Scott H. Hawley

Technology and Artificial Intelligence, both today and in the near future, are dominated by automated algorithms that combine optimization with models based on the human brain to learn, predict, and even influence the large-scale behavior of human users. Such applications can be understood to be outgrowths of historical trends in industry and academia, yet have far-reaching and even unintended consequences for social and political life around the world. Countries in different parts of the world take different regulatory views for the role and protection of user data, and this will in turn determine the course of development for technology and AI in the near future.

Visions of future applications of artificial intelligence tend to veer toward the naively optimistic or frighteningly dystopian, neglecting the numerous human factors necessarily involved in the design, deployment and oversight of such systems. The dream that AI systems may somehow replace the irregularities and struggles of human governance with unbiased efficiency is seen to be non-scientific and akin to a religious hope, whereas the current trajectory of AI development indicates that it will increasingly serve as a tool by which humans exercise control over other humans. To facilitate the responsible development of AI systems for the public good, we discuss current conversations on the topics of transparency and accountability.

Of primary importance in formulating a response to the increasing prevalence and power of artificial intelligence (AI) applications in society are questions of ontology. Questions such as: What “are” these systems? How are they to be regarded? How does an algorithm come to be regarded as an agent? We discuss three factors which hinder discussion and obscure attempts to form a clear ontology of AI: (1) the various and evolving definitions of AI, (2) the tendency for pre-existing technologies to be assimilated and regarded as “normal,” and (3) the tendency of human beings to anthropomorphize. This list is not intended as exhaustive, nor is it seen to preclude entirely a clear ontology, however, these challenges are a necessary set of topics for consideration. Each of these factors is seen to present a 'moving target' for discussion, which poses a challenge for both technical specialists and non-practitioners of AI systems development (e.g., philosophers and theologians) to speak meaningfully given that the corpus of AI structures and capabilities evolves at a rapid pace. Finally, we present avenues for moving forward, including opportunities for collaborative synthesis for scholars in philosophy and science.