Improvements in machine intelligence will not lead to runaway machine-led revolutions. They may change the kind of jobs that people do, but they will not spell the end of human existence. There will be no robo-apocalypse.
The emphasis of intelligence testing and computational approaches to intelligence has been on well-structured and formal problems. That is, problems that have a clear goal and a set number of possible solutions. But we humans are creative, irrational, and inconsistent.
Hardly a day goes by without a call for some kind of regulation of artificial intelligence, either because it is too stupid (for example, face recognition) or imminently too intelligent to be trusted.
But good policy requires a realistic view of what the actual capabilities of computers are and what they have the potential to become.
If all that is necessary for a machine learning system is to engage its analytic capabilities, then the machine is likely to exceed the capabilities of humans solving similar problems. Analytic problem solving is directly applicable to systems that gain their capabilities through optimization of a set of parameters.
On the other hand, if the problem requires divergent thinking, commonsense knowledge, or creativity, then computers will continue to lag behind humans for some time.
