Research misconduct is a developing issue that jeopardizes the credibility of scientific research. As the volume of research output grows each year, new forms of research misconduct emerge on the outskirts. Although research misconduct accounts for a small percentage of all published works, each instance appears much larger when magnified by public scrutiny. To prevent research misconduct, a preventative and proactive solution is required. Sami Benchekroun, CEO, and Co-founder of Morressier, suggests that to create such a solution, it is important to understand why research misconduct happens and address it on the industry level, not just within workflows.
When a system is under pressure, with limited resources and a constant need to accomplish things faster, research misconduct occurs. Researchers are under enormous pressure to publish in order to progress their careers and develop their personal reputations, which exposes them to predatory journals and paper mills. Scale and the temptation to examine more articles faster are difficulties in publishing and peer review workflows. The increasing strains on workflows and workloads have resulted in new forms of misconduct. The broader revenue structures of scholarly publications have also evolved, adding to the pressure from the open-access sector.
Today, research misconduct is treated reactively by retracting individual articles, which is a critical show of transparency but is misunderstood publicly. A proactive approach would involve a broader industry effort that addresses some of the underlying pressures for key stakeholders. This would include evolving the criteria for tenure processes, career progression, and evaluation to provide relief on the pressure to publish.
There are strategies to make the peer review process more streamlined and transparent, and a more streamlined editorial process will support publishers’ need to publish more research. Technology can support the improvement of papers from researchers for whom English is not a first language, democratizing the world of scholarly publishing.
We must strike a compromise between the requirement for research integrity and the desire to disseminate research more quickly. Curing research misconduct has the potential to delay science, yet emphasizing research integrity is an expensive and time-consuming investment. An ecosystem that struggles to scale risks losing sight of its quality goals. We lose trust if research integrity initiatives are not implemented, and public trust in science is already at stake. We risk embedding biases in the machine learning process if we feed our AI algorithms fake data or anything other than high-quality science. Leaders across the tech industry have recently signed an open letter calling on the industry to pause giant AI experiments and develop AI systems only after addressing research integrity at the center of the focus.