Engineering and Scientific Progress.
Recent philosophical debate on progress in science has focused on answering the question of what constitutes scientific progress. In my dissertation, I argue that engineering constitutes scientific progress rather than only promoting or following from scientific progress. My argument proceeds in four stages, with each stage corresponding to a chapter of the dissertation. In the first chapter, I critically review the literature on maker’s knowledge and develop my own positive account of maker’s knowledge that understands making as essentially an embodied and socially situated practice. In the second chapter, I argue that engineering should be understood as essentially a kind of making, rather than an application of scientific theory to design problems independent of embodied and situated construction practices. In the third chapter, I use resources from embodied cognition to argue that engineering is just as cognitively sophisticated as science. In the fourth and final chapter, I argue that the essential epistemic feature of engineering is maker’s knowledge, and that the accumulation of maker’s knowledge constitutes progress in science.
The long-term goal of this research project is to understand and describe how our knowledge progresses by making in science and beyond through the framework for Maker’s Knowledge I developed in my dissertation.
Robotics and Embodied Cognition.
The second direction of my research investigates the role of engineering robotics in the practice of cognitive science and artificial intelligence and in philosophical accounts of the mind. In my dissertation, I rely on robotics research as a case study in support of my more general thesis that science progresses through making. Having gained significant education and experience in robotics since I began writing my dissertation, I intend to pursue my research into robotics in a greater level of detail than is permitted in case study analysis by more thoroughly investigating the philosophy of robotics for its own sake. For instance, robotics is a key point of contention in philosophy of cognitive science as proponents of embodied cognition (like me) appeal to the success of robotics in support of their views; this makes sense because robots are themselves embodied intelligent systems. Additionally, the necessarily embodied nature of robots makes them importantly different from disembodied models of mind like ChatGPT. My research in this area suggests that robots, because they are embodied like we are, are more likely to reveal the mechanisms of our own cognition than LLMs and other software-centric artificial intelligence.
Robotics research also seems to me a fruitful way forward for addressing two central problems in embodied cognitive science. These are the scaling-up problem and the integrity criterion. The scaling-up problem asserts that appeals to our embodiment alone cannot explain our ‘higher-order’ cognitive capacities like imagination, planning, and creativity. My contention is that robotics research is already producing convincing, embodied intelligent systems with increasingly higher-order cognitive capacities. Therefore, the severity of the scaling-up problem for embodied cognition is rapidly shrinking. The integrity criterion requires that psychology also be able to explain the psychologist. This is a potential problem for proponents of embodied cognition if psychological research cannot be explained through embodied practices. However, following what I argue in my dissertation, engineering robotics is a thoroughly embodied practice of making. Hence, to the extent that we make robots as models of intelligent systems in psychological research, our psychology does not violate the integrity criterion.
Social and Ethical Implications of Science and Engineering.
The third direction of my research concerns the broader social and ethical implications of engineering and science, especially artificial intelligence. In 2023, I was awarded an NSF Education Fellowship at the Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment. As part of my NSF AI fellowship, I published a paper titled “Leveraging Participatory Sense-Making and Public Engagement with Science for AI Democratization” in Studies in History and Philosophy of Science, arguing for a fruitful connection between public engagement with science and embodied cognitive science. Relatedly, as a graduate fellow of the UC Center for Public Engagement with Science, I co-authored a now in-press Cambridge Element titled A Guide for Academic Researchers Conducting Science Outreach. This paper and element are the start of a larger AI ethics research project concerned with developing ‘participatory cognitive strategies’ for including and engaging the public in science and engineering.