to Wrangle Your Data

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@Ronald_vanLoon: “43 New External Machine Learning Resources and Updated Articles | #DataScience #MachineLear…”

Starred articles are candidates for the picture of the week. A comprehensive list of all past resources is found here. We are in the process of automatically c…

43 New External Machine Learning Resources and Updated Articles

After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says Tom Standage

People at the time did not talk of an “industrial revolution” but of the “machinery question”.
In 2015 a record $8.5 billion was spent on AI companies, nearly four times as much as in 2010, according to Quid, a data-analysis company.
AI excites fear and enthusiasm in equal measure, and raises a lot of questions.
Technologists, economists and philosophers are now debating the implications of artificial intelligence (AI), a fast-moving technology that enables machines to perform tasks that could previously be done only by humans.
Technology giants are buying AI startups and competing to attract the best researchers from academia.

Read the full article, click here.

@TheEconomist: “Artificial intelligence—the return of the machinery question”

After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says…

After many false starts, artificial intelligence has taken off. Will it cause mass unemployment or even destroy mankind? History can provide some helpful clues, says Tom Standage

What history tells us about the future of artificial intelligence—and how society should respond

And welfare systems will have to be updated, to smooth the transitions between jobs and to support workers while they pick up new skills.
Others worry that AI will cause widespread unemployment, by automating cognitive tasks that could previously be done only by people.
When jobs are perishable, technologies come and go and people’s working lives are longer, social skills are a foundation.
Even if job losses in the short term are likely to be more than offset by the creation of new jobs in the long term, the experience of the 19th century shows that the transition can be traumatic.
As technology changes the skills needed for each profession, workers will have to adjust.

Read the full article, click here.

@TheEconomist: “What history tells us about the future of artificial intelligence—and how we should respond”

What history tells us about the future of artificial intelligence—and how society should respond

Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups

Google Ventures , which backed over 10 unique companies, ranked second as an active investor in AI.
As we earlier reported , Google is also a major acquirer of AI startups.
Intel Capital is the most active corporate investor on our list, having backed over a dozen separate unique AI-based companies, including healthcare startup Lumiata , machine-learning platform DataRobot , and imaging startup Perfant Technology .
Corporates and their venture capital groups are among the most active investors in this category ( tech corporates have also been active acquirers in the category ).
Our artificial intelligence category includes companies applying AI solutions to verticals like healthcare, advertising, and finance as well as those developing general-purpose AI tech.

Read the full article, click here.

@peterxing: “Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups”

With AI dealmaking exploding recently, corporates and their venture arms have not been left out of the rush.

Intel, Google, GE, And Samsung Among Most Active Corporate Investors In AI Startups

Concrete AI safety problems

Advancing AI requires making AI systems smarter, but it also requires preventing accidents – that is, ensuring that AI systems do what people actually want them to do.
We think that broad AI safety collaborations will enable everyone to build better machine learning systems.
We (along with researchers from Berkeley and Stanford) are co-authors on today’s paper led by Google Brain researchers, Concrete Problems in AI Safety .
Many of the problems are not new, but the paper explores them in the context of cutting-edge systems.
The paper explores many research problems around ensuring that modern machine learning systems operate as intended.

Read the full article, click here.

@RickKing16: “Concrete #AI safety problems”

We (along with researchers from Berkeley and Stanford) are co-authors on today’s paper led by Google Brain researchers, Concrete Problems in AI Safety. The paper explores many research problems around ensuring that modern machine learning systems operate as intended. (The problems are very practical, and we’ve already seen some being integrated into OpenAI Gym.)

Concrete AI safety problems

How Behavioral Economics Helps Entrepreneurs—and March Madness Pickers

But choice architecture’s actual point is to help consumers more easily get to the choice that best serves them .
So now let’s take a moment to look at how understanding behavioral economics can be essential in helping entrepreneurs become better business leaders-and March Madness pickers.
The good news for entrepreneurs-and bracket pickers-is that data science and well-structured teams can help us “think slower” and ameliorate such cognitive biases.
Market data provided by Interactive Data .
In one experiment conducted at a racetrack, gamblers were asked how confident they were in their bets either immediately before or after placing their bets; those polled afterward were significantly more confident in their choice than those asked beforehand.

Read the full article, click here.

@andi_staub: “#BigData? #IoT? #AI?
How #BehavioralEconomics Helps Entrepreneurs

#fintech #startup #biases”

Behavioral economics explains a lot of the biases that distort the choices made by entrepreneurs and March Madness bracket pickers.

How Behavioral Economics Helps Entrepreneurs—and March Madness Pickers