“Trustworthiness isn’t a very stable construct between individuals or between societies,” Spanton explained. The premises and methods used to develop the trustworthiness algorithm hinge on flawed and racist premises. researcher at the University of Plymouth, and Olivia Guest, Ph.D., an assistant professor at Radboud University, recently wrote a critique of the study that is now under consideration by the journal. “In this instance, the process is ongoing,” the spokesperson said, noting they would be willing to provide additional details at a future time “when further information is available.” “Once such processes have concluded and we have the necessary information to make an informed decision, we will follow up with the response that is most appropriate and that provides clarity for our readers as to the outcome,” the spokesperson added. “Whenever concerns are raised about any paper we have published, we look into them carefully, following an established process, consulting the authors and, where appropriate, seeking advice from peer reviewers and other external experts,” said a spokesperson for Nature Communications in an email.
In a response to The Debrief about the status of that review process, a representative for the publication wrote that it is still ongoing. The editors at Nature Communications are still reviewing and reconsidering the study, almost two years later. Only eight days after the study was published, the journal added an editor’s note, indicating that some of the criticisms against the paper are under further review. In 2020, research in Nature Communications claimed that changes in historical trustworthiness could be tracked through a machine learning algorithm that assessed facial cues in paintings.
Though facial recognition technology is used by police departments, governments, and even online proctoring services, it has little scientific basis and often leads to discriminatory and harmful outcomes.
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