This Scientist catches FRAUD in Harvard and Stanford Research

Summary

In a revealing interview, Elizabeth Bick, a renowned science data image detective, shares her journey and techniques in uncovering image fraud in academic papers. With a PhD in microbiology and 15 years at Stanford, Bick transitioned to full-time investigation, using her keen eye and software like Image Twin and PRIC to detect duplications. Her work has led to significant revelations, including fraud in papers by high-profile scientists, highlighting a culture in academia that often prioritizes sensationalism over truth. Bick's insights into the challenges of addressing these issues within the scientific community underscore the need for systemic change and integrity in research.

Takeaways

• 💚 Elizabeth Bick is celebrated as a hero in science for her work in uncovering image fraud in academic papers.
• 📌 She played a crucial role in revealing image manipulation in the work of high-profile figures, including a Stanford University president and a Nobel Prize winner.
• 🔍 Bick's background is in microbiology, and she has spent over 15 years at Stanford before becoming a full-time science data image detective in 2019.
• 👁‍🗨️ Her primary method involves using her keen observational skills to detect duplications and manipulations in scientific images, although she also uses software tools like ImageTwin and PRIC.
• 🛠️ The use of software like ImageTwin has significantly aided her in identifying fraudulent images that would be challenging to detect with the naked eye alone.
• 📚 Bick's talent for spotting patterns is a key asset in her work, drawing parallels between natural uniqueness and the expected variance in scientific imagery.
• 👨‍🔬 She advocates for incorporating image verification software into the peer review process to catch academic misconduct more efficiently.
• 🚫 Many of the image manipulations Bick uncovers are symptomatic of broader issues within research culture, such as a preference for quantity over quality and a lack of integrity.
• 💡 The problems in academic research are often linked to toxic lab cultures, including bullying and the exploitation of researchers on temporary visas.
• 🛡️ Despite uncovering numerous cases of fraud, Bick expresses frustration over the lack of action taken by publishers and editors, likening it to consumer rights issues.

Q & A

Who is Elizabeth Bick and what is she known for?

Elizabeth Bick is a microbiologist known for her work in identifying image fraud in academic papers, notably uncovering evidence of image manipulation in research by prominent figures such as Mark Tessier-Lavigne, Greg Semenza, and Khed Sha.

What led to Mark Tessier-Lavigne stepping down from his position at Stanford University?

Mark Tessier-Lavigne stepped down from his position as the president of Stanford University following allegations of image fraud in his papers, uncovered by Elizabeth Bick.

How does Elizabeth Bick find evidence of image fraud in scientific papers?

Elizabeth Bick primarily uses her eyes to detect duplications and manipulations in images within scientific papers. She looks for identical images, overlapping panels, or duplications within a panel. In recent years, she has also utilized software, such as Image Twin and PRIC, to help identify these duplications more efficiently.

What software does Elizabeth Bick use to assist in her investigations?

Elizabeth Bick uses software packages like Image Twin and PRIC to help identify duplications and manipulations in scientific images. Image Twin, for instance, has a database of images that can help find duplications across different papers.

How did Elizabeth Bick's use of software lead to the discovery of fraudulent images in Khed Sha's research?

Through the use of Image Twin, Elizabeth Bick was able to identify multiple instances of duplicated images in Khed Sha's work that were taken from completely different papers and even from websites selling scientific equipment, which were falsely presented as original research evidence.

Why does Elizabeth Bick believe that nature's uniqueness is crucial in spotting image fraud?

Elizabeth Bick points out that in nature, patterns are unique, such as no two leaves or rocks being identical. Similarly, in scientific images like cells or tissues, while patterns might be similar, they should not be identical. Spotting identical patterns is usually indicative of fraud, as it goes against the natural variability expected in scientific data.

What does Elizabeth Bick suggest about the culture in some research labs?

Elizabeth Bick suggests that a worryingly large number of research labs have a culture that prioritizes quantity over quality and sensationalism over truth. This culture, which often involves bullying and cutting corners, may contribute to the prevalence of data manipulation and fraud.

What motivates scientists to engage in image manipulation or data fraud, according to Elizabeth Bick?

Elizabeth Bick indicates that the motivation behind image manipulation or data fraud often stems from the culture of the research lab rather than the individuals being inherently evil. This culture promotes high output and significant results, sometimes at the cost of scientific integrity.

What challenges has Elizabeth Bick faced in getting academic journals to act on her findings?

Elizabeth Bick has expressed frustration with the lack of action from academic journals and publishers upon reporting cases of image fraud. She compares the situation to complaining about a faulty car and being told to just live with it, highlighting a systemic issue in scientific literature where editors are reluctant to address problems in peer-reviewed papers.

How does Elizabeth Bick view the role of software like Image Twin in the peer review process?

Elizabeth Bick believes that software like Image Twin should be integrated into the standard peer review process for papers containing images. She argues that this would make catching academic misconduct easier and more reliable, as well as help expand the software's database for detecting duplications, ultimately improving the integrity of scientific research.