Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society

2025-06-05

AI Summary

This study addresses the lag in applying scenario-building methods within computer science—particularly the lack of systematic exploration regarding the societal impacts of emerging technologies. We conducted a systematic literature review (SLR) and qualitative content analysis of 59 studies published over the past decade. Our coding and framework modeling reveal a pervasive absence of participatory design mechanisms in current practice, and identify three dominant application patterns: technological risk anticipation, ethical alignment, and public engagement—each accompanied by critical methodological gaps. Building on these findings, we propose an innovative methodology for inclusive technology governance, optimizing scenario-building to shift from a purely technical orientation toward a pluralistic, co-constructive governance tool. This reframing advances both the theoretical foundations and practical implementation of anticipatory socio-technical impact assessment—especially for AI and related emerging technologies.

Technology Category

• Philosophy and Ethics of AI: Societal Impact of AI
• Humans and AI: Understanding People, Theories, Concepts and Methods
• Game Theory and Economic Paradigms: Mechanism Design

Application Category

• Responsible Web: Social and technical mechanisms of refusal for web technologies and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Scenario building is an established method to anticipate the future of emerging technologies. Its primary goal is to use narratives to map future trajectories of technology development and sociotechnical adoption. Following this process, risks and benefits can be identified early on, and strategies can be developed that strive for desirable futures. In recent years, computer science has adopted this method and applied it to various technologies, including Artificial Intelligence (AI). Because computing technologies play such an important role in shaping modern societies, it is worth exploring how scenarios are being used as an anticipatory tool in the field -- and what possible traditional uses of scenarios are not yet covered but have the potential to enrich the field. We address this gap by conducting a systematic literature review on the use of scenario building methods in computer science over the last decade (n = 59). We guide the review along two main questions. First, we aim to uncover how scenarios are used in computing literature, focusing especially on the rationale for why scenarios are used. Second, in following the potential of scenario building to enhance inclusivity in research, we dive deeper into the participatory element of the existing scenario building literature in computer science.

Problem

• Explore how scenario methods anticipate computing technologies' societal impact
• Identify gaps in traditional scenario uses for enriching computing research
• Analyze participatory elements in scenario building for inclusive computing futures

Innovation

• Systematic review of scenario methods in computing
• Exploring AI futures with narrative-based scenarios
• Enhancing inclusivity via participatory scenario building