Humans might not always make the best decisions, but algorithms can

We are faced with thousands of decisions every day with an infinite number of possible outcomes. In light of this, you would think that we would be expert decision makers. However, thanks to many of our thought processes, this isn’t always the case.

Firstly, the stress produced when making decision can impede our ability to think clearly. Most humans are very risk averse, which means we place extra focus on avoiding choices which result in regret. This deep set fear of making the wrong choice can influence our brain activity, especially in the medial orbitofrontal region, the anterior cingulate cortex and the hippocampus, the areas which manage emotions and emotion-related memories in the brain.

We can look at a real life example such as playing poker to highlight this type of thought process. If you are playing a game of poker where all players are gambling with valueless matchsticks instead of chips that actually represent thousands of dollars, you are more likely to be calmer and more rational. Essentially, when we gamble with lower stake our brain is less alarmed, allowing better judgment.

Not only are our thought processes muddled with emotion and past experiences, we can also be very poor at considering statistical facts. Double-counting base rates is a prime example of how we can overestimate or underestimate the chance of danger. For example, if a doctor informs a non-smoking, slightly overweight 50-year-old he has an 8% chance of having a heart attack, the patient may think, “Well, I don’t smoke, so it’s probably less for me.” The only problem is that the 8% already takes that into account. Unlike calculators, we do not consider statistics in such a rigid manner.

So how do computer’s decision making processes differ from that of humans? This is a concept best explained by Tom Griffiths, Ph.D., professor of psychology and director of the Computational Cognitive Science Lab at the University of California, Berkeley, and the co author of Algorithms to Live By.

During an interview with berkeleywellness.com, he states that “Computers offer a different way of thinking about rational decision-making. Intuitively, we feel like we should weigh all the options to make a rational decision. But when computers try to solve the kind of difficult problems that people face, that’s not what they do.”

He adds “The computer isn’t going to consider all possible solutions because there are too many to look at. It’s not going to carefully evaluate each one. And it’s not necessarily going to produce the same answer each time. Both computers and humans have to make decisions with a finite amount of time and computational resources.”

One company that has utilized the intelligent processing abilities of algorithms is Paypie. Risk score analysis is central to many major industries within the financial sector, such as financing, compliance, auditing, credit insurance, and review. The market is colossal and nearly all SMEs are subject to a risk score check at some point in time. Even though it is incredibly large, the risk score market for business is riddled with discrepancies and inconsistencies that create a serious problem for the third parties vetting them. Fraud and data manipulation are two of the biggest issues in this area.

Paypie aims to bring a solid answer to the uncertainty of this imperfect system by using its unique risk algorithm. This algorithm is based on blockchain triple entry accounting, which provides certainty that the risk score is accurate and fraud proof.  

We can put a man on the moon and we can send a message from one side of the word  to the other in seconds, but no matter how much we achieve we are still inherently flawed beings which is evident in our emotionally influenced, illogical decisions frequently made. However, while we may not be the smartest decision makers, we are smart enough to create algorithms which can do the hard work for us.