Article ID: CBB775831884

Managing Ambiguities at the Edge of Knowledge: Research Strategy and Artificial Intelligence Labs in an Era of Academic Capitalism (July 2017)

unapi

Many research-intensive universities have moved into the business of promoting technology development that promises revenue, impact, and legitimacy. While the scholarship on academic capitalism has documented the general dynamics of this institutional shift, we know less about the ground-level challenges of research priority and scientific problem choice. This paper unites the practice tradition in science and technology studies with an organizational analysis of decision-making to compare how two university artificial intelligence labs manage ambiguities at the edge of scientific knowledge. One lab focuses on garnering funding through commercialization schemes, while the other is oriented to federal science agencies. The ethnographic comparison identifies the mechanisms through which an industry-oriented lab can be highly adventurous yet produce a research program that is thin and erratic due to a priority placed on commercialization. However, the comparison does not yield an implicit nostalgia for federalized science; it reveals the mechanisms through which agency-oriented labs can pursue a thick and consistent research portfolio but in a strikingly myopic fashion.

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Authors & Contributors
Carsten Ochs
Beth Singler
Tom Kane
Sigrid Vertommen
Barbara Büttner
Vlad Schuler Costa
Concepts
Technoscience; science and technology studies
Research and development (R&D)
Ethnography
Intellectual property
Capitalism
Artificial intelligence
Time Periods
21st century
20th century, late
20th century
20th century, early
19th century
Places
United States
Africa, Sub-Sahara
Georgia (Republic)
South Korea
Palestine
Romania
Institutions
Facebook (firm)
Industrial Technology Research Institute- ITRI
Korea Institute of Science and Technology - KIST
Chinese Academy of Sciences
International Business Machines Corporation
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