[emcai] "Outlasting ‘disruption’: Empirical perspectives on practical reasoning with AI" - panel at EASST 2026 conference

[Jakub Mlynář]

Dear colleagues,

We would like to invite you to submit abstracts to our panel “*Outlasting
‘disruption’: Empirical perspectives on practical reasoning with AI*”,
scheduled for the EASST 2026 conference in Kraków (Poland), 8–11 September.
The panel welcomes empirical investigations – including EM/CA – that shed
light on the lived difficulties of working with automated systems and
contribute to ongoing debates on the future of work, human–machine
collaboration, and the societal implications of AI-based technologies.
Details of the panel’s scope and aims are attached and included below.

Abstracts can be submitted *until 9 March* via:
*https://nomadit.co.uk/conference/easst2026/p/18164
<https://nomadit.co.uk/conference/easst2026/p/18164>*

More information about the conference is available here:
*https://easst.net/conference/easst2026/easst2026-home/
<https://easst.net/conference/easst2026/easst2026-home/>*

We look forward to receiving your submissions.

Kind regards,

Jakub Mlynář & Dipanjan Saha


===


*Outlasting ‘disruption’: Empirical perspectives on practical reasoning
with AI (panel P136)*

The inflationary narratives surrounding the achievements of the ‘new’
Artificial Intelligence (AI), often propagated by the corporations
developing them, hinder our understanding of the true potentials of these
technologies. To get a better grasp on their rapid advancements and their
future consequences for various forms of work, we need to understand how
they are made relevant to their specific contexts of use. While often
presented as seamless or autonomous tools, these technologies are
frequently messy, unpredictable, and prone to generating outputs that users
find ambiguous, problematic, or simply incorrect. This creates a critical
gap between the AI's prescribed operation and the practical, situated work
required to make it useful. Attending to the broad sphere of activities
that goes on to make AI work provides a more measured and empirically
grounded basis for evaluating their achievements and limitations in the
world.

This panel invites empirical investigations that allow us to uncover the
lived difficulties of working with these automated systems. We welcome
contributions exploring, but not limited to, the following questions:

   - How do a wide range of users, from domain experts to laypersons,
   actually manage and make sense of the results produced by these
   technologies in practice?
   - What mundane methods and practical reasoning skills do people employ
   to evaluate, trust, or challenge AI’s outputs?
   - How can we empirically study the multiplicity of reasoning styles and
   ad-hoc procedures users adopt when evaluating AI-generated results?
   - What does attending to these practical difficulties reveal about the
   actual, rather than promised, capabilities of automation and the necessity
   of situated human skill?


By focusing on the ‘how’ of AI’s use, this panel will contribute to the
ongoing debates surrounding the future of work, human-machine
collaboration, and the societal implications of these powerful technologies.
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