A rise of academic capitalism over the past four decades has been well documented within many research-intensive universities. Largely missing, however, are in-depth studies of how particularly situated academic groups manage the uncertainties that come with intermittent and fickle commercial funding streams in their daily research practice and problem choice. To capture the strategies scientists adopt under these conditions, this article provides an ethnographically detailed (and true) story about how a single project in Artificial Intelligence grew over several years from (...) a peripheral idea to the very center of an academic lab’s commercial portfolio. The analysis theorizes an epistemic form—nimble knowledge production—and documents three of its lab-level features: 1) rapid prototyping to keep sunk costs low, 2) shared search for “real world problems” rather than “theoretical” ones, and 3) nimble commitment to research problem choice. While similar forms of academic knowledge transfer have been lauded as “mode 2,” “innovative,” or “hybrid” for initiating cross-institutional collaboration and pushing science beyond disciplinary silos, this case suggests it can rely on fleeting attention to problems resistant to a quick fix. (shrink)

By following the arguments developed by Vygotsky and employing the cultural-historical activity theory (CHAT) in addition to dialectical logic, this paper attempts to investigate the interaction between psychology and artificial intelligence (AI) to confront the epistemological and methodological challenges encountered in AI research. The paper proposes that AI is facing an epistemological and methodological crisis inherited from psychology based on dualist ontology. The roots of this crisis lie in the duality between rationalism and objectivism or in the mind-body rupture that (...) has governed the production of scientific thought and the proliferation of approaches. In addition, by highlighting the sociohistorical conditions of AI, this paper investigates the historical characteristics of the shift of the crisis from psychology to AI. Additionally, we examine the epistemological and methodological roots of the main challenges encountered in AI research by noting that empiricism is the dominant tendency in the field. Empiricism gives rise to methodological and practical challenges, including challenges related to the emergence of meaning, abstraction, generalization, the emergence of symbols, concept formation, functional reflection of reality, and the emergence of higher psychological functions. Furthermore, through discussing attempts to formalize dialectical logic, the paper, based on contradiction formation, proposes a qualitative epistemological, methodological, and formal alternative by using a preliminary algorithmic model that grasps the formation of meaning as an essential ability for the qualitative reflection of reality and the emergence of other mental functions. (shrink)

Environmental, health, and safety management systems have become common in research settings to improve laboratory safety through systematic observation and self-regulation. However, there is scant empirical evidence assessing whether these surveillance and inspection systems meet their intended objectives. Using data from safety inspections in research laboratories at a large university, we investigate whether conducting inspections, and recording and reporting findings back to the formally responsible actors (i.e., principal investigator scientists) lead to the improvement of regulatory compliance. Our analyses identify a (...) population of well-funded, high-status, tenured researchers whose non-compliant practices persist. Our interviews with environmental, health, and safety personnel suggest that higher-status actors disengage from the regulatory system, the compliance officers, and the system’s feedback process by their variable recognition and acknowledgment of relevant regulations, attention to the inspection reports, and responses to the feedback concerning repair of the unsafe situation. This study extends previous literature on regulatory compliance by providing evidence for the role of power and status in explaining actor-level non-compliant behavior. (shrink)