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[ RESEARCH INTEGRITY ] June 30, 2023

Research integrity unraveling: Recent cases of fraud and misconduct

Research fraud headlines in the news can greatly damage the collective reputation of science. Discover the latest research misconduct cases and learn what emerging tools might be the key to carrying our forward community to better integrity.


When dishonesty studies become dishonest

A recent case has sent shockwaves throughout the academic community. Today’s spotlight falls on Francesca Gino, a Harvard Business School professor, and Dan Ariely, a behavioral economist at Duke University, and the author of “The Honest Truth About Dishonesty”. The controversy began when the Data Colada blog initiated a compelling series, unearthing evidence of fraud in four academic papers co-authored by Gino, suggesting the presence of fabricated data. 

Both Gino and Ariely co-authored a 2012 study that examined the effect of honesty pledges on dishonest behavior using three examples. Astonishingly, the blog's investigation revealed that the data in the third study, supervised by Ariely, and the first study, where Gino solely handled data collection and analysis, had been tampered with.

You heard right! Two different researchers faked data for two separate studies within a paper on dishonesty, independent of one another.

Dan Ariely denies fabricating data, stating: “If I knew that the data was fraudulent, I would have never posted it.” Yet the author can't produce records to clear his name, which raises suspicions. Meanwhile, Gino has been placed on administrative leave at Harvard. 

This ironic case has created big questions about the nature of dishonesty and the credibility of research as a whole. It forces us to contemplate the underlying factors that foster this behavior and challenges the integrity of the academic environment itself.



Fishy findings

Earlier this year, The Proceedings of the Royal Society B: Biological Sciences refused to retract a 2016 paper which a team of whistleblowers deemed untrustworthy. The paper was authored by marine ecologists Danielle Dixson of University of Delaware and Anna Scott of Southern Cross University in Australia, and stated that anemone fish can “smell” whether coral reefs are bleached or healthy. Yet, despite the data Dixson reported, the researchers would not have had enough time to complete the studies described over the indicated 13 days. Last year, a correction stated that the experiments actually took place over 33 days, causing the journal to refuse retraction as the correction seemingly solved the paper’s issue.

Yet, the controversy continued. Josefin Sundin, one of the whistleblowers said: “Why would anyone run an experiment for 33 days but by mistake write the methods and data as if it was conducted during 12 days? That is a very large discrepancy.” 

On June 27th, 2023, the paper was finally retracted after a university investigation raised “substantial doubts regarding the new timelines stated in the correction and the feasibility of the experimental design”, causing the journal to lose faith in the research’s reliability. Both academics deny any wrongdoing.

New innovations sparking hope for integrity 

While recent cases of research misconduct may raise concerns about the reliability of scholarly work, the emerging power of artificial intelligence (AI) brings a glimmer of hope. 
AI has the potential to uncover patterns that elude human observation. Recently, an atlas of biomedical research has become publicly available that connects and maps the relationships between nearly 21 million articles, allowing us to detect patterns in research that would otherwise remain unnoticed.

 In one instance, the atlas highlighted almost 12,000 papers that had been flagged as retracted on the PubMed database.  These clusters provide insights into the topics that are more susceptible to content production by paper mills, giving us the ability to recognize early indicators of fraudulent research and prevent its detrimental impact on the scientific community.

But, the potential of these AI-driven solutions extends far beyond detecting misconduct. With further development, these tools could also help identify disparities in representation, shedding light on areas where female researchers and researchers of color may be underrepresented or overlooked.


As research integrity cases grow and become more complex, the future may seem scary and unsettling. 

In reality, there is a brighter path ahead. And the only way to get there is through embracing exciting new tools, bold thinking, and proactive strategies. Start your journey with us today.

using experimentation to improve research integrity