Denial & The Importance of Reflection

Denial is a phenomena where one refuses to acknowledge that their version of the world is inconsistent with reality.I’ve often felt that some people are in denial, and I’m certain many folks have felt I was in denial about numerous things. As a behavior, denial has always intrigued me, and reading “Phantoms in the brain” brought a lot of clarity to me.

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OBSERVATIONS OF DENIAL

Dr. Ramachandran describes experiments he conducted on patients who’s right side of the brain had suffered a stroke, resulting in paralysis of the left side of the body. Some of these patients showed acute symptoms of denial.

A lady who’s left arm was paralyzed claimed she could touch the doctor’s nose with her left hand. When asked about the motionless hand that lay on her left side, she would say that’s her brother’s arm. In another incident, a woman with who’s left arm was paralyzed claimed she could lift a table higher with her left arm than with her right arm. In one incident, a man with his left side of the body paralyzed accepted under pressure that he was misleading the doctor, but soon went back to his original view that his left arm was as strong as his right arm. In yet another observation, a perfectly intelligent man with a terminal brain tumor in a right side of the brain refused to acknowledge it entirely & labeled his physician as a malicious liar while focussing exclusively on a tiny sore on his face, asking that he be treated for this.
According to the author, these patients were perfectly intelligent. In fact, after 2 to 4 weeks, they started accepting that their left side was paralyzed. Interestingly, they believed that they were telling the truth about this paralysis all this while (also seen as revisionism for many of us). For the author, these patients were a great microcosm to understand the brain, as the symptoms of denial in them were very strong, and on very short time scales (think minutes to go from one belief system to another).

OUR BRAIN’S BELIEF SYSTEM

According to the book (rather, my understanding of the book), the left side of the brain observes the world, and takes in various stimuli. It then folds these actions into a world view or a belief system that already exists. For example, if I get my wife flowers, her left side of the brain will observe this and fold this action into a belief system that I love her, or that she deserves flowers, or whatever beliefs she holds. The left side of the brain is often considered “conservative” because it wants to fold every observation into the existing belief system.

The belief system itself is created & maintained by the right side of the brain. The right side of the brain decides whether the observation of the world & subsequent folding into the belief system, is consistent with its belief system. If it is not, the right side of the brain alters & at times, destroys the existing belief system and builds a new one that is consistent with the observations. In doing so, this part often checks the left side of the brain pushing back on inconsistencies. As a result, this part of the brain is called the “revolutionary” because it wants to throw away the prevalent belief system.

This belief system is important because it allows humans to act with some level of rationale & predictability. Absent of such a belief system, we would be rudderless as we won’t have any basis for action. However, if the belief system is not open to being destroyed & reconstructed based on observations, we will go mad because our observations of the world would be entirely inconsistent with the reality, & as a result, our actions based in our imagination.

In denial patients that the author describes, the part of the brain that destroys and rebuilds the belief system stops functioning for extended periods of time.

UNDERSTANDING DENIAL

As with these patients, many of us live in some state of denial at all times, and are generally unaware of it. This becomes easier to accept once we realize that our body image is part of this belief system. The extent of denial depends on how capable we are of destroying our belief system & rebuilding it based on new observations.
The manners in which denial manifests itself is interesting too. As Freud explained (though without any experiments & attributed to nonsense basis), it ranges from outright denial, to reaction formation (where we overcorrect for our inconsistent belief system like the woman who believed her paralyzed arm was stronger than her good arm) to projection (where we focus our action on something external to avoid the anxiety related with destroying the belief system). While we don’t fully understand the neurological basis for this, we have empirical observations that corroborate this.

WHAT DOES THIS MEAN FOR US?

Accepting that denial is a perfectly normal state of existence is the first step. Many of us unaware that it even exists. For example, a founder might not see that he or she is almost out of money, instead projecting that the business will turn around. Optimism for some, but a state of denial for others. See this tweetstorm from Sam Altman for instance, where he describes this state of mind.

In my view, to deal with this, we must always be open to, & keep, challenging our belief system. When we see something that doesn’t reconcile with our belief system, instead of blocking it out, or distorting it, it is important that we take time to develop other plausible belief systems deliberately where such an observation would be rational, and then seek alternative steps forward in terms of our actions. It is very likely that those other belief systems are delusional, but it is also entirely likely that our existing belief system is delusional.
The word we use today to describe this ability to ponder over our belief system is called “reflection”. A quality that allows us to reflect is “humility”. The character trait that gets in the way of “reflection” is over-confidence. Ongoing reflection allows us to build a belief system that is consistent with reality, though it requires constant & painful introspection. However, it allows us to act with greater predictability, and form a more representative world view

Applying machine learning to enterprise problems

There are many flavors of problems that machine learning can help solve, but I’m most interested in problems of decision making in the enterprise space. In order to help identify the right set of problems, I’ve built a simple framework that helps me gauge good problems.

Before I get into the framework, I should define what I mean by a good problem. A good problem, in this case, is one where solving it provides a step-change in the productivity of the enterprise while enabling humans to do what they excel at.

Length of feedback loop

Humans often get better at tasks when they receive instantaneous feedback. This allow us to form mental models, & predict the outcome of our actions. This is the essence of game play. In this feedback loop is longer than a few days, it is practically non-existent. This makes it impossible for humans to get better at the task, and they end up relying on “rules of thumb” to improve their decision making. Examples of these are sales & recruiting cycles, or performance feedback cycles that last several days to weeks & months. It is impossible for folks at the top of these funnels to improve their decisions based on feedback

In these scenarios, a machine learning based approach essentially incorporates the feedback by bringing insight from the bottom of the funnel to the top of the funnel, & augments human decision making.

Irregularity of environments

Even when rapid feedback is present, if the environment is irregular, it is impossible for human beings to improve their decision making. Most recruiting & sales situations have abundant examples of this. Prospect (or Candidate) Joe under circumstances A & B has high likelihood of closing, whereas if circumstance C is present along with A & B, that deal is a non-starter. These features are impossible to extract for humans, & even when extracted, they are difficult to identify, integrate, & maintain in day to day operation.

In such a scenario, a machine learning algorithm can extract features that can guide a sales rep or a recruiter in their decision making. Further, this machine learning algorithm stays current, is personalized, & integrated into the workflow of workers.

Length of decision-distance

I define decision-distance as the degrees of separation between the ideal decision maker & their proxy. For example, in recruiting the ideal decision maker is the hiring manager or a group of interviewers. However, sourcing is typically carried out by relatively junior recruiters who are not domain experts or come from a different industry. This separation leads to exasperation & waste due to poor decision making.

Here machine learning algorithms that are trained on successful data can bring real time insight of hiring managers (to stick with an example from recruiting) to recruiters who are looking for, and building relationships.

I believe that these 3 principles should be used to examine any decision making problems in order to identify if its a good application for machine learning.