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<h3
id="large-language-models-for-the-history-philosophy-and-sociology-of-science-workshop">Large
Language Models for the History, Philosophy, and Sociology of
Science (Workshop)</h3>
<p>April 2-4, 2025, Technische Universität Berlin, Germany</p>
<p>Organized by: Gerd Graßhoff, Arno Simons, Adrian Wüthrich, and
Michael Zichert</p>
<h4 id="summary">Summary</h4>
<p>We invite contributions to our workshop on <strong>using large
language models (LLMs) in the history, philosophy, and
sociology of science (HPSS).</strong> 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 <strong>April
2–4, 2025, at Technische Universität Berlin</strong>, Germany.<a
class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>
Attendance (online and on site) will be <strong>free and open
to the public</strong> but registration will be required. To
contribute a talk, please submit <strong>abstracts of 300–600
words by December 31, 2024</strong>, to <a
href="mailto:arno.simons@tu-berlin.de"
class="moz-txt-link-freetext">arno.simons@tu-berlin.de</a>.</p>
<h4 id="workshop-topics">Workshop topics</h4>
<p><strong>Computational approaches</strong> to the <strong>history
of science</strong> 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 <strong>sociology of science</strong>
have focused, since long, on quantitative methods such as
bibliometrics and scientometrics. More recently, <strong>philosophy
of science</strong> 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 <strong>open
up new avenues</strong> which to explore would otherwise be
hopeless.</p>
<p>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 <strong>semantics</strong>.
However, a deeper understanding of scientific concepts, the
structure of scientific arguments, and the process of knowledge
transformation and spread have remained <strong>formidable
challenges</strong> for computational approaches in the
mentioned fields.</p>
<p>With the <strong>advent of LLMs</strong> 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 <strong>unique obstacles</strong> 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.</p>
<p>Accordingly, the workshop will address <strong>two key themes</strong>,
with the goal of synthesizing them over the course of the event.
On one hand, contributions should articulate <strong>the
specific needs and desiderata of HPSS researchers</strong>—what
they hope LLMs can achieve for their work. On the other hand, <strong>the</strong>
<strong>current state of LLM development</strong> 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.</p>
<p>We particularly encourage contributions that focus on:</p>
<ul>
<li>Use cases that demonstrate how LLMs can help <strong>resolve
current issues</strong> in HPSS<br>
</li>
<li>Examples of how LLMs allow researchers to <strong>ask and
answer new types of questions</strong> in HPSS<br>
</li>
<li>How <strong>new types of sources and data</strong>, made
analyzable through LLMs, contribute to novel insights in HPSS
research</li>
</ul>
<p>We look for contributions that help resolve questions like
these:</p>
<ul>
<li>How can LLMs help gain <strong>new perspectives on
long-standing problems</strong> in HPSS such as determining
the relevant contexts of knowledge claims, the dynamics of
scientific controversies, problems of incommensurability, and
generalizability of case studies?<br>
</li>
<li>How can LLMs handle the <strong>specialized language of
scientific texts</strong>, including technical jargon,
citations, and mathematical formulas?<br>
</li>
<li>How can LLMs <strong>bridge the gap between qualitative and
computational methods</strong> and help overcome their
limitations?<br>
</li>
<li>How can LLMs be <strong>integrated into existing
theoretical and methodological frameworks</strong> in HPSS,
or how should these frameworks evolve to accommodate LLM-based
analysis?<br>
</li>
<li>How can we <strong>evaluate</strong> the validity of
results generated by LLMs, given their opacity?<br>
</li>
<li>How can LLMs account for the <strong>temporal development</strong>
of scientific language and knowledge over time?</li>
</ul>
<h4 id="format-and-practical-information">Format and practical
information</h4>
<p>The workshop will take place from <strong>April 2-4, 2025</strong>
at <strong>Technische Universität Berlin</strong>. 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 <strong>free and open
to the public</strong> but registration will be required.
Information on this will follow closer to the date.</p>
<p><strong>To contribute a talk</strong>, please send an <strong>abstract</strong>
of your planned contribution <strong>of 300-600 words by e-mail</strong>
to <a href="mailto:arno.simons@tu-berlin.de"
class="moz-txt-link-freetext">arno.simons@tu-berlin.de</a> by
<strong>December 31, 2024</strong>. 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.</p>
<p><strong>Participation of underrepresented groups</strong> 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.</p>
<p>We plan to <strong>publish the slides, videos, and abstracts</strong>
on a suitable platform. We also plan to write a report on the
workshop and on the perspectives resulting from it.</p>
<section class="footnotes" role="doc-endnotes">
<hr>
<ol>
<li id="fn1" role="doc-endnote">
<p>The workshop is funded by the European Union through the
project “<strong>Network Epistemology in Practice (NEPI)</strong>”
(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.<a class="footnote-back"
role="doc-backlink">↩︎</a></p>
</li>
</ol>
</section>
</div>
<p></p>
<pre class="moz-signature" cols="72">--
Adrian Wuethrich
Technische Universitaet Berlin
Institut fuer Philosophie, Literatur-, Wissenschafts- und Technikgeschichte
Raum H 2534 / Sekr. H 23
Strasse des 17. Juni 135
D-10623 Berlin
<a class="moz-txt-link-abbreviated" href="mailto:adrian.wuethrich@tu-berlin.de">adrian.wuethrich@tu-berlin.de</a>
+49 30 314 24069
<a class="moz-txt-link-freetext" href="https://www.tu.berlin/go214591/">https://www.tu.berlin/go214591/</a></pre>
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