Why Do We Make the Wrong Choice Even When We Know Better?

Billy Odell Tucker-Robinson Founder & Host — Banking With Billy Network • Intelligence Network • Data Science • AI Research • World News
Published: 2026-10-06T17:15:35.550Z • Permanent link

Netflix, the US-based streaming giant, recently revealed that it had made over 1,500 changes to its recommendation algorithm in 2022 alone. The move was seen as a significant step towards improving the accuracy of its personalized suggestions, which are a key driver of user engagement. However, the company's efforts to refine its algorithm were hindered by a surprising finding: users continued to make irrational choices, even when they had access to the best possible information.

Netflix's struggles to crack the code of human decision-making are not unique. Research has shown that our brains are wired to prioritize short-term gains over long-term benefits, and that we often fail to consider the full implications of our choices. This phenomenon, known as the "IKEA effect," refers to the tendency to overvalue things that we have invested time and effort into, even if they are not necessarily the best choice. In the case of Netflix, users were found to be more likely to continue watching a show they had already invested in, even if it was no longer engaging, simply because they had already spent time and emotional energy on it.

One of the key individuals driving this research is Dr. Sheena Iyengar, a professor of social psychology at the University of Michigan. Her work has shown that our brains are highly susceptible to biases and heuristics, which can lead us to make irrational choices. In the context of Netflix, Dr. Iyengar's research suggests that the company's algorithm is not the only factor at play. Users' emotional connections to the shows they watch, as well as their social connections with others who are also watching, play a significant role in shaping their viewing habits.

Netflix's struggles to crack the code of human decision-making have significant implications for the social and behavioral sciences. Companies like Netflix, which rely heavily on data-driven decision-making, are increasingly dependent on understanding human behavior in order to stay ahead of the competition. However, the fact that users continue to make irrational choices, even when they have access to the best possible information, highlights the limitations of data-driven approaches.

For example, a recent study by the Harvard Business Review found that companies that rely heavily on data-driven decision-making are more likely to experience cognitive dissonance, or feelings of discomfort, when their assumptions are challenged. This can lead to a range of negative consequences, including decreased employee morale and reduced innovation. In the context of Netflix, this means that the company's efforts to refine its algorithm may be hindered by the very same biases and heuristics that it is trying to overcome.

The struggles of Netflix to crack the code of human decision-making are part of a larger pattern. The rise of big data and artificial intelligence has led to a growing recognition of the limitations of data-driven approaches. In recent years, there has been a growing trend towards more nuanced and contextualized approaches to decision-making, which take into account the complex interplay between data, human behavior, and social context.