Visual digital data, ethical challenges, and psychological science.

Digital visual data afford psychologists with exciting research possibilities. It becomes possible to see real-life interactions in real time and to be able to analyze this behavior in a fine-grained and systematic manner. However, the fact that faces (and other personally identifying physical characteristics) are captured as part of these data sets means that this kind of data is at the highest level of sensitivity by default.

Investigating age-related differences in ability to distinguish between original and manipulated images.

Manipulated images can have serious and persistent ramifications across many domains: They have undermined trust in political campaigns, incited fear and violence, and fostered dangerous global movements. Despite growing concern about the power of manipulated images to influence people's beliefs and behavior, few studies have examined whether people can detect manipulations and the psychological processes underpinning this task. We asked 5,291 older adults, 5,291 middle-aged adults, and 5,291 young adults to detect and locate manipulations within images of real-world scenes.

AI-synthesized faces are indistinguishable from real faces and more trustworthy.

Artificial intelligence (AI)-synthesized text, audio, image, and video are being weaponized for the purposes of nonconsensual intimate imagery, financial fraud, and disinformation campaigns. Our evaluation of the photorealism of AI-synthesized faces indicates that synthesis engines have passed through the uncanny valley and are capable of creating faces that are indistinguishable-and more trustworthy-than real faces.

Perceptual and computational detection of face morphing.

A relatively new type of identity theft uses morphed facial images in identification documents in which images of two individuals are digitally blended to create an image that maintains a likeness to each of the original identities. We created a set of high-quality digital morphs from passport-style photos for a diverse set of people across gender, race, and age. We then examine people's ability to detect facial morphing both in terms of determining if two side-by-side faces are of the same individual or not and in terms of identifying if a face is the result of digital morphing.

Assessing the reliability of a clothing-based forensic identification.

A 2009 report by the National Academy of Sciences was highly critical of many forensic practices. This report concluded that significant changes and advances were required to ensure the reliability across the forensic sciences. We examine the reliability of one such forensic technique used for identification based on purported distinct patterns on the seams of denim pants.

Can people detect errors in shadows and reflections?

The increasing sophistication of photo-editing software means that even amateurs can create compelling doctored images. Yet recent research suggests that people's ability to detect image manipulations is limited. Given the prevalence of manipulated images in the media, on social networking sites, and in other domains, the implications of mistaking a fake image as real, or vice versa, can be serious.

Detecting morphed passport photos: a training and individual differences approach.

Our reliance on face photos for identity verification is at odds with extensive research which shows that matching pairs of unfamiliar faces is highly prone to error. This process can therefore be exploited by identity fraudsters seeking to deceive ID checkers (e.g.

Can people identify original and manipulated photos of real-world scenes?

Advances in digital technology mean that the creation of visually compelling photographic fakes is growing at an incredible speed. The prevalence of manipulated photos in our everyday lives invites an important, yet largely unanswered, question: Can people detect photo forgeries? Previous research using simple computer-generated stimuli suggests people are poor at detecting geometrical inconsistencies within a scene. We do not know, however, whether such limitations also apply to real-world scenes that contain common properties that the human visual system is attuned to processing.