ORIGen 2025 : The First Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models

The First Workshop on Optimal Reliance and Accountability in Interactions
with Generative Language Models (*ORIGen*) will be held in conjunction with
the Second Conference on Language Modeling (COLM) at the Palais des Congrès
in Montreal, Quebec, Canada, on October 10, 2025!

With the rapid integration of generative AI, exemplified by large language
models (LLMs), into personal, educational, business, and even governmental
workflows, such systems are increasingly being treated as “collaborators”
with humans. In such scenarios, underreliance or avoidance of AI assistance
may obviate the potential speed, efficiency, or scalability advantages of a
human-LLM team, but simultaneously, there is a risk that subject matter
non-experts may overrely on LLMs and trust their outputs uncritically, with
consequences ranging from the inconvenient to the catastrophic. Therefore,
establishing optimal levels of reliance within an interactive framework is a
critical open challenge as language models and related AI technology rapidly
advances.

* What factors influence overreliance on LLMs?
* How can the consequences of overreliance be predicted and guarded against?
* What verifiable methods can be used to apportion accountability for the
outcomes of human-LLM interactions?
* What methods can be used to imbue such interactions with appropriate levels
of “friction” to ensure that humans think through the decisions they make
with LLMs in the loop?

The ORIGen workshop provides a new venue to address these questions and more
through a multidisciplinary lens. We seek to bring together broad
perspectives from AI, NLP, HCI, cognitive science, psychology, and education
to highlight the importance of mediating human-LLM interactions to mitigate
overreliance and promote accountability in collaborative human-AI
decision-making.

Submissions are due June 20, 2025. Please see our call for papers [1] for
more!

[1] https://origen-workshop.github.io/submissions/