Is rationality real?

In financial markets where standard and divisible instruments are traded, it has been shown that rational outcomes are more likely. Even though individuals act irrationally most of the time, the aggregation of individuals, markets in general, tend toward rational outcomes. It appears that this is unlikely to be true in real markets. In a recent experiment in the US, three entities - one from radio, one from TV and one from a powerful position, have been able to create irrational responses from a very large population - perhaps as much as 50 million. All the "broadcasters," had to do is to repeat incorrect information over and over again. This has broad implications for rationality, policy and the future of humanity.

Rationality is not real in non-financial markets. Humans tend to clump, perhaps an evolutionary trait that kept small clans together. Early in homo-sapien progression, identifying and protecting the clan was dominant. Although early humans used more sophisticated attributes, the modern variety seems to have fallen into using surface heuristics such as the color of the skin, eyes, and hair. The fundamental reason three loudspeakers could lead a large population down an irrational rabbit hole is that they used ideas from hundreds of thousands of years ago. This is not something the "intellectuals," understand. It is not that there aren't rational solutions to the problems we face but rather if such choices align with the human brain created much before modern times. 

Real markets cannot assume rationality. Anybody who assumes rationality exists and design campaigns around that is bound to fail.

Next wave of Artificial Intelligence

As Artificial Intelligence matures over half a century, we may be fast approaching the limits of independent developments in software and hardware. Consulting companies seem to have embraced "data science," an ill-conceived and confusing area. Hardware companies, pressured to sell Silicon at any cost, have been creating Pizza sized "smart boxes." and "cognitive networks.". Not to be left behind, companies that specialize in "IoT," things that are on the internet, have been struggling to define how they are different. All of these, aided by massive hype, will likely destroy shareholder value in many ways.

There are two important avenues to make progress in this area. First, the hype created by consulting companies has to be tempered - data scientists do not add value, they typically destroy it. R and Python do not automatically add any value if the users of these somewhat obsolete tools do not understand the problem they are trying to solve. Most of the "new math," has been around for many decades, it is just that fast and cheap computers now have made the incompetent look smart.

It is time to focus on the assimilation of hardware and software to move the field forward. Lack of a theory of consciousness automatically means that humans are better off abandoning the idea of "modeling," the brain. However, we could learn a lot from observing the brain - it is an efficient learning system that gets tired and ages over time. No machine based on conventional computing architecture exhibits these qualities. This means that it is futile to throw more Silicon to a foreign design in an effort to make it act like the brain. In other words, intelligence is never artificial.

Human intelligence, albeit impressive, cannot be the end game. The inability of individual specimens to form a network has substantially restricted their ability to advance. So, replicating the human brain in silicon is not a good idea both because contemporary designs do not allow consciousness and the lack of network capabilities disallow scaling.

It's time software and hardware came together to advance AI.