5. Machines Will Take Our Jobs
No doubt, machines will take over our jobs one day. However, what we don’t realize is when they will take over, and to what extent? Well, as we’re about to find out, it’s to a large extent.
According to top consultancy and auditing firm PricewaterhouseCoopers (PwC), robots will take over 21 percent of the jobs in Japan, 30 percent of jobs in the United Kingdom, 35 percent of jobs in Germany, and 38 percent of jobs in the United States by the year 2030. By the next century, they will have taken over more than half of the jobs available to humans.
The most affected sector will be transportation and storage, where 56 percent of the workforce will be machines. This is followed by the manufacturing and retail sectors, where machines will take over 46 and 44 percent of all available jobs.
Talking about “when,” it is speculated that machines will be driving trucks by 2027 and manning retail stores by 2031. By 2049, they’ll be writing books, and by 2053, they’ll be performing surgery. Only few professions will be free of the machine incursion. One is the role of a church minister, which would remain free not because a machine can’t run a church but because most people won’t approve of being preached to by a robot.
4. Robots Have Learned To Be Deceitful
In human-style fashion, robots are learning to be deceitful. In one experiment, researchers at the Georgia Institute of Technology in Atlanta developed an algorithm that allowed robots to decide whether or not to deceive other humans or robots. If the robots decided to take the route of deceit, the researchers included an algorithm to allow the robot decide how to deceive the people and robots while reducing the likelihood that the person or robot being deceived will ever find out.
In the experiment, a robot was given some resources to guard. It frequently checked on the resources but started visiting false locations whenever it detected the presence of another robot in the area. This experiment was sponsored by the United States Office for Naval Research, which means it might have military applications. Robots guarding military supplies could change their patrol routes if they noticed they were being watched by enemy forces.
In another experiment, this time at the Ecole Polytechnique Federale of Lausanne in Switzerland, scientists created 1,000 robots and divided them into ten groups. The robots were required to look for a “good resource” in a designated area, while they avoided hanging around a “bad resource.” Each robot had a blue light, which it flashed to attract other members of its group whenever it found the good resource. The best 200 robots were taken from this first experiment, and their algorithms were “crossbred” to create a new generation of robots.
The robots improved on finding the good resource. However, this led to congestion as other robots crowded around the prize. In fact, things got so bad that the robot that found the resource was sometimes pushed away from its find. 500 generations later, the robots learned to keep their lights off whenever they found the good resource. This was to prevent congestion and the likelihood that they would be sent away if other members of the group joined them. At the same time, other robots evolved to find the lying robots by seeking areas where robots converged with their lights off, which is the exact opposite of what they were programmed to do.
3. The AI Market Is Being Monopolized
The AI market is being monopolized. Bigger companies are buying smaller AI startups at an alarming rate. With the current trend, we would end up with AI that is controlled by a very small number of corporations. As of October 2016, reports indicated that companies like Apple, Facebook, Intel, Twitter, Samsung, and Google had purchased 140 artificial intelligence businesses over five years.
In the first three months of 2017, big tech companies bought 34 AI startups. Worse, they’re also paying huge bucks to hire the top scholars in the field of artificial intelligence. If this remains unchecked, you can guess where we’re heading.