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.
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.
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.
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.
Japan’s labor force do not mind robots in factories because they’re seen as a source of help, Japanese Deputy Prime Minister and Minister of Finance Taro Aso said in a panel discussion at the Asian Development Bank’s annual gathering in Manila.
Unlike many of their Western counterparts, Japanese workers aren’t afraid of robots stealing their jobs, a top-ranking official from the country said Friday.
Will they teach humanities?
Some experts have suggested that autonomous systems will replace us in jobs for which humans are unsuited anyway — those that are dull, dirty, and dangerous. That’s already happening. Robots clean nuclear disaster sites and work construction jobs. Desk jobs aren’t immune to the robot takeover, however — machines are replacing finance experts, outperforming doctors, and competing with advertising masterminds.
The unique demands placed on primary and secondary school teachers make this position different from many other jobs at risk of automation. Students all learn differently, and a good teacher must attempt to deliver lessons in a way that resonates with every child in the classroom. Some students may have behavioral or psychological problems that inhibit or complicate that process. Others may have parents who are too involved, or not involved enough, in their education. Effective teachers must be able to navigate these many hurdles while satisfying often-changing curriculum requirements.
In short, the job demands that teachers have nearly superhuman levels of empathy, grit, and organization. Creating robotic teachers that can meet all these demands might be challenging, but in the end, could these AI-enhanced entities solve our most pervasive and systemic issues in education?