Balkinization: The Algorithm Will See You Now

The Algorithm Will See You Now

Guest Blogger

Claudia Haupt

For the Symposium on The Law And Policy Of AI, Robotics, and Telemedicine In Health Care.

Artificial intelligence (AI) may well turn out to have a transformative effect on the delivery of healthcare services. Various mobile devices now feature “mHealth” applications, prompting healthcare providers to explore novel ways to incorporate these functions into medical care. Technology companies are connecting existing consumer-facing technologies like Alexa to diagnostics AI, creating new avenues of medical advice-giving. Similarly, professional-use algorithms and AI are available on the provider side. As we may be moving from computer-aided diagnosis to algorithm-generated advice, new technical, medical, and legal questions emerge. What seems like a new frontier in the delivery of healthcare services actually takes us back to the early days of AI—after all, ELIZA’s DOCTOR script, developed in the mid-twentieth century, simulated a psychotherapist.

Technological innovation in healthcare occurs in a densely regulated space dominated by asymmetries of knowledge and social relationships based on trust. Professional advice is valuable to patients and clients because of the asymmetry between lay and expert knowledge. Professionals have knowledge that clients lack, but need to make important life decisions. These relationships are governed by a legal framework of professional advice-giving consisting of several elements, including professional licensing, fiduciary duties, informed consent, and professional malpractice liability. The regulatory goal is to ensure that the patient (or client) receives comprehensive, accurate, reliable advice from the doctor (or other advice-giving professional). Traditionally, this framework assumed interactions between human actors. Introducing AI challenges this assumption, though I will stipulate that AI does not entirely replace human doctors for now.

The questions underlying professional advice-giving involving various forms of technology raise enduring questions about the nature of the doctor-patient relationship. What does it mean to give and to receive professional advice, and how do things change when technological solutions—including AI—are inserted into the process of advice-giving?

We might consider the various medical tech solutions to be medical devices and contemplate potential regulation by the U.S. Food and Drug Administration (FDA). But the line between medical devices, so understood, and other electronic health gadgets seems increasingly blurry. And the process of professional advice-giving is the same across professions, whereas the FDA’s potential jurisdiction over medical devices only applies to one slice of the professional universe. The theoretical questions have much deeper roots that would be obscured by a sector-specific regulatory solution. Or we might want to subject AI, independent of its application, to regulation by a separate agency. I have recently started to explore yet another perspective: for AI in professional advice-giving, such as AI in the doctor-patient relationship, we might want to start with the traditional regulatory framework for professionals. This perspective builds on a theory of professional advice-giving that has the professional-client or doctor-patient relationship at its core and conceptualizes professionals as members of knowledge communities. So doing, this approach puts scholarship on professional regulation into conversation with the emergent literature on AI governance.

Outside of the medical context, Jack Balkin explains that a rapid move from “the age of the Internet to the Algorithmic Society” is underway. He defines the Algorithmic Society as “a society organized around social and economic decision making by algorithms, robots, and AI agents [] who not only make the decisions but also, in some cases, carry them out.” In this emerging society, we need “not laws of robotics, but laws of robot operators.” Here, “the central problem of regulation is not the algorithms but the human beings who use them, and who allow themselves to be governed by them. Algorithmic governance is the governance of humans by humans using a particular technology of analysis and decision-making.”

We should likewise begin to consider forms of algorithmic governance in the medical advice-giving context. Should professional-use algorithms be subject to professional licensing, and what level of technical proficiency should be expected of licensed professionals who employ AI in their practice? As a matter of professional malpractice, who is liable for harm caused by bad AI-generated advice? Does the introduction of AI require informed consent? How do fiduciary duties apply?

Instead of assessing each algorithm or AI agent individually, or dividing the professional AI world into sector-specific regulatory regimes in order to consider whether and how it should be regulated, we should first turn to the traditional regulatory framework that governs professional advice-giving. This point, in fact, applies to all advice-giving professions. But it is perhaps most clearly conveyed in the medical context, where we have strong intuitions about the doctor-patient relationship and its underlying values.

Claudia E. Haupt is Associate Professor of Law and Political Science at Northeastern University School of Law. You can reach her by e-mail at c.haupt@northeastern.edu

Posted 11:00 AM by Guest Blogger [link]