Back in the 1970s, the American people were told that fax machines would revolutionize the modern office and create oodles of leisure time. That never happened.
In the 1980s, we were told that personal computers would do so much repetitive and math work that we would have oodles of leisure time – and a paperless office.
Look around. Do you see any paperless offices? How about people lounging around with their feet up, enjoying the riches of a Brave New World operated by artificially intelligent machines? Nope.
The only folks sitting idle are jobless. And whether or not a machine performs a job formerly assigned to a human – say, sorting postal boxes by zip code onto conveyor belts – the person who used to do that job still needs an income to pay for food, housing, transportation, children’s education, and on and on.
McKinsey Global Institute concluded, after two years of study on “Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages,” that some occupations will almost no impact from AI competitors. In other sectors, job replacements could go as high as 30 percent.
The types of jobs at the most risk for automation are physical activities in “predictable environments” such as “operating machinery and preparing fast food.”
In an Orwellian twist of irony, low-income Americans are being recruited to teach smart machines how to take over tasks now performed by humans. A Texan company called Alegion is hiring disabled veterans to prepare information from old databases so that AIs can make sense of it.
Alegion is building its business on the old computer adage: “Garbage in, garbage out.” The corporate website puts it a bit more elegantly than that:
“Artificial Intelligence is only as good as the data used to train it. Alegion addresses the common challenges of building large-scale, custom training data sets.”
Companies like Alegion are enabling AI machines to do what is called deep learning. Basically, robots are being trained to take in and process data which is then used to make decisions, very much like humans do:
“Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Similarly to how we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome. We refer to ‘deep learning’ because the neural networks have various (deep) layers that enable learning. Just about any problem that requires ‘thought’ to figure out is a problem deep learning can learn to solve.”
Out-of-work disabled veterans on working on a defense contractor project (no alarm bells here) that entails labeling every type of vehicle – car, pickup truck, semi truck, or whatever – in aerial photographs. After an AI learns how to tell a Tesla from a tractor trailer, it could report on how many of them drove down a certain highway or parked in a specific lot.
International Data Corporation (IDC) is the “premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets.” IDC predicted that the AI industry will grow five-fold – quintuple – over the next three years.
Nathanial Gates, CEO of Alegion is telling the truth when he says, “We are employing people.” But those people are only getting paid minimum wage while their employers are getting rich quick. A Cornell University study found that “only 4% earned more than $7.25/hour” for Amazon Mechanical Turk jobs.
Amazon Mechanical Turk (MTurk) is “a crowdsourcing Internet marketplace enabling individuals and businesses (known as Requesters) to coordinate the use of human intelligence to perform tasks that computers are currently unable to do.”
Crowdsourcing is when a group of people works together to solve a problem. Wikipedia is the largest and best example of crowdsourcing today. Crowdworkers are all the people who contribute to a crowdsource.
Gates readily admitted that teaching AI machines how to process data as humans do is not the road to riches:
“This is supplemental income—people aren’t going to switch to a career of drone image tagging. But it is real work, and it can bridge the gap until they can receive skills and training to re-enter the workforce.”
Assuming, that is, that there is a workforce to re-enter.
Optimistically, Erik Brynjolfsson and Daniel Rock from MIT and Tom Mitchell from Carnegie Mellon University maintain that AIs will never fully replace humans because “few – if any – jobs can be fully automated using machine learning.”
This group of well-educated researchers believes that the following jobs are likely to be the first to phase out humans:
- Mechanical drafters
- Morticians, undertakers, and funeral directors
- Credit authorizers
- Brokerage clerks
These jobs, however, will be tough for AIs to master well enough to threaten employees’ job security:
- Massage therapists
- Animal scientists
- Public address system and other announcers
- Plasterers and stucco masons
Forbes reassures us that new AIs being developed in the U.S. and abroad pose no threat to workers because they will “replace tasks, not jobs.”
This positive outlook hinges on the assumption that the robots will assume boring tasks, leaving humans free to do “higher-level tasks.” Aren’t there enough people filling those higher-level jobs now? Experts say that new jobs will be created by AI replacements. They aren’t quite sure what those job descriptions will look like, though.
How far will this technology go in terms of stepping in to drive industry forward as employers kick out those unreliable, demanding, and high-priced human workers? Here’s one clue:
In China, the one nation that is on the verge of totalitarian control through a completely integrated digitized police state, the official news agency has trotted out a ” virtual newsreader sporting a sharp suit and a somewhat robotic voice.”
Employer Xinhua News bragged that their English-speaking announcer “can read texts as naturally as a professional news anchor.” Even if that is a bit of an exaggeration today, this is China’s goal: to fabricate public-facing robots that ultimately will be indistinguishable from a human being.
Xinhua is delighted with their new robotic AI because it can operate (“work”) round-the-clock, never getting tired, never talking back, never gossiping at the water cooler, never asking for a raise, and never having an original idea.
If that doesn’t give you the creeps, perhaps you are an AI?