AI in Healthcare _ ___________________________________________________________________________
• Continual validation and evaluation of AI-powered platforms to detect hallucinations and employ diverse datasets • Human oversight by healthcare and mental health professionals to review AI results to ensure clinical accuracies • Provide training and continuing education to practitioners about the use of AI • Delineate explainable and transparent AI models and protocols so practitioners understand how AI algorithms are developed • Establish ethical and legal governance committees to provide oversight Questions about liability may arise with the involvement of AI, including who or what is liable and accountable for outcome(s) [4; 54]. Because AI is new and developing quickly, many health and mental healthcare professionals have not been fully trained on how to utilize AI nor are they fully aware of the latest evidence-based practice guidelines [55]. This raises the ethical issue of professional competency. The heart of clini- cal decision-making and judgment have traditionally revolved around the expertise of the professional, and a shift to an AI “expert” system requires practitioners to be fully trained and feel competent and comfortable with the operation of AI systems [26]. Practitioners who are interested in using AI in their clinical practice may refer to the Association for the Advancement of Artificial Intelligence (https://aaai.org) for guidance and to keep up to date on new developments [55]. OVER-RELIANCE ON AI AND PERCEPTION OF CLIENT/PATIENT ABANDONMENT On a macro level, some have argued that overreliance on AI tools in health and mental health can result in practitioners becoming complacent in continuing to build and enhance their skills [62]. In other words, this could ultimately lead to the de-skilling of the health and mental healthcare workforce [62]. Some providers may also feel pressure to follow AI rec- ommendations, instead of using the AI recommendations to supplement their clinical judgment [64]. On a micro level, patients/clients whose providers use AI extensively may feel that their practitioners are abandoning them [55]. While chatbots can offer immediate support, some patients/clients will prefer direct human interaction that cannot be obtained from a bot. At the heart of the provider- patient/client relationship is human empathy, conveyed through verbal and nonverbal communication and human interaction. Ultimately, AI does not have emotional intel- ligence to employ clinical wisdom, intuition, and empathy [27]. An over-reliance on AI can lead to an impersonal and dehumanizing experience for patients/clients [64].
COLLABORATION BETWEEN PRACTITIONERS AND AI
Some are skeptical of the use of AI in the health and mental health fields, and others are wholly enthusiastic. The reality is that optimal outcomes will come from a partnership of AI and practitioners. In an ideal world, AI would serve as a comple- ment to humans, enhancing and supporting clinical decision- making but with practitioners providing oversight [29]. The American Medical Association coined the term “augmented intelligence” to refer to the ideal relationships between humans and AI applications [36]. The following ideal outcomes can result from an AI partnership with practitioners [27]: • Combined insights to better understand the needs of the patient/client • Timely interventions, with the practitioner providing oversight to ensure the interventions are tailored to specific needs and handle new issues that emerge real time • Combined AI efficiency and practitioner empathy help to promote patient/client trust • Reduce diagnostic errors by combining precision from AI and clinical wisdom and intuition of the practitioner • Improved ethical decision-making by the AI objective analysis with the practitioner’s experience, wisdom, and insights However, this partnership is still tenuous. Some research indicates that team members’ sense of trust does not neces- sarily grow over time in human-AI teams (HATs or HAIT) [65]. Incorporating AI team members does not necessarily enhance communication and coordination, perhaps because human team members have excessively high of expectations of AI team members. Alternatively, human team members may lack the training and understanding necessary for clear and optimal communication and collaboration with AI team members [65]. Ultimately, more training and continuing educa- tion are needed to improve the relationship between AI and practitioners and to explore how specific skills can merge and complement each other [27]. CONCLUSION The technology of AI is growing at a rapid pace, and it can be difficult to keep up. While many remain skeptical and mistrustful of the application of AI in day-to-day life, practi- tioners in the health and mental health fields are called on to recognize that AI will continue to be a part of the professional landscape. In order for a positive synergistic relationship to develop between AI and practitioners, practitioners require an understand of AI systems and an opportunity to take part in AI-powered clinical decision-making, rather than passive relegation of clinical practice to AI. All professionals should
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