As technology advances, a portion of our population cannot help but react with panic. Throughout our human history, as technology grows, so to has our fear as to where this technology will take us. This fear has taken hold through each and every stage of the industrial revolution. Fears such that, the alphabet will wipe away our memories, the telegraph will stop us from remembering how to write in full sentences. But the closer the technology resembles us humans, as in robotics and artificial intelligence, the greater is our fear. Yet if we build robots in the image that we wish for us to be, then the future of technology is sure to be an exciting one.
Computers can only answer questions posed by the humans who programmed them. So it is up to humans to ask the truly important questions. Is it possible for machines to make better decisions than humans? Several top tech company CEO’s have advised about the concerns they have about the singularity. But now there is a new idea, called the multiplicity, in which diverse groups of humans work together with diverse groups of machines, with the goal to ultimately be making the very best decisions. Computers and machines have the advantage over humans in their speed and precision. We rely on them in our everyday lives, with things like pace makers and auto pilot systems. And now many Institutions studying computer science are putting the emphasis on machines that can learn, when conducting their research. Recent research has shown that a group of machines is capable of making much better decisions than one machine making the decision by itself. There are millions of robots working in factories all over the world, yet we have none in our homes. This is because of Moravec’s Paradox, which is the idea that, what is very difficult for humans to do is very easy for robots, but what is very hard for robots to do, is very easy for humans. Outside of a factory, a robots function is uncertain. This uncertainty is very hard for robots to deal with. But robots can cope with this uncertainty by using spacial probability distributions, and statistical learning to maximize expected utility. But this requires enormous computation. Yet this can be resolved by using remote processors in the cloud, and it allows robots to share information, and as a result, the robots become smarter. This is referred to as Cloud Robotics.
As technology shifts from cloud computing, to social networks, to mobile networks, to data science and artificial intelligence, in which we moved from systems of record to systems of engagement, but none of these will remain in place unless they are trusted by the public.