Frictionless Futures, Invisible Conflicts: The Case for Scenario Methodology in Human-AI IS Research
Journal
International Conference on Information Systems (ICIS)
Type
conference paper
Date Issued
2026-12-13
Author(s)
Abstract
Information systems (IS) research has established AI as a delegation-capable organizational actor with normative consequences. Yet this body of work is methodologically present-bound: it explains how humans and AI coordinate in existing arrangements, not what competing arrangements are possible before design and governance decisions foreclose them. IS has opened epistemological space for researching not-yet-accessible phenomena, but without specifying a method. I argue that scenario methodology fills this gap: not as a management tool, but as a research method that structurally preserves contested stakeholder positions, unresolved normative conflicts, and structured uncertainty. I call this epistemic friction. A comparative corpus study of 4,320 human-authored and GPT-generated scenarios shows what is lost when friction disappears: high-certainty, low-contention, technology-centric futures. Strategically appealing. Analytically impoverished. This pattern illustrates precisely what IS research on human-AI coexistence cannot afford to reproduce.
Language
English
Keywords
scenario method
Artificial Intelligence
Large Language Models (LLMs)
HSG Classification
contribution to scientific community
Refereed
No
Number
2026
Event Title
International Conference on Information Systems (ICIS)
Event Location
Lisbon, Portugal
Event Date
December 13-16, 2026
Subject(s)
Division(s)
File(s)![Thumbnail Image]()
Name
ICIS2026_DianaKozachek 2.pdf
Size
752.59 KB
Format
Adobe PDF
Checksum (MD5)
f8b590b9d12286c151751ea9e17528de