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Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society
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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.
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Cited by 2 Pith papers
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Informing AI Policy Assessment using Large-Scale Simulation of Interventions
A genetic algorithm exploring billions of policy combinations, scored by LLM-evaluated harm mitigation, expert cost, and participatory ratings, identifies viable AI policy options under different weighting schemes.
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