Large Language Models for the History, Philosophy, and Sociology of Science
(Workshop)*
April 2-4, 2025, Technische Universität Berlin, Germany
Organized jointly by: Gerd Graßhoff (HU Berlin), Arno Simons (TU Berlin),
Adrian Wüthrich (TU Berlin), and Michael Zichert (TU Berlin)
Summary
We invite contributions to our workshop on using large language models (LLMs)
in the history, philosophy, and sociology of science (HPSS). The workshop will
focus on exploring use cases and proposals for how, and to what extent, LLMs
might help overcome long-standing challenges in studies of how science works.
The event will take place from April 2–4, 2025, at Technische Universität
Berlin, Germany. Attendance (online and on site) will be free and open to the
public but registration will be required. To contribute a talk, please submit
abstracts of 300–600 words by December 31, 2024, to [email protected].
Workshop topics
Computational approaches to the history of science are in the process of
establishing themselves among the standard repertoire of tools in the field and
we have seen remarkable successes in their application already. Subfields of
sociology of science have focused, since long, on quantitative methods such as
bibliometrics and scientometrics. More recently, philosophy of science has
experienced a shift towards allowing more empirical approaches including
large-scale algorithmic analyses of scientific or methodological concepts.
Computational tools can not only help reduce the workload in traditional
research in these fields but, more importantly, also open up new avenues which
to explore would otherwise be hopeless.
Analyses of co-occurrences and word frequencies as well as more advanced
techniques such as topic modeling have helped go beyond identifying only
structural features of scientific activities and began scratching the surface
of semantics. However, a deeper understanding of scientific concepts, the
structure of scientific arguments, and the process of knowledge transformation
and spread have remained formidable challenges for computational approaches in
the mentioned fields.
With the advent of LLMs this might change now. Natural language processing and
machine learning have made a spectacular leap forward in their attempt to
capture and analyze meaning and grammatical structures of texts. This promises
that LLMs can help HPSS researchers meet the aforementioned challenges.
However—besides general issues such as opacity, bias and interpretability—the
use of LLMs for HPSS is likely to face unique obstacles arising from the
specialized nature of scientific language as well as the specific perspectives
and objectives of HPSS. It will be the main goal of this workshop to see how,
given these obstacles, the most recent advances in LLM development can help
overcome long-standing challenges in HPSS.
Accordingly, the workshop will address two key themes, with the goal of
synthesizing them over the course of the event. On one hand, contributions
should articulate the specific needs and desiderata of HPSS researchers—what
they hope LLMs can achieve for their work. On the other hand, the current state
of LLM development should be critically examined to determine to what extent
these research goals are becoming attainable. Ideally, contributions will
address both these objectives, though submissions focused on only one of them
are also welcome.
We particularly encourage contributions that focus on:
Use cases that demonstrate how LLMs can help resolve current issues in HPSS
Examples of how LLMs allow researchers to ask and answer new types of questions
in HPSS
How new types of sources and data, made analyzable through LLMs, contribute to
novel insights in HPSS research
We look for contributions that help resolve questions like these:
How can LLMs help gain new perspectives on long-standing problems in HPSS such
as determining the relevant contexts of knowledge claims, the dynamics of
scientific controversies, problems of incommensurability, and generalizability
of case studies?
How can LLMs handle the specialized language of scientific texts, including
technical jargon, citations, and mathematical formulas?
How can LLMs bridge the gap between qualitative and computational methods and
help overcome their limitations?
How can LLMs be integrated into existing theoretical and methodological
frameworks in HPSS, or how should these frameworks evolve to accommodate
LLM-based analysis?
How can we evaluate the validity of results generated by LLMs, given their
opacity?
How can LLMs account for the temporal development of scientific language and
knowledge over time?
Format and practical information
The workshop will take place from April 2-4, 2025 at Technische Universität
Berlin. The program will consist of an invited keynote and contributed short
talks (15+10 min) as well as additional sessions for discussions. Attendance
(online and on site) will be free and open to the public but registration will
be required. Information on this will follow closer to the date.
To contribute a talk, please send an abstract of your planned contribution of
300-600 words by e-mail to [email protected] by December 31, 2024. We
encourage every contributor to present on site and to participate in the whole
workshop program. In exceptional cases, we will offer the possibility to
present remotely.
Participation of underrepresented groups is particularly welcome, and we may be
able to offer financial support to cover travel costs for contributing authors
in exceptional cases. Please indicate in your submission if you would like to
apply for financial support.
We plan to publish the slides, videos, and abstracts on a suitable platform. We
also plan to write a report on the workshop and on the perspectives resulting
from it.
Stable workshop URL: https://www.tu.berlin/hps-mod-sci/workshop-llms-for-hpss
* The workshop is funded by the European Union through the project “Network
Epistemology in Practice (NEPI)” (ERC Consolidator Grant, Project No.
101044932). Views and opinions expressed are however those of the organizers
only and do not necessarily reflect those of the European Union or the European
Research Council. Neither the European Union nor the granting authority can be
held responsible for them.
--
Arno Simons
Technische Universität Berlin
Institut für Philosophie, Literatur-, Wissenschafts- und Technikgeschichte
https://www.tu.berlin/hps-mod-sci/arno-simons
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