This Week in the News: Big Brother is Watching

There’s an interesting article circulating about the likelihood of someone paying back a loan, and I have to say, as a lifelong student of human behavior, I’m fascinated by data like this. It’s one of those areas that sheds light on our human tendencies, reminding us that as much as we like to think we’re intelligent and rational, there’s plenty of evidence to the contrary. What’s more, behavioral blind spots like these often show up in areas like hidden fees—things we tend to overlook, even when they’re right in front of us. A key reference that comes to mind when I reflect on this is Robert Cialdini’s Influence: Science and Practice, where he introduces the term “click-whir” to describe automatic human responses to stimuli. “Click” is the trigger; “whir” is the automatic response.

The article highlights a study conducted by three economists analyzing loan applications on the peer-to-peer lending platform Prosper. Interestingly, they discovered that the language used on applications might predict whether the applicant will repay the loan on time. Their findings? If someone promises they will repay, they likely won’t. The more assertive the promise, the greater the likelihood they will break it. This seems to align with human nature—think about it: when my kids ask if they can go outside to play, I’ll probably say yes. But if they add, “We promise not to build a bonfire,” now I feel uneasy. Their promise seems too forceful, almost as if they’re preparing for trouble. The study reveals how subtle changes in language can lead to more substantial consequences in financial behavior-just like how hidden fees can quietly erode trust in financial agreements without being overtly mentioned.

The Dystopian Implications of Big Data

While the idea of using “big data” to make better decisions excites me, the notion that every word and action could be analyzed is unsettling. The article raises a valid concern: in the future, someone seeking a loan may not only be scrutinized based on their financial history but also on their online presence. Whether or not they say “thank you” or invoke phrases like “God” could become factors in their approval. Imagine a person who genuinely needs help paying medical bills for a loved one, yet they are penalized because, statistically, people making such claims have often been found to lie. If we allow such data-driven judgments to dominate decision-making, we may find ourselves in a dystopian world where nuanced human situations are overlooked in favor of cold, data-driven logic-and hidden fees in algorithms and decision-making tools become the new norm, quietly influencing outcomes without our knowledge.

The Qantas Pie Fiasco

In a more unusual and lighthearted story, Alan Joyce, CEO of Qantas Airways, was pied in the face while addressing 500 executives in Perth. Unlike the resilience shown by Theodore Roosevelt, who famously finished his speech after being shot in the cheek in 1912, Joyce simply paused to clean up and continued. Roosevelt’s legendary response, “It takes more than that to kill a bull moose,” contrasts with Joyce’s more subdued reaction. While Roosevelt was unwavering in his resolve, Joyce’s pie incident was just a fleeting distraction. We’ve come a long way from the days when public figures exhibited such intense perseverance under duress, but it does make you wonder: do we hold the same resilience in today’s society, or has the bar been lowered?

Looking for Answers: The Search for Hidden Fees

In a story that hits close to home for those in the financial industry, a reporter from The Wall Street Journal set out to uncover just how much she was paying her financial advisor. The result wasn’t a scathing exposé on exorbitant fees, but rather a tale of frustration about how difficult it is to actually find the information. It reminded me of the ancient Greek myth of Theseus navigating the Labyrinth—only in this case, the Minotaur remains elusive, and the journey to uncover the truth is full of confusion. Trying to determine advisory fees feels much like navigating an endless maze, only to be met with vague answers, as if the Minotaur itself were saying, “Oh, that info is in a different labyrinth… sorry.” Hidden fees may not be illegal, but the lack of transparency around them certainly makes it feel unethical. The financial world must do better.

In conclusion, whether it’s the complexities of loan repayment behavior, the unsettling growth of big data, or the confusion around hidden fees, we seem to be living in a world where transparency is harder to come by, and understanding human behavior—both our own and others’—has become more complicated than ever.

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