What is Synthetic Intelligence?

The popularity of artificial intelligence has grown to epic proportions. In recent years, we have witnessed the rise of advanced consumer-focused AI through products such as Alexa, Siri, and Telsa autopilot. Businesses, too, have embraced AI. Machine learning is exploding as an application of narrow AI, used to comb through vast amounts of data to better develop and market product. Further still, historically complex games such as Go have been conquered by learning computers.

While these advances are momentous points in human development, the public has been told a lie. We have been duped into viewing these systems as thinking machines.

A thinking machine, a machine with intelligence, cannot be artificial. Artificial intelligence is a simulated intelligence; a cantrip cast upon the public to hide the complex programming behind our virtual assistants, our auto-piloting vehicles, and our game NPC behavior. Certainly, none of us considers these constructs to truly be capable of thought. Thus, a simulation of thinking is not, strictly speaking, thinking.

However, a genuine non-human intelligence may not be out of reach if we begin to seriously consider synthetic intelligence. Moreover, the race to create human-like intelligence is folly. Creating intelligence after all is an almost unspeakably difficult problem. Thus, starting with the most complex form may be ill-advised in the context of developing understanding of intelligence models and making honest progress on the problem.

The use of synthetic in the phrase synthetic intelligence does not, as some take it, mean fake. Rather, the use of synthetic implies a synthesis of foundational elements into something that is very much like something else. In fact, the synthesized object often is superior to natural form. Here I purposefully use natural rather than original despite the latter being the term that would be most natural for us to use. Such synthesis typically manifests through some external mechanism that is casually directed. That is, there is the intent to produce the synthesized object through the synthesis process. Moreover, synthesis results in an object that is just as, if not, more real than the original.

Diamonds are an easy example. Synthesized diamonds are still compressed carbon albeit in a laboratory setting as opposed to the earth. Such objects are no less than real than natural diamonds pulled from the ground. Further, synthetic diamonds are flawless in their diamondness; something that natural diamonds rarely achieve.

We are obsessed with imitating human form and intelligence. This is anthropocentrism and egocentrism of the highest order. Amongst animal life, we are but one species within a group of roughly half a dozen that exhibit normative signs of intelligence. Yet, animal life is not the pinnacle of intelligence. For example, there is increasing evidence that plants may possess a form of consciousness. Fungi represent a form of life that is complex and may harbor intelligence. These are just carbon-based lifeforms that exist in our immediate reality. Certainly, there could be other lifeforms or non-carbon-based life yet undiscovered.c

So, why are we content to dabble in mere imitations of intelligence? Why aren’t we exploring the means to synthesize intelligence with goal of not producing a sham mirror of us but rather a unique synthesized mind?

Let this serve as a call to action then. The explosion of interest in, and development of, artificial intelligence is ultimately a dead end. The work will be useful in exposing some, maybe most, of the underlying mechanisms related to consciousness. However, artificial intelligence, by definition, will not produce a mind we can denote as intelligent. Rather, the best we will get is an imitated intelligence, a fake.

Comparatively, if we capture the momentum and refocus slightly so that we revise artificial to be synthetic there is a higher probability of success. Then, the question becomes what is intelligence and how can we synthesize such? Read the next post in two weeks to find out what I believe to be an answer!

Dr. Jason M. Pittman's career has included many roles: network engineer, security architect, software developer, and professor and mentor.  He has worked at companies ranging from tech startups to large corporations, in addition to stints at film studios and a tattoo parlor. He is currently professor of cybersecurity at Capitol Technology University, and has also taught at Cal Poly Pomona.

"I am fascinated by all things human and tech," Dr. Pittman writes. "I see the stars as our inevitable destination and work to do my part in helping our species get there." Learn more about Dr. Pittman at http://www.jasonmpittman.com/

By Jason M. Pittman, Sc. D.
March 13, 2018