Human-computer symbiosis: enhancing dermatologic care while preserving the art of healing

Public Perceptions, Factors, and Incentives Influencing Patient Willingness to Share Clinical Images for Artificial Intelligence-Based Healthcare Tools

INTRODUCTION

The use of artificial intelligence (AI) as a diagnostic and decision-support tool is increasing in dermatology. The accuracy of image-based AI tools is incumbent on images in training sets, which requires patient consent for sharing. This study aims to understand individuals' willingness to share their images for AI and variables that influence willingness.

METHODS

In an online survey administered via Amazon Mechanical Turk, sketches of the hand, face, and genitalia assigned to two use cases employing AI (research vs. personal medical care) were shown. Participants rated willingness to share the image on a 7-point Likert scale.

RESULTS

Of the 1010 participants, individuals were most willing to share images of their hands (81.2%), face (70.3%), and lastly genitals (male: 56.8%, female: 46.7%). Individuals were more willing to share for personal care versus research (OR 0.77 [95% CI 0.69-0.86]). Willingness to share was higher among males, participants with higher education, tech-savvy participants, and frequent social media users. Most participants were willing to share images if offered monetary compensation, with face images requiring the highest payment (mean $18.25, SD 20.05). Only 38.7% of individuals refused image sharing regardless of any monetary compensation, with the majority of this group unwilling to share images of the genitals.

CONCLUSIONS

This study demonstrates overall public support for sharing images to AI-based tools in dermatology, with influencing factors including image type, context, education level, technology comfort, social media use, and monetary compensation.

Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study

Importance

The use of artificial intelligence (AI) is expanding throughout the field of medicine. In dermatology, researchers are evaluating the potential for direct-to-patient and clinician decision-support AI tools to classify skin lesions. Although AI is poised to change how patients engage in health care, patient perspectives remain poorly understood.

Objective

To explore how patients conceptualize AI and perceive the use of AI for skin cancer screening.

Design, Setting, and Participants

A qualitative study using a grounded theory approach to semistructured interview analysis was conducted in general dermatology clinics at the Brigham and Women's Hospital and melanoma clinics at the Dana-Farber Cancer Institute. Forty-eight patients were enrolled. Each interview was independently coded by 2 researchers with interrater reliability measurement; reconciled codes were used to assess code frequency. The study was conducted from May 6 to July 8, 2019.

Main Outcomes and Measures

Artificial intelligence concept, perceived benefits and risks of AI, strengths and weaknesses of AI, AI implementation, response to conflict between human and AI clinical decision-making, and recommendation for or against AI.

Results

Of 48 patients enrolled, 26 participants (54%) were women; mean (SD) age was 53.3 (21.7) years. Sixteen patients (33%) had a history of melanoma, 16 patients (33%) had a history of nonmelanoma skin cancer only, and 16 patients (33%) had no history of skin cancer. Twenty-four patients were interviewed about a direct-to-patient AI tool and 24 patients were interviewed about a clinician decision-support AI tool. Interrater reliability ratings for the 2 coding teams were κ = 0.94 and κ = 0.89. Patients primarily conceptualized AI in terms of cognition. Increased diagnostic speed (29 participants [60%]) and health care access (29 [60%]) were the most commonly perceived benefits of AI for skin cancer screening; increased patient anxiety was the most commonly perceived risk (19 [40%]). Patients perceived both more accurate diagnosis (33 [69%]) and less accurate diagnosis (41 [85%]) to be the greatest strength and weakness of AI, respectively. The dominant theme that emerged was the importance of symbiosis between humans and AI (45 [94%]). Seeking biopsy was the most common response to conflict between human and AI clinical decision-making (32 [67%]). Overall, 36 patients (75%) would recommend AI to family members and friends.

Conclusions and Relevance

In this qualitative study, patients appeared to be receptive to the use of AI for skin cancer screening if implemented in a manner that preserves the integrity of the human physician-patient relationship.