Impact of Artificial Intelligence (AI) Image Enhancing Filters on Patient Expectations for Plastic Surgery Outcomes

Aesthetic Plast Surg. 2025 Jan 8. doi: 10.1007/s00266-024-04635-5. Online ahead of print.

Abstract

Background: Artificial intelligence (AI) technologies use a three-part strategy for facial visual enhancement: (1) Facial Detection, (2) Facial Landmark Detection, and (3) Filter Application (Chen in Arch Fac Plast Surg 21:361-367, 2019). In the context of the surgical patient population, open-source AI algorithms are capable of modifying or simulating images to present potential results of plastic surgery procedures. Our primary aim was to understand whether AI filter use may influence individuals' perceptions and expectations of post-surgical outcomes.

Methods: We utilized Amazon's Mechanical Turk platform and collected information on prior experience using AI-driven visual enhancement. The cohort was divided into two groups: AI-exposed and non-AI-exposed. Questions gauged confidence in plastic surgery's ability to meet participant expectations. A second survey exposed users to either AI-enhanced or to unenhanced pre-operative photographs. Then, unedited post-operative photographs were shown and surgery's ability to enhance appearance was assessed. A multivariable linear analysis was constructed to measure associations between exposure to AI enhancement and survey outcomes.

Results: A total of 426 responses were analysed: 66.9% with AI exposure and 33.1% with no prior exposure. Participants with previous experience using AI-driven enhancers had a significantly higher average score for expectations after plastic surgery (P < 0.001). This finding was true across all outcomes, including surgery's ability to relieve discomfort with appearance/self-esteem (P < 0.001), to avoid post-operative complications (P < 0.001), to decrease post-operative scarring (P < 0.001), and to improve overall appearance (P < 0.001). The image comparison survey revealed that post-operative images were viewed as more successful at improving appearance when no pre-operative filter was applied (P = 0.151).

Conclusion: Exposure to AI photograph enhancement may significantly raise expectations for plastic surgery outcomes and may predispose to having lower satisfaction after surgery. The significance of this study lies in its potential to reveal the extent to which AI technologies can shape patient understanding of their plastic surgery outcomes. Plastic surgeons aware of the effect of AI enhancement may consider using these results to guide counselling.

Level of evidence iii: his journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Keywords: Artificial intelligence; Patient expectations; Pre-operative counselling; Technology.