Lifeboat Foundation

• There has been a 14X increase in the number of active AI startups since 2000. Crunchbase, VentureSource, and Sand Hill Econometrics were also used for completing this analysis with AI startups in Crunchbase cross-referenced to venture-backed companies in the VentureSource database. Any venture-backed companies from the Crunchbase list that were identified in the VentureSource database were included.

• The share of jobs requiring AI skills has grown 4.5X since 2013., The growth of the share of US jobs requiring AI skills on the Indeed.com platform was calculated by first identifying AI-related jobs using titles and keywords in descriptions. Job growth is a calculated as a multiple of the share of jobs on the Indeed platform that required AI skills in the U.S. starting in January 2013. The study also calculated the growth of the share of jobs requiring AI skills on the Indeed.com platform, by country. Despite the rapid growth of the Canada and UK. AI job markets, Indeed.com reports they are respectively still 5% and 27% of the absolute size of the US AI job market.

• Machine Learning, Deep Learning and Natural Language Processing (NLP) are the three most in-demand skills on Monster.com. Just two years ago NLP had been predicted to be the most in-demand skill for application developers creating new AI apps. In addition to skills creating AI apps, machine learning techniques, Python, Java, C++, experience with open source development environments, Spark, MATLAB, and Hadoop are the most in-demand skills. Based on an analysis of Monster.com entries as of today, the median salary is $127,000 in the U.S. for Data Scientists, Senior Data Scientists, Artificial Intelligence Consultants and Machine Learning Managers.

Continue reading “10 Charts That Will Change Your Perspective On Artificial Intelligence’s Growth” »

Driverless vehicles could eliminate millions of jobs in the future, from cabbies to truckers to food delivery workers. But the companies that are hoping to hasten the adoption of this disruptive technology don’t want to seem callous to this brewing labor crisis, so they are joining forces to study the “human impact” of robot cars.

The Partnership for Transportation Innovation and Opportunity (PTIO) is a newly formed group comprised of most of the major companies that are building and testing on self-driving cars. This includes legacy automakers like Ford, Toyota, and Daimler; tech giants like Waymo (née Google), Uber, and Lyft; and logistics providers like FedEx and the American Trucking Association. The new organization is being formed as a 501©(6), which allows it to accept donations like a nonprofit and lobby government like a chamber of commerce.

But there’s a recent lesson worth learning from. Globalization and automation caused upheaval in the manufacturing industry from the 1980s through the early 2000s, and millions of factory workers lost their jobs. The disruption to communities is still being felt, and is arguably at the root of a lot of the biggest social and economic problems of this era.

Some big ideas are starting to percolate. But less dramatic ones might work, too.

NHS hospital bosses are debating a reform involving “widespread adoption of artificial intelligence” and “full automation”.

From diagnosis to recovery, machines could take on a range of jobs, a new report suggests.

Denis Campbell Health policy editor.

Continue reading “The robot will see you now: how AI could revolutionise NHS” »

Millions of low-skilled workers who are already being pushed out will need to adapt to the new economy.

I t’s an odd thing for someone to say about neurons: “Let’s see if anyone is awake.” And it’s an even odder thing to hear in a cavernous, half-furnished office suite where one whole room is occupied only by copy machines and a lonely foosball table.

Not far from that foosball table, Oshiorenoya Agabi and Benjamin Sadrian are sitting in a lab at their startup, Koniku, in Berkeley, California. Agabi founded the company, and Sadrian is a senior neuroscientist. They are toggling between a microscope and a screen full of blue graphs, looking for signs of activity in a cluster of neurons. Sadrian pauses as he scrolls through slightly fuzzy readouts on the screen, reminiscent of stock charts with buzz cuts. “I wish you’d come later, even tomorrow,” he sighs.

These readouts measure signals inside cells, and Agabi and Sadrian are looking for spikes that would show Koniku’s neurons reacting to a chemical Sadrian exposed them to moments ago. When we examined them under the microscope, they glowed a faint neon green, which indicates they’re starting to mature. A few tentative dendrites reached out into the void, the neurons just beginning to form connections with one another. But the telltale spikes don’t materialize on the screen. At just six days old, these neurons are still too young to do the jobs they’ve been engineered to do.

Continue reading “The Birth of Wetware” »

Artificial intelligence and automation stand poised to put millions out of work and make inequality even more pronounced. Is it possible to solve one problem with another?

There’s always a lot of talk about how AI will steal all our jobs and how machines will bring about the collapse of employment as we know it. It’s certainly hard to blame people for worrying with all the negative press around the issue.

But the reality is that AI is completely dependent on humans, and it appears as if it will stay that way for the foreseeable future. In fact, as AI grows as an industry and machine learning becomes more widely used, this will actually create a whole host of new jobs for people.

Let’s take a look at some of the roles humans currently play in the AI industry and the kind of jobs that will continue to be important in the future.

Continue reading “Introducing The Humans Behind Artificial Intelligence” »

So much talk about AI and robots taking our jobs. Well, guess what, it’s already happening and the rate of change will only increase. I estimate that about 5% of jobs have been automated — both blue collar manufacturing jobs, as well as, this time, low-level white collar jobs — think back office, paralegals, etc. There’s a thing called RPA, or Robot Process Automation, which is hollowing out back office jobs at an alarming rate, using rules based algorithms and expert systems. This will rapidly change with the introduction of deep learning algorithms into these “robot automation” systems, making them intelligent, capable of making intuitive decisions and therefore replacing more highly skilled and creative jobs. So if we’re on an exponential curve, and we’ve managed to automate around 5% of jobs in the past six years, say, and the doubling is every two years, that means by 2030, almost all jobs will be automated. Remember, the exponential math means 1, 2, 4, 8, 16, 32, 64, 100%, with the doubling every two years.

We are definitely going to need a basic income to prevent people (doctors, lawyers, drivers, teachers, scientists, manufacturers, craftsmen) from going homeless once their jobs are automated away. This will need to be worked out at the government level — the sooner the better, because exponentials have a habit of creeping up on people and then surprising society with the intensity and rapidity of the disruptive change they bring. I’m confident that humanity can and will rise to the challenges ahead, and it is well to remember that economics is driven by technology, not the other way around. Education, as usual, is definitely the key to meeting these challenges head on and in a fully informed way. My only concern is when governments will actually start taking this situation seriously enough to start taking bold action. There certainly is no time like the present.