Your Lizard Brain Triune And How It Shapes Driverless Car Software Design

Dr. Lance Eliot, AI Insider

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When I was a youngster, some of my playmates would hurl a verbal insult at one other by saying that the person was a lizard brain.

I don’t believe that the same taunt of being referred to as a lizard brain is used much anymore and it has ultimately gone by the wayside as a toss-able insult for kids.

Background About Our Triune Brain

There was a kind of scientific revival of referring to a lizard or reptilian brain in the 1990’s when a book by Paul MacLean came out, known today as a now-classic entitled “The Triune Brain in Evolution.”

The triune brain theory postulates that the human brain physically evolved over time and consists of three separate parts. Presumably, evolution of the brain over time coincides with the rise of humanity and the bolstering of our thinking processes.

The three parts are united in that they ultimately work together in various fashions to undertake human thinking. Though there is a united aspect, they are nonetheless considered distinctive in their own right each.

This notion of having three separable and distinct functions might be likened to certain aspects of a car. If I had a car engine in front of us, I might tell you that one part has to do with the generating of thrust that is used to propel the car, and there is also a part or segment for keeping the engine cool by the use of liquid or air, and a third part or potion that lubricates the engine. That’s a triune.

In the case of the triune brain theory, the three proposed portions are named as follows:

  • Reptilian portion (also known as the Lizard Brain)
  • Paleomammalian portion (also known as the Limbic System)
  • Neomammalian portion (also known as the so-called Thinking Brain)

In the triune theory, the lizard or repilitian portion of the brain has to do with your instincts. It includes brain elements that are often described as the brainstem and the striatum (also known as the basal ganglia or nuclei). In a manner of speaking, you could say it is the “blockhead” part of the brain that does the simplest and least thoughtful kinds of thinking efforts.

Fight-or-flight response is undertaken by the Reptilian portion of your brain. It has your core instinctive capabilities.

The paleomammalian portion of your brain is said to consist of higher levels of thinking capabilities, including your emotions, your overall memory storage and access, your behavioral fundamentals such as parenting behavior and reproductive behavior.

The neomammalian segment of your brain is the higher-level thinking element of your mind. With this portion, you are able to think in abstract ways, you can communicate using language, you can mentally craft plans and carry them out.

Three Minds In One Mind But Not Of One Mind Necessarily

When I mentioned that the triune theory postulates that the three portions are united, I was not stating that they are always in agreement. They might be diametrically opposed to each other.

At any point in time, any of the three portions might prevail in terms of shaping your thinking and your efforts. There can be a lack of balance in the sense that one prevails, or two prevail, over the other portion or portions.

They could also all three be perfectly aligned.

I’m sure you seen people say that they hear voices in their head. Assuming that you aren’t mentally deranged, it could be that you are somehow able to sense or realize the debate among the three portions of your triune brain.

This then brings us too to the matter of whether you buy into the triune brain theory.

Some would say that the theory was handy at the time that it was being proposed. It helped us to get our hands around the vast complexities of the human brain. It sparked discussion and research into the biologically mechanical and chemical inner workings of the brain. For a slew of good reasons, the theory was helpful.

There are now some that argue the triune brain theory is a grossly oversimplified way of modeling the brain.

On the oversimplification criticism, it might also be oversimplified to postulate that there are only say three to five major portions. Perhaps there are a dozen. Maybe there are a hundred major portions. Why does the brain need to be only a small number of major portions? That’s just a means to make things simpler for us to grasp what it is, but this doesn’t necessarily need to be the reality of how the brain actually is structured.

Comparative Neuroanatomy Is Included

If you could come up with a competing theory that says the brain has five major portions, it will right away be questioned as to how or why the brain has five major portions. What is the cause for this structure? What justifies it?

In the triune theory, we get the nicely with-a-bow-wrapped aspect that the three each evolved over time. They progressively got us toward greater and greater levels of thinking. Each portion has its own set of thinking-like elements.

If you examine the “evolution” of the triune brain theory, much of it arises from research in comparative neuroanatomy.

Comparative neuroanatomy is an approach to studying the brain that says we might be able to figure out the human brain by comparing it to the brains of other animals.

By doing a comparison and a contrasting of human brains versus animal brains, we can perhaps discover what we have that they don’t, and this added piece might be the final piece in the puzzle that makes us thinker and humans.

AI And The Triune Brain

This now takes us into the realm of Artificial Intelligence (AI).

One of the most vocal debates about trying to create automation that exhibits intelligent behavior is whether you need to first know how the human brain physically works, or whether you can skip that aspect and just aim at the behaviors that emerge out of thinking humans.

The triune brain theory attempts to cover both the physical inner workings of the brain and also commingle that with the resulting thinking behaviors that arise from the brain. Some might say you aren’t going to get to unlock both. Trying to get both the inner aspects and the outer aspects figured out might be too much. You are biting off more than you can chew.

For those that are developing Deep Learning systems and using artificial neural networks, particularly the use of deep or large-scale neural networks, it might be suggested they are trying to go the route of the inner workings of the brain. They seem to assume that if you amass enough of the linchpins of what the brain seems to be composed of, voila there will be intelligence that emerges from the spaghetti.

There are some that assert we are not doing enough of a “comparative neuroanatomy” within the realm of artificial neural networks. Generally, nearly all of the neural networks being done on a large-scale basis are not being done in a manner that allows a comparison and contrasting between them. Each is its own one-off. Each is often hidden from other researchers and not revealed so that others can see what it is composed of.

AI Self-Driving Driverless Autonomous Cars

What does this have to do with AI self-driving driverless autonomous cars?

At the Cybernetic AI Self-Driving Car Institute, we are developing AI software for self-driving cars. One interesting aspect involves whether the triune brain theory can be applied to the AI systems being developed for AI self-driving cars. We believe so.

Returning to the topic of the triune brain theory, let’s consider how this relates to AI and the advent of AI self-driving cars.

The first aspect involves whether the AI of self-driving cars should be based on a primarily brain-based underlying structure, vis-à-vis Deep Learning and large-scale neural networks, or whether it should be based on a symbolistic approach of focusing on artificial intelligence that is exhibited in human driving behavior.

I earlier described that there is an ongoing and vocal debate about which of those two approaches is the sounder and more likely to get us toward true AI.

Currently, other than the use of Deep Learning and deep neural networks in the sensory data portion of an AI self-driving car, there is actually not a significant amount of the AI in an AI self-driving car that is shaped around the notion of a brain-based kind of structure.

For now, the prevailing Version 1.0 of AI self-driving cars is going to be based on a more programmatic construct, and we’ll have to wait and see how well this pans out, plus it could be that the Version 2.0 of AI self-driving cars swings further into the brain-based kind of structures, especially as that neural network style approach further evolves to become more robust.

The second aspect to consider is the notion of comparative neuroanatomy. I had earlier mentioned that there is relatively scant comparison and contrasting going on in the development of Deep Learning and large-scale neural networks. Developments tend to be proprietary and not provided for wide open analyses and comparisons.

The same kind of proprietary and shall we say secretive approach is being used by the auto makers and the tech firms that are crafting the AI for self-driving cars. There is no readily available means to do any kind of comparison or contrasting of the numerous underway AI self-driving car efforts, other than to try and examine any outward metrics such as number of miles driven and number of disengagements, though these are woeful metrics for doing any under-the-hood assessments and comparisons.

Autonomous Cars And The Triune Brain

Let’s shift our attention now toward the triune brain theory and its claim of three major portions of the human brain.

Recall, it is three portions, each separate, yet also united in their efforts, and are presumably based on evolution over time, encompassing becoming more elevated in terms of increasing levels of thinking capabilities.

As far as I know, there aren’t any similar triune type of efforts underway by the auto makers or tech firms in terms of how they have opted to organize or structure their AI systems for their self-driving cars. In that sense, there isn’t the use of a “three major portions” to the AI systems of self-driving cars.

The point being that rather than being overly constrained to a limited set of major systems or subsystems, and then hanging everything else off of those structures, there tends to be a more organic and sprawling structure to the AI systems of many self-driving cars underway.

Let’s consider another element of the triune brain theory and see how it applies to AI self-driving cars.

One crucial aspect is that the three major portions of the brain are separate and yet united. They work together, though this does not mean they necessarily get along.

This is definitely an aspect to be wary about the AI systems of self-driving cars. With the perhaps overly complex nature of the AI systems and subsystems in a self-driving car, in theory they are working separately and yet are united. The united aspect tends to be shaped around a centralized controller.

Sadly, there are some AI developers and AI self-driving cars that have not yet vetted the numerous points of contention between the complex sprawl of AI systems and subsystems in their self-driving car.

This means that you might have an image processing portion that examines a camera image or video stream in real-time and determines that the road ahead is clear, and meanwhile the radar processing portion determines that there might be a truck or similar large object crossing the road ahead of the in-motion self-driving car. Some believe this might have been a factor for example in the real-world case of the Tesla in Florida that ended-up in a deadly crash.

Being Fast Is Important

Another interesting aspect of the triune brain theory consists of the notion that the Reptilian portion is likely to react more quickly than the other portions. It’s the gut instinctive reaction mechanism.

This can be welcomed when you are faced with a rapidly emerging situation for which there might not be time to think things through. Merely reacting upon impulse might be the difference between making it out of a dire situation versus not.

We can leverage that notion into the design of AI self-driving cars.

One of the biggest issues confronting an AI self-driving is the time factor. The AI system must be continually watching the clock.

A car that’s in-motion at 65 miles per hour has a limited amount of time to decide what action to take. The AI cannot meander or ponder excessively a myriad of options.

With the self-driving car in-motion and when complicated by other nearby cars also in motion, the timing of figuring out what to do must be relatively fast. Options as to maneuvers of the self-driving car will only be possible in short windows of time. The longer the AI goes to try and identify what to do, the odds are that the number of available and viable avenues of safety are going to be reduced.

I refer to this timing matter as the “cognition timing” of the AI self-driving car. This is a real-time system and therefore must be battling the clock at every moment. When the Uber self-driving car incident occurred in Phoenix, I had right away predicted that it might be partially due to an internal timing aspect, and it turns out that I was right. Time is king in an AI system and subsystems of a self-driving car.

Wrapping It All Up

Pulling together then the triune brain theory model with the need for fast processing by the AI of a self-driving car, we are advocates of an approach of having a kind of Reptilian portion of the AI system for a self-driving car.

Here’s what we mean by this Reptilian metaphor.

There should be a core aspect of the overall AI system that acts like an instinctive portion. It is relatively stripped down in comparison to the full-blown and likely overly complex entire AI system and subsystems of the self-driving car. This tightly woven and smaller core is the last-man-standing if the clock has run out of time and something needs to be done.

The overarching AI system might get itself tied into a knot and not be able to pull out its head in time to realize that something must be done about the control of the self-driving car. In a circumstance whereby the self-driving car has gotten into a dire situation, the default of inaction because the AI overall system has gotten itself bogged down would seem undesirable as an approach.

In lieu of the overarching AI being able to proceed, the core or instinctive portion would step into the matter. Due to being stripped down, it is built and has been tested to be fast, very fast. As needed, it would issue car controls commands of a fundamental nature to try and save the day.

I’d like to emphasize that this is a last-resort option. The core is simplistic. It does not have the means to make the more robust kinds of decisions that the fuller AI system and its array of subsystems does. The instinctive choices it makes can be the wrong choices. We’re focusing herein on the difference between making no choice, assuming that the fuller AI has not been able to reach a conclusion of what to do, and making some choice, though albeit one that is off-the-cuff.

Therefore, the Reptilian gets back onto the table as a last-resort option.

Of course, this is not so easy to build and nor to invoke.

What portion of the AI system and subsystems will decide that the Reptilian core should be invoked? It could be a Catch-22. The overall AI system is so hopelessly engrained in what it is doing that it fails to realize the clock is out-of-time and therefore fails to hand the reins over to the Reptilian core. In that case, the Reptilian was there, but not invoked, and it is a sad day that the very contingency put in place had no chance to kick into gear.

If you say that the Reptilian-core can invoke itself, which presumably is how the triune brain theory postulates that things happen, we are then faced with a different kind of problem. Let’s suppose the neomammalian portion of the AI system is doing its thinking thing, and the Reptilian-core will activate when say the clock is reaching a preset time threshold of a countdown.

Okay, so the overarching AI system is trying to consider a myriad of options and examining the sensory data and the rest. The time threshold is reached. The Reptilian-core leaps to life. It does a rapid analysis and decides that the brakes should be stomped upon, doing so by immediately issuing a full-stop command to the braking system of the car.

The real twist that I was trying to take you toward was the notion that it could be that the Reptilian gets invoked, due to the time threshold countdown, and while the Reptilian is deciding what to do, the neomammalian portion of the AI system and subsystem finishes figuring out what to do. The thinking portion says to push full throttle and accelerate out of the crisis. The Reptilian says to hit full brake and come to an immediate halt.

Conclusion

The triune brain theory is fascinating and provides much food-for-thought about how we humans seem to be able to think.

It has been a useful pair of glasses in which to see the world of the mind and attempt to investigate it.

The simplicity has wide appeal and makes the theory accessible to the public and to those steeped into the science of the brain.

For free podcast of this story, visit: http://ai-selfdriving-cars.libsyn.com/website

The podcasts are also available on Spotify, iTunes, iHeartRadio, etc.

More info about AI self-driving cars, see: www.ai-selfdriving-cars.guru

To follow Lance Eliot on Twitter: @LanceEliot

For his Forbes.com blog, see: https://forbes.com/sites/lanceeliot/

For his Medium blog, see: https://medium.com/@lance.eliot

For Dr. Eliot’s books, see: https://www.amazon.com/author/lanceeliot

Copyright © 2019 Dr. Lance B. Eliot

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Dr. Lance B. Eliot is a renowned global expert on AI, Stanford Fellow at Stanford University, was a professor at USC, headed an AI Lab, top exec at a major VC.

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