"What does a neural network model?"
(Philosophy of Science)
Eamon Duede (UChicago)
"Abduction Through Social Syllogisms and the Logic of Scientific Advance"
(Philosophy of Science)
Here we argue that the production of novel scientific claims through the process of abduction, the historical province of philosophy, represents a critical scientific practice, central to scientific success and failure, and increasingly available to science studies through large-scale data. We re-scale abduction to show how it necessarily occurs through conversation between those who understand a particular
scientific system and its anomalies—its priests—and those exposed to alien and disruptive patterns, theories,
and findings that could resolve them—its prophets. We argue that these complex, extended conversations between
those with divergent backgrounds define a social logic of discovery that yield speculative hypotheses with
outsized impact across science.
Eamon Duede (UChicago) and James Evans (UChicago)
"Distance Matters in Science and Scholarship"
(Science of Science)
The effect of spatial distance on scientific discovery and innovation is a highly important policy
issue. Yet, there is still significant debate concerning how space affects science. Ubiquitous
digitization has led many to declare a “death of distance” in science. This implies that, while
search and discovery are still necessary, what influences us is not, itself, a function of its
location. Consequently, citations, a primary policy metric, are assumed to be “placeless” such
that, when scientists cite work, they simply acknowledge the contributions that influenced them.
Nevertheless, a growing body of research argues that spatial distribution of science still matters,
with distance affecting the probability of citation. However, this work relies on indirect measures
of influence. Here, we present and deploy a direct measure of influence, derived from a survey
of ~12,000 authors. Combining direct reporting of how authors were influenced by their references,
authors’ institutional data, and geographic locations from the Google Maps API, we are able to
measure the relationship between spatial distance and influence much more directly than previously
Eamon Duede (UChicago), Misha Teplitskiy (Michigan), and Karim Lakhani (Harvard)
"How We Cite: Quality and Inequality in Science."
(Science of Science)
Citations and metrics derived from them increasingly dictate all aspects of science, from what
gets funded to who gets hired. But what do citations counts actually measure? Authors may cite
for a variety of reasons, including purely rhetorical ones, but how these motives affect aggregate
citation counts is poorly understood. Here, we use a large-scale survey of authors of scientific
papers, asking them about specific citation decisions. Using responses from nearly 10K authors
from all areas of science, we find that most citations are rhetorical in nature, and many are only
skimmed. Authors "invest" reading effort primarily into famous papers, and end up being influenced
primarily by them, whereas obscure papers are cited more rhetorically. An experiment embedded in
the survey shows that low citation counts cause scientists to perceive those papers as being of
lower quality. Taken together, the results suggest a model of reading and citing in which famous
papers matter even more than their already high citation counts indicate. (In Review)
Misha Teplitskiy (Michigan), Eamon Duede (UChicago), Michael Menietti (Harvard), and Karim Lakhani (Harvard)
When Technology Transforms Society: Considering the Societal and Ethical Impacts of Quantum Computing and AI.
Quantum computing and artificial intelligence are currently making significant technical progress, with commensurate interest from the public, media outlets, funding agencies, and corporate partners. Stakeholders frequently point to the potential of these technologies to “transform society,” but what does this mean, practically? Should we, as researchers, anticipate the social, political, and ethical consequences of our work and steer our research programs accordingly? Can we draw from scholarship in the social sciences and the humanities to inform understanding of the distributional impacts of our programs? This workshop will explore these questions and develop collaborations across disciplines, institutions, and key stakeholders who may be able to help responsibly steer the evolution of these revolutionary technologies in ethical and socially beneficial ways.
Co-Organized by Daniel Bowring (Fermilab), Chihway Chang (UChicago), Eamon Duede (UChicago), and Brian Nord (Fermilab). Funding provided by the Center for Data and Computing at the University of Chicago and the Kavli Foundation