AIDD, Autonomy, and Military Ethics

In “Artificial Intelligence, Social Media and Depression,” Laacke and colleagues (2021) consider the ethical implications of artificial intelligence depression detector (AIDD) tools to assist practitioners in diagnosing depression or posttraumatic stress. Although the revised account of health-related autonomy (HRDA) offers important correctives in the era of digital data, I argue that additional considerations ought to operate in institutional contexts where autonomy is already compromised, such as in the military. Complementing the health-related account with insights from military ethics and the ethics of war, specifically, jus in bello internal obligations to military personnel, demonstrates the importance of considering alternative ethical frameworks and institutional contexts of compromised autonomy prior to implementing any AIDD. HRDA provides some checks to ensure that the use of AIDD preserves the autonomy of the participant. But what about situations wherein autonomy is already compromised? Does the context of voluntary involvement in an institution of compromised autonomy, like the military, affect an ethical analysis of artificial intelligence instruments in health care contexts? On one hand, diagnostic technology may provide a lifesaving intervention to help soldiers or veterans who are suffering from depression or posttraumatic stress disorder (PTSD). This could facilitate greater attention to mental health concerns in the field and help alleviate some of the burden on the veterans’ health system, allowing for ease of triage to better allocate resources. Further, given the documented stigma surrounding mental health care, artificial intelligence (AI) could make mental health a uniform element of overall well-being in institutionalized contexts like the military. On the other hand, diagnostic technology contributes to what might be called “control creep” by institutions and is particularly troubling for institutions that already compromise autonomy. The military is a large institution with responsibility for the health and well-being of its members. Although members join voluntarily, their lives are circumscribed by the decisions of others. Further, diagnostic technology risks expanding the divide between soldiers and citizens, making it even easier for citizens to renounce collective responsibility for war, abandon the obligation to care for military personnel, and fail to engage responsibly with the burdens of war (Scholz 2020). As a society, we ought to resist quick fixes that reduce the moral burden of war to an algorithm, including the costs for the mental health of military personnel. The dominant framework in the ethics of war, just war theory, articulates principles to guide decisions to go to war, behavior within war, and peaceful resolution of war. The principles emerge from a long tradition aimed at preserving the rights of the innocent and avoiding unnecessary harm. The just war tradition considers maintaining the moral rights and status of those fighting as instruments of a political community to be part of the moral burdens of war (Walzer 1977). A human rights-based approach to just war theory includes a defense of the basic rights of soldiers while they serve their government in times of peace as well as in times of war. Brian Orend describes the “big five” rights of security, subsistence, liberty, equality, and recognition, which guide the jus in bello internal obligations to military personnel. Although military involvement transforms certain basic rights of military personnel, they still possess rights, albeit in context-delimited form. The right to liberty includes the right to refuse certain enhancements (Orend 2013, 146), and the right to equality ensures access to adequate health care. Digital diagnostic tools, whether through social media or wearables, often place efficiency above other considerations, as Laacke and colleagues note. Within voluntary institutions like the military, efficient provision of health care quickly gives way to considerations of the costs imposed on the nation. But what other costs are borne with a reliance on machines for diagnosing mental health concerns? Consider, for instance, the cost to the individual, the cost to society, and the cost to collective understanding of mental health within institutional contexts of compromised autonomy. Control creep, like its relative, surveillance creep, may influence the obedience demanded of soldiers. In discussions of surveillance creep, AI ethicists often bring up the erosion of an expectation against surveillance, sacrificing privacy and subtly affecting decisions (Frischmann and Selinger 2018, 26). Users of platforms become accustomed to their information being part of “big data,”