An Experiment in Large-Scale Behavior Modification

“Everybody experiences far more than he understands.
Yet it is experience, rather than understanding, that influences behavior.”

— Marshall McLuhan

Tesla has implemented an unprecedented program designed to introduce a self-driving technology that emphasizes safety and control. For this program, more than 100,000 owners signed up to become eligible for Tesla’s software beta release. Eligibility was based on each driver’s performance over a minimum of 100 tested miles. 1 out of 10 drivers qualified and received the beta software version. Public-wide distribution will not occur until the software has been refined, fully tested, and deemed solid and foolproof.

At this moment, FSD (full self-driving) is rather like having a teenager with quick reflexes but limited distance-vision, driving your car for you. To improve that, Tesla intends to have as much data as can be safely tested, by as many people as can be deemed safe. In addition, many users have paid full price for the software, so there is a need to quickly refine and approve it in a timely fashion.

Tesla’s project is one of the largest systematic attempts to monitor and shape behavior in a public setting. It has elements of classic behavioral modification, albeit in a commercially-targeted project. It evaluates four specific driving behaviors, all of which affect your chance of being allowed to try the new software.

Based upon considerable driving data and accident reports, Tesla was able to identify these behaviors as being predictors of future accidents. That is not to say that these behaviors cause accidents, but simply that when these behaviors are present, there is an increased likelihood of a future accident, regardless of whether the driver is at fault or not.

One of these behaviors is the tendency to stop slowly, which may mean drifting into an intersection, or being too close to another car, situations where one might have to suddenly hit the brakes. A second qualifying behavior is to avoid vehicles by choosing routes that might be less occupied. Selecting quiet but fast country roads that, even if a little out of the way, may still afford a fast trip. A major limitation is the unpredictable situation, such as when service vehicles stop in the street, giving the FSD vechicle no alternative but to cross the no-cross lines. Interestingly, keeping well behind a vehicle ahead of you tempts other drivers to cut in to that space, introducing greater risk. The criteria also selects for location. Because of dense and unpredictable traffic, it is nearly impossible to get a good score driving in locations such as Manhattan or Los Angeles. So while traveling less busy roads is seen as a positive behavior, living in an urban area is considered a negative one.

Are these conditions fair? You might think: “I deserve the software, it’s not my fault if…” However, this behavioral assessment is not a case of fair or not. It is simply a method designed to scientifically avoid risk and ensure a best outcome; not to make people happy, nor to quickly issue FSD software. Given this tacit goal, all other considerations take second place. It is a case of regulation of allostasis, not homeostasis.

So, this evaluation process is an example of shaping spontaneous behavior by applying a specific set of reinforcements or inhibitors. It is not unlike any learning paradigm. It does, however, change how the brain works while driving. Rather than attending to many small adjustments and changes, the brain takes on a state of vigilance and stillness; focusing on readiness to move, not the movement itself. Research has shown that a brain in optimal rest is also in optimal readiness, evidenced by EEG testing as well as behavioral findings. That means drivers using the new FSD system will be making more SMR {??}, being more relaxed, and having a different type of symbiotic relationship with their vehicles. We have evolved from the horse to the car. The next evolution is to the car of the future.

According to my sources, 120,000 Tesla owners signed up for the beta trial. Initially about 12,000 people achieved a high enough score to get the software. So what of these 1 out of 10 drivers? What can we say about them? Well, they avoided sudden stops, did not turn too quickly, and did not follow other vehicles too closely. Do these conditions produce a safer driver? Experience shows that rigidly adhering to these requirements sometimes compromises safety. For example, avoiding sudden stops means that if a vehicle appears unexpectedly, the driver will hesitate to “slam on” the brakes, even if this is the best option.

Similarly, avoiding sharp turns results in spending extra time at intersections and roundabouts, causing following vehicles to slow down, and occasionally, issue a warning honk. Indeed, Teslas during this phase have gained a reputation for driving too slow, and for holding things up at intersections. Hardly a positive public image.

It was also reported that a driving student failed the driving test because he did not press the brake pedal in order to stop. A Tesla can be set to stop whenever the accelerator is not pressed, so using the brake pedal is unnecessary. However, the student had learned a habit that, while appropriate in the Tesla vehicle, did not conform to the world’s expectations. Clearly, there is learning both ways that will be required, both on the part of the driver and also on the part of the other vehicle’s driver, before self-driving becomes the norm.

What are the benefits of FSD?

When it is working well, I am sure that the driver will be making more SMR waves, being in a state of rest, but alert readiness. The driver learns to shift between manual and automatic control, in a smooth and effortless fashion, without deliberate thought.

One of the interesting effects of the beta trial, which is also true of neurofeedback, is that one simply becomes more aware of things they may not have noticed in the past. Whether you come to a full stop, how close you follow, how quickly you turn, these things are usually lost in the layers of automatic behavior that we don’t even think about. It is possible to drive for miles, with the mind elsewhere, and find oneself at the destination, not recalling the trip itself. With awareness comes the capacity to evaluate, and the capacity to change.

As it turns out, this trial is creating a fleet of drivers who — for better or for worse —share certain learned behaviors. This would have little impact were it not for the existence of other vehicles on the road. The effects of these changed driving habits are made more visible when there are unforeseen vehicles, or when other drivers must accommodate the new behavior of self-driving vehicles. It is a system of dynamics similar to social or family systems, in which changes in one component affect others.

We can learn a lot from this trial, above and beyond the question of how a technology innovator can interface with the public to improve software and deploy innovative functions. We can learn that as you select specific behaviors to reinforce, you may produce changes you did not anticipate. In neurofeedback, we choose specific EEG and biological signals to feed back to the subject, to learn what we hope to be: concentration, relaxation, focus, self-regulation, allostatic control, and so on. As we do this, we need to also be aware of other changes we may be producing; and how these changes serve the overall goals.

Neurofeedback, when put into an overall context of self-efficacy and neuroplasticity, can teach people to find their ways in and out of their mental and emotional situations, much the way a self-driving car can help you find your way to work, school, or wherever you need to go.

What is needed is to study drivers using different driving styles, and monitor their brain and biological signs. We did this very testing along with General Motors, in the Corvette Reverse Test Drive.

What we found was that the best drivers were calm, relaxed, and automatic in their actions; the way a driver should be, whether using manual, autopilot, or full self-driving.

It’s time to repeat this project with the Tesla team, and find out how advanced driving technology affects the driving experience at all levels.

We’re ready, if you are, to go deeper into what the new world of technology is doing for us, with us, and to us.

Tom Collura

 “The first step towards getting somewhere
is to decide you’re not going to stay where you are.”

— J.P. Morgan