Why Experts Get it So Wrong?

Experts get shocked when outcomes don't align with their underlying assumptions. It's even more troubling when this happens repeatedly.

For example, in July 2021, President Biden confidently appeared on TV to declare that it would take "years and years" of fighting for the Taliban to take over Kabul. Yet, just a few weeks later, the Taliban seized Kabul in only 24 hours without bloodshed. Similarly, experts at The New York Times predicted that Hillary Clinton would easily win the 2016 election, but the actual outcome was far from what they anticipated.

There are countless other instances where experts have completely missed the mark, which raises a critical question: Why do experts get it wrong so often?

The answer may be simple: confirmation bias at best; paid analysis at worst. Let’s stick to the former as I would need a separate article to comment on ‘intellectuals for hire’. Over time, experts become entrenched in certain data sets and theoretical frameworks that may have been true and relevant at one point but are utterly irrelevant in other contexts, especially during times of uncertainty and crisis. Moreover, with digitalization and decentralized power, the fundamentals of our reality have changed entirely.

This is why a PhD expert with 25 years of experience can be as ineffective as a blindfolded monkey throwing darts when predicting geopolitical outcomes. In fact, this was the conclusion of the infamous Princeton University study that compared stock market experts with blindfolded monkeys selecting stock portfolios.

As you might imagine, the monkeys outperformed the top stock market experts, much like random social media accounts are now often more credible and accurate in their analysis and predictions than so-called "seasoned" experts and journalists.

For the experts then, the future is clear: evolve or perish.