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Dear colleagues,<br>
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<p> <br>
for the <a moz-do-not-send="true"
href="https://2022.hci.international/index.html">24th
International Conference on Human-Computer Interaction</a>
on 26 June - 1 July 2022 (HCII 2022, virtual) we invite you to
submit your contributions to our panel<br>
<br>
"AI-in-the-loop" - Reconfiguring HCI for AI development<br>
<br>
An important paradigm in the development of interactive AI
systems is “humans-in-the-loop” as trainers in machine
learning (see <a class="moz-txt-link-freetext"
href="https://humansintheloop.org/" moz-do-not-send="true">https://humansintheloop.org/</a>)
or as evaluators of results or predictions in unsupervised
machine learning, primarily optimizing the ML model. Even
though dominant, this paradigm however does not adequately
represent all approaches made in AI. What is not yet prominent
in the debate are alternative HCI paradigms in AI development,
e.g. the option to put AI in the loop for primarily supporting
human analyses, which might still include mechanisms to
enhancing AI performance; this we are currently exploring in
the D-WISE project (<a class="moz-txt-link-freetext"
href="https://www.dwise.uni-hamburg.de/en.html"
moz-do-not-send="true">https://www.dwise.uni-hamburg.de/en.html</a>).
In our project, qualitative discourse analyses, in the
tradition of the sociology of knowledge, get support by
automated analyses of multimodal materials for “filtering”
(e.g. theoretical sampling, annotating, development of
categories, simultaneous data expansion) relevant materials:
AI is in the loop of human analysis and supports human
decision making. At the same time, in this mode of
human-computer interaction, we are not only motivated to
improve human analyses; we aim to constantly improve the
representations in the AI systems in the loop of our system,
creating a win-win situation for both human understanding and
training of the AI system.<br>
<br>
“Humans-in-the-loop” and “AI-in-the-loop” are paradigms of
human and computer interaction with rather contradicting ideas
of how AI and human analyses relate to each other. Thus far,
AI-in-the-loop is mostly referred to as an idea but rarely
developed as a paradigm in AI research. This panel is
interested in bringing together approaches that set
AI-in-the-loop of human analytics, rather than operating the
other way round. We wish to learn about different ways of
putting AI-in-the-loop for human analyses and the different
modes of how human-computer interaction is arranged.<br>
<br>
Accepted submissions will be included in the conference
proceedings to be published by Springer in the Lecture Notes
in Computer Science (LNCS) or Lecture Notes in Artificial
Intelligence (LNAI) series.<br>
<br>
<b> Important dates:</b><br>
Submission of Abstracts (at least 500 words), 31 Oct 2021<br>
Submission of Full Papers (12 pages but no less than 10 and no
more than 20 pages), 10 Dec 2021<br>
Information on approved papers, 31 Dec 2021<br>
Camera-ready version, 4 Feb 2022<br>
<br>
<b> Convenors of the panel:</b><br>
Gertraud Koch, Institute of Anthropological Studies in Culture
and History, University of Hamburg<br>
Chris Biemann, Language Technology Group, University of
Hamburg<br>
with collaboration of: Dr. Teresa Stumpf, Alejandra Tijerina
García, Isabel Eiser, Tim Fischer, Florian Schneider</p>
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