The assessment of society’s acceptance of artificial intelligence use in healthcare

Abstract Background We observe the surge of interest and application of artificial intelligence (AI) in various areas. AI use in healthcare and medicine is followed by society with interest; however, acceptance varies depending on the area of its application. This study aimed to understand the differences in acceptance depending on the type of solution and explain the factors influencing the attitude toward the use of AI in healthcare. Methods The data from the online survey was collected from a representative sample of 1109 adult Internet users in Poland. The respondents were asked about their acceptance of AI use for several purposes in healthcare. Based on the responses to these items, an ad-hoc score of AI acceptance in healthcare (AIAHC) was developed. The determinants of AIAHC were assessed with uni- (ULRM) and multivariable linear regression (MLRM) models. Results The highest acceptance of AI use was found for monitoring medication intake at home: mean (standard deviation, SD)-3.81 (1.39), the lowest for AI making decisions about the mode of therapy -2.78 (1.35). ULRMs showed that significant predictors of AIAHC were age, gender, chronic disease, vocational status, income, the use of the Internet (IU), and e-health literacy (eHL). In MLRM, only gender, vocational status, income, and eHL maintained a significant relationship with AIAHC. Males showed significantly higher AIAHC than females (B, 95%CI: 2.56, 1.42 - 3.71), and students had higher AIAHC than employees (B, 95%CI: 3.01, 0.14 - 5.89). Persons who refused to reveal their income demonstrated lower acceptance of AI use than those who revealed their income (B, 95%CI: -4.64, -6.54 - -2.74). Finally, greater eHL favored higher AIAHC (B, 95%CI: 0.46, 0.34 - 0.57). Conclusions Evidently, there is a hierarchy of potential areas of application in terms of society’s acceptance. Improving eHL should exert a positive effect on the acceptance of innovative technologies, including AI, in healthcare. Key messages • Citizens show moderate enthusiasm toward the broader use of AI in healthcare. • E-health literacy exerts a positive effect on the introduction of AI-based solutions in healthcare.