Professional Judgment in an Era of Artificial Intelligence and Machine Learning

There are two fundamental features of the information processing behind most efforts to substitute artificial intelligence, machine learning, and robotics for professionals in health and education: reductionism and functionalism. True professional judgment is at odds with the mindset of substitutive automation. Instead of reductionism, an encompassing holism is a hallmark of professional practice — an ability to integrate facts and values, respect the demands of particular cases, and to balance mission and margin in institutional decision-making. The only way these sectors can progress is to maintain a large core of professionals that intermediate between technology and the patients/students. However, the lifeblood of AI ambitions — data — is neither brute nor given. Deciding what data matters, how it is fairly and accurately collected, and how to balance quantitative and qualitative approaches to the representation of situations, will be critical and enduring roles for professionals.