In our second of a two-part grounding conversation on “What is AI?”, Lucy Suchman draws connections between military logics, our own conception of intelligence, and how we map that onto AI as we know it. How we conceptualize “intelligence” in neural networks and machine learning is crucial for how we understand this technology. AI does relatively well at identifying statistical patterns in closed-world data. But real, open-world environments are notoriously difficult for the field of robotics and machine learning writ large, and as such “engineering” the world these machines inhabit and draw data from becomes almost as important for their proper functioning as the algorithms underlying them. Ultimately, we need to understand the limitations of AI systems, their risks, and acknowledge the aspects of the world that resist automation.BiographyLucy Suchman, Professor Emerita at Lancaster University and an expert in AI and human-computer interaction, delves with us into what lies beneath AI as we know it today– its history as a subfield of computer science, its functioning as a technology that extracts meaning from vast datasets, and ultimately, as a term that defies precise definition, sometimes to the benefit of the corporations behind its current form.