Humanist Discussion Group, Vol. 38, No. 377.
Department of Digital Humanities, University of Cologne
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www.dhhumanist.org
Submit to: humanist@dhhumanist.org
[1] From: Alex Gekker <gekker.alex@gmail.com>
Subject: PhD on Interfaces of Intelligence: How Generative AI Reshapes Knowledge, Media, and Interpretation (139)
[2] From: lustre network <lustre.network@mailbox.lboro.ac.uk>
Subject: Unlocking Digital Archives with AI: Explore the LUSTRE Project Special Issue (60)
--[1]------------------------------------------------------------------------
Date: 2025-02-27 07:09:41+00:00
From: Alex Gekker <gekker.alex@gmail.com>
Subject: PhD on Interfaces of Intelligence: How Generative AI Reshapes Knowledge, Media, and Interpretation
Dear Colleagues,
We are recruiting a PhD for a joint project of Erik Borra, Bernhard Rieder
and me at the Media Studies department, University of Amsterdam. More
details below, but the TL;DR is:
The deadline for submission is *March 23rd*, the position will start in
October, and one applies with a research proposal of 800-1000 words
(excluding references) that describes your topic and the main conceptual
lens that would inform your project. More information and submission here:
https://werkenbij.uva.nl/en/vacancies/phd-on-interfaces-of-intelligence-how-
generative-ai-reshapes-knowledge-media-and-interpretation-netherlands-13848
_PhD Position: How AI is Reshaping Knowledge Production_
Models (LLMs) and other generative AI systems integrate into everyday
practices. Society is transitioning from an information retrieval paradigm,
where search engines provide specific sources relevant to specific queries,
to an interrogation and interpretation paradigm, in which knowledge is
embedded within AI models through extensive, often opaque training
processes and configurations. AI is also increasingly integrated into
agentic systems - designed for specific contexts, goals, and degrees of
autonomy - reconfiguring how knowledge is produced, validated, and
operationalized across domains such as journalism, research, and education.
This shift raises critical questions about authority, transparency, and the
evolving role of human expertise in AI-mediated workflows.
To critically assess and learn from such shifts, our project takes a
two-pronged approach: first, we examine how research methods are embedded
within AI tools, adopting a digital methods perspective to explore their
affordances and limitations. Second, we analyze how AI-driven software
changes interfaces, influencing how users access and interact with
knowledge. Both approaches aim to understand how knowledge is constructed,
accessed, and made usable - both in digital research and everyday digital
interactions.
_This is what you will be doing_
As a PhD in the project, you will pursue your own research agenda that
intersects with that of the PIs, and falls under one of the following broad
categories:
- Epistemic shifts in generative AI – How does GenAI reshape processes
of knowledge validation, credibility, and facticity? How do these models
affect established knowledge gatekeepers institutions? How do different
modes and modalities of GenAI shape its contexts of use?
- Workflow transformations in generative AI – How does GenAI reshape
professional routines and decision-making in knowledge-intensive
domains?
How do AI-driven agentic systems, designed with specific contexts,
capabilities, and goals, redefine collaboration and expertise? How
do they
integrate into and redefine existing software interfaces?
Your tasks and responsibilities:
- submission of a PhD thesis within the period of appointment;
- participating in meetings of the project research group and developing
a shared database;
- publishing one single-authored, peer reviewed article;
- presenting intermediate research results at workshops and conferences;
- organising knowledge dissemination activities;
- participation in the Research School and Faculty of Humanities PhD
training programmes.
- (co-)teaching courses at BA-level in the second and third year of the
appointment (maximum 0,2 fte per year).
_This is what we ask of you_
Candidates need to have the following qualifications:
- a completed Master's degree in media and communication studies,
critical artificial intelligence, science and technology studies.
You may
apply if you have not yet completed your Master's degree only if you
provide a signed letter from your supervisor stating that you will
graduate
before 1 September 2025;
- excellent research skills demonstrated by an outstanding Master's
thesis and a demonstrable capacity to develop a track record of
publishing
in high-ranking journals and/or with leading presses;
- a strong cooperative attitude and willingness to engage in
collaborative research;
- enthusiasm for communicating academic research to non-academic
audiences;
- good command of English
We are looking for a PhD candidate who can critically engage with
generative AI while also exploring its practical applications. The ideal
candidate is neither solely focused on critiquing AI from a distance nor
unreflectively applying it without questioning its implications. Instead,
we seek someone who combines critical analysis with hands-on
exploration—someone who can interrogate the epistemic, social, and
technical dimensions of AI while also experimenting with its affordances in
digital research methods and interface studies. Please note that if you
already hold a doctorate/PhD or are working towards obtaining a similar
degree elsewhere, you will not be admitted to a doctoral programme at the
UvA.
The candidate should be comfortable working across disciplines, bridging
media and communication studies, critical artificial intelligence, and
science and technology studies. The candidate should have an analytical yet
open-minded approach, willing to engage with both the strengths and
limitations of AI in knowledge production, dissemination, and professional
workflows. Strong expository writing skills are essential, both for
effectively commanding large language models and for producing clear,
rigorous academic output. Prior experience with digital methods, such as
data scraping and visualization, as well as a working knowledge of
foundation models (understanding of their training processes and/or
prompting), is highly desirable. While not mandatory, basic proficiency in
programming in Python for digital analysis would be a plus.
_This is what we offer you_
- A salary of between €2.901 - €3.707 p.m; additional social benefits
(more information available here:
https://werkenbij.uva.nl/en/about-working-at-the-UvA);
- PhD candidates receive a tuition fee waiver;
- PhD candidates have free access to courses offered by the Graduate
School of Humanities and the Dutch National Research Schools;
- excellent possibilities for further professional development and
education;
- an inspiring academic and international work environment in the heart
of Amsterdam;
- an enthusiastic and professional academic team.
Kind regards,
Alex.
Alex Gekker, PhD. Assistant Professor in Digital Research Methods, Media
Studies, University of Amsterdam.
Profile and publications <https://orcid.org/0000-0001-6042-2086> //
a.gekker@uva.nl // tw: @AlexGekker <http://twitter.com/alexgekker> //
mastodon @gekker@aoir.social <https://aoir.social/@gekker>
--[2]------------------------------------------------------------------------
Date: 2025-02-26 14:44:32+00:00
From: lustre network <lustre.network@mailbox.lboro.ac.uk>
Subject: Unlocking Digital Archives with AI: Explore the LUSTRE Project Special Issue
Dear all,
I am delighted to share that the special issue on "When data turns into
archives: making digital records more accessible with AI" has just been
published in AI & Society!
Developed as a key output of the LUSTRE project—funded by the Arts and
Humanities Research Council (AHRC)—this collection addresses the unique
challenges and opportunities AI offers in unlocking archival data within the
government sector and beyond.
The articles in this issue provide new interdisciplinary theoretical
interpretations, apply research methodologies to diverse case studies, and
explore the current and future role of AI in working with data and digital
archives. Contributions span digital humanities, archival studies, cultural
heritage studies, critical data studies, and computer science, with insights
from both established experts and early-career professionals.
Highlights of this special issue include the following articles:
* AI to review government records: New work to unlock historically
significant digital records<https://doi.org/10.1007/s00146-025-02221-0>, by
David Canning (UK Cabinet Office) and myself;
* Developing computer vision and machine learning strategies: Innovative
approaches to unlock government-created
records<https://doi.org/10.1007/s00146-025-02231-y>, by Greg Jansen & Richard
Marciano;
* Improving the diversity of archival collections with AI: Opportunities,
risks, and solutions to ensure equitable
representation<https://link.springer.com/article/10.1007/s00146-025-02222-z>, by
myself and my wonderful team!
Explore the full collection here:
https://link.springer.com/collections/eabccfhhbd
This special issue is an essential resource for anyone interested in how AI can
shape the future of archives, data, and cultural heritage. Join the conversation
and discover how cutting-edge research is connecting policy makers, computer
scientists, digital humanists, and GLAM professionals.
Learn more about the LUSTRE project here: https://lustre-network.net/
Feel free to repost the announcements I have shared on:
* X/ Twitter (https://twitter.com/lisejaillant)
* Bluesky (https://bsky.app/profile/lisejaillant.bsky.social)
* Linkedin (https://uk.linkedin.com/in/lise-jaillant-79378252)
More articles to be announced soon!
Best regards,
Professor Lise Jaillant
School of Social Sciences and Humanities | Loughborough University, UK
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