Two years ago, a 2012 study on dishonesty co-authored by renowned social psychologist and best-selling author Dan Ariely faced criticism. Some scientists argued that the underlying data, which described the reported number of miles driven by customers of a car-insurance company, had been falsified. The academic paper featuring the study was subsequently retracted. Ariely maintained that the figures had been given to him by the insurance company and he had no knowledge of any falsification. Recently, NPR’s Planet Money revealed that the insurance company, The Hartford, had found evidence of data manipulation in the study. Ariely once again denied engaging in any research misconduct. The situation becomes even more peculiar when considering the recent allegations against Harvard Business School professor Francesca Gino, who co-authored the 2012 paper. The question arises whether the fraud allegations are coincidental or if they indicate a case of coordinated misconduct. Scientific misconduct is difficult to determine due to the lack of systematic investigation and self-reporting. However, clues suggest that fraudulent behavior might be more common than expected. Identifying fraud requires a skeptical approach and meticulous examination of data. The lack of interest from scientific institutions in identifying fraud is reinforced by the naive assumption that scientists are inherently trustworthy. The existence of “clusterfakes,” where multiple instances of fraud occur within the same paper, would challenge the assumption that scientific misconduct is rare. It is possible that fraud is more prevalent than commonly acknowledged, with “mad, fraudulent unicorns” lurking in the scientific community.
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