What We Choose to Believe - The Power of Belief

How much do our beliefs color our perception of what is good or bad? What do we have to believe, especially about ourselves, just to survive another day?

In this era of Big Data ushered by Google’s brilliant algorithm designs, some of us are in awe, some are cautiously optimistic, and many are confused and uncomfortable. What are algorithms doing and how are they changing the world?

This question inspired a research publication from The Wharton School: “Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err”. The authors discussed their findings in a recent article: “Confidence Games: Why People Don’t Trust Machines to be Right --http://knowledge.wharton.upenn.edu/article/why-people-dont-trust-machines-to-be-right/ (Feb. 12, 2015)

This research may help explain why many people don’t trust science and the results of scientific experiments - on principle.

For those of us who believe in science, what we believe in is actually the practice of science. We are confident that the scientific process is a valid way of learning useful information. To laypeople, the purpose of science is to discover answers and practical solutions to problems. To scientists, especially academic researchers, their work is to ask deeper and more probing questions, to explore the unknown. The results of a good experiment, whether the original hypothesis is validated or not, lead to a succession of new questions and studies which will enrich the body of knowledge.

The conundrum comes with our expectations of science, and even rational logic, such as in software and algorithms. Scientists think in terms of probabilities. Laypeople want to believe in absolutes, because probabilities can be confusing. The nature of belief is certainty.

When your doctor tells you that you have a 40% chance of being alive five years from now because of a cancer tumor, what do you understand and believe?

Why do people buy lottery tickets, when the odds of winning are 1 in tens of millions? Do those people really believe they might win?

How much does what do we want to believe act as a filter that colors judgment? How consistently do we act on our beliefs? How well do our beliefs serve us?

From a practical mindset focused on answers and solutions, we expect rational logic (“science”) to be perfect and 100% correct all the time. Because this mindset is deterministic and judgmental, we want to distinguish between a “right answer” and a “wrong answer”. Right answers are good, everything else is bad. For answers based on probabilities, some will be “right” and some will be “wrong”, some of the time. We are disappointed because we didn’t get what we want – something we can clearly believe in. We blame the process for our confusion.

When gambling in a casino, even though we accept the fact that mathematics definitively proves that the casino will always win, eventually, we also see “spurts of luck” and experience those ourselves. Casino slot machines are even engineered to deliver occasional small payouts to entice customers to believe that luck is on their side and to keep playing.

The research at Wharton showed that many people prefer to trust their own judgment, rather than the results of an algorithm, even when presented with evidence showing the superiority of the algorithm over human judgment. The explanation is that we have much higher expectations of the perfectability of mathematics. On seeing evidence that an algorithm (or science) fails to provide a correct answer, we are much more distrustful of it than when we are faced with our own, human, fallibility.

This behavior is also central to the entrepreneurial mindset. Every day, entrepreneurs make decisions that are based, however loosely, on probabilistic estimates. The outcomes are rarely assured and often unknown. Could a startup be established purely on algorithms, on data-driven decision-making? Google, Facebook, and many others, are exploring this direction.

Entrepreneurs have a different perspective on risk, and it’s not all based on ego. They must embrace a fundamental paradox, to have a very strong sense of self-confidence, while having, at the same time, a very open mind to feedback from external sources. That feedback is essential for the entrepreneur and the venture to grow. The mindset of the entrepreneur is like a mental algorithm that wants to learn and improve as quickly as possible. The more data it can absorb, the better. Entrepreneurs must deal with belief in more complex dimensions than the rest of us because they are constantly struggling for survival. At least that is what they believe – as Andy Grove wrote in his book: “Only the Paranoid Survive”.