The benefits of Artificial Intelligence (AI) in medicine are unquestionable, and it is unlikely that the pace of its .
Fabrice Jotterand
May 5, 2024
Datafied Brain | Does Unregulated AI Implementation Serves Human?
Datafication
The benefits of Artificial Intelligence (AI) in medicine are unquestionable, and it is unlikely that the pace of its development will slow down. From better diagnosis, prognosis, and prevention to more precise surgical procedures, AI has the potential to offer unique opportunities to enhance patient care and improve clinical practice overall. How-ever, at this stage of AI technology development, it is unclear whether it will de-humanizeor re-humanize medicine. Will AI allow clinicians to spend less time on administrative tasks and technology related procedures and more time being present in person to attend to the needs of their patients? Or will AI dramatically increase the presence of smart technology in the clinical context to a point of undermining the humane dimension of the patient–physician relationship?
In this brief commentary, we argue that technological solutions should be only integrated into clinical medicine if they fulfill the following three conditions:
(1) they serve human ends
(2) they respect personal identity
(3) they pro-mote human interaction.
These three conditions form the moral imperative of humanity.
Human Reasons and the “Datafied Brain”
Despite these potential capabilities, there are concerns about the inability of AI to account for the realities of the human condition in its social, cultural, and embodied dimensions. The modus operandi of AI-enabled neurotechnology is based on statistical methods that do not include “human reasons” in conceptualizing cognition and behavior (i.e. beliefs, desires, motivations, and intentions). As Rainey and Erdenrightly remark “to reduce human reasons to simple gap-filling causes of behaviour is to miss details informed by a rich phenomenological experience of rationality and behaviour” (p. 19). Psychiatry, due to the nature of its practice, is inherently con-fronted by the realities of the human condition and is always in the process of evaluating how “human reasons” interact with, and shape patients’ behavior and identity. Human demeanor cannot be understood nor reduced to mere neural activity.It is certainly the case that technological solutions via neural-activity data can aid in diagnosis and establishing treatment options, but “the aim should always be to include the agent, and to presume agency” (p. 21). Therefore, the datafied brain (i.e.,detectable neural activity) is not “the proper brain” (p. 11). As Rainey and Erdenexplain “diagnosing problems of mind in terms of neurophysical anomaly omits key details about what mindedness consists in” (p. 12). Furthermore, as already dis-cussed, mental states and neural processes alike are not experienced in a vacuumbut are part of a rich social context with norms, culture, language, reasoning, other dimensions of human behaviors, and body language. In short, the mind is “an open system” (p. 12) not determined nor explained by mere statistical processes but by complex reasoning capacities that convey agency. Understanding the nature and role of neural states provides a basis to explain human behavior.The use of AI-enabled neurotechnology in psychiatry, however, adds another layer of explanatory power. Traditional, interpersonal modes of practice in psychiatry are, to a certain extent, challenged by neural explanation based on statistical models. The specificity in diagnosis and prognosis that AI-enabled neurotechnol-ogy affords, is unable to integrate “human reasons” into clinical judgments about patient behavior. AI-enabled neurotechnology “by-passes” the agency of the user as mental states are generated through neuro interventions (e.g. a closed neurot echno-logical device to detect and modify neural activity as stated by Rainey and Erden).It might not be an exaggeration, as Rainey and Erden bluntly conclude, that there is“no human in the loop on this neurotechnology model” (p. 9). Will AI-enabled neurotechnology de-humanize or re-humane in medicine? It might allow physicians to spend more time with patients, hence re-humanizing clinical practice, but the question still remains about whether clinical interventions themselves might de-human-ize patients by undermining their agency.
The Ethical Imperative of Humanity
AI-enabled neurotechnology will be technologically useful and clinically relevant but also problematic since it has the potential to view psychiatric patients as reducible to neuroscientific norms. Therefore, we argue that the technological solutions should be only integrated into clinical medicine if they fulfill the following three conditions: (1) they serve human ends; (2) they respect personal identity; and (3) they promote human interaction. These three conditions form what we call the moral imperative of humanity. The ethical framework we suggest is not limited to the ethical imperative of humanity. Rather humanity is the foundational concept from which the other five derive: information, transparency, participation, consensus, accountability. Before we take a deeper dive into humanity, we want to briefly outline the other moral imperatives which are grounded in three main categories. The first category includes information and transparency to deal with how human beings engage with technology. To anticipate the potentially deleterious implications of AI-enabled neurotechnology, gathering pertinent information about AI must always be at the forefront of any robust analysis. The complexity of AI technologies requires knowledge acquisition about their nature and abilities across relevant disciplines. Further, it is important to maintain transparency by informing all stakeholders including society at large since they will be the beneficiary of AI in medicine. To this end, communicating risks and benefits of AI cannot be limited to the context of their particular use, e.g., during the consenting process in the clinical context. Transparency is paramount to ensure a responsible and ethical implementation of AI in the clinical and social contexts. The second category concerns the way the technology might affect patient care and includes participation and consensus. As stated above, the public, as patients or potential patients, will be affected by the use of AI. Hence, strategies should be implemented to include all stakeholders in the analysis of the ethical, social, and regulatory implications of AI. This effort of course is not without challenges, in particular how to build consensus among stakeholders. Due to the limited scope of this article, it is not our intention to address this issue here. Rather, the importance of creating an environment conducive to develop ethical norms that responsibly guide public policies and establish standards of practice is crucial to harvest the potential benefits of AI-enabled neuro technologies. This point cannot be stressed enough in light of recent advances in neurotechnology (brain–computer interfaces; consumer neuro technologies), including the gathering of brain data by various third parties to generate neural profiles. The last category in our ethical frame work focuses specifically on health care, that is, how physicians should engage with AI-enabled neuro technologies and how current and future physicians ought to be trained. Fostering responsible development and implementation of AI in healthcare will demand that physicians be accountable for patient safety—accountability.
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