Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society
- URL: http://arxiv.org/abs/2506.05605v1
- Date: Thu, 05 Jun 2025 21:35:24 GMT
- Title: Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society
- Authors: Julia Barnett, Kimon Kieslich, Jasmine Sinchai, Nicholas Diakopoulos,
- Abstract summary: We conduct a systematic literature review on the use of scenario building methods in computer science.<n>We aim to uncover how scenarios are used in computing literature, focusing on the rationale for why scenarios are used.
- Score: 2.981139602986498
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
Related papers
- Mapping Technological Futures: Anticipatory Discourse Through Text Mining [1.998140290950519]
This study examines anticipatory discourse surrounding technological futures by analysing 1.5 million posts from 400 key opinion leaders (KOLs) published on the X platform (from 2021 to 2023)<n>Using advanced text mining techniques, including BERTopic modelling, sentiment, emotion, and attitude analyses, the research identifies 100 distinct topics reflecting anticipated tech-driven futures.
arXiv Detail & Related papers (2025-03-25T15:20:15Z) - Networking Systems for Video Anomaly Detection: A Tutorial and Survey [55.28514053969056]
Video Anomaly Detection (VAD) is a fundamental research task within the Artificial Intelligence (AI) community.<n>With the advancements in deep learning and edge computing, VAD has made significant progress.<n>This article offers an exhaustive tutorial for novices in NSVAD.
arXiv Detail & Related papers (2024-05-16T02:00:44Z) - A Disruptive Research Playbook for Studying Disruptive Innovations [11.619658523864686]
We propose a research playbook with the goal of providing a guide to formulate compelling and socially relevant research questions.
We show it can be used to question the impact of two current disruptive technologies: AI and AR/VR.
arXiv Detail & Related papers (2024-02-20T19:13:36Z) - Predictable Artificial Intelligence [77.1127726638209]
This paper introduces the ideas and challenges of Predictable AI.<n>It explores the ways in which we can anticipate key validity indicators of present and future AI ecosystems.<n>We argue that achieving predictability is crucial for fostering trust, liability, control, alignment and safety of AI ecosystems.
arXiv Detail & Related papers (2023-10-09T21:36:21Z) - Generative AI [20.57872238271025]
"generative AI" refers to computational techniques that are capable of generating seemingly new, meaningful content.
The widespread diffusion of this technology with examples such as Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work and communicate with each other.
arXiv Detail & Related papers (2023-09-13T08:21:59Z) - Literature Review: Computer Vision Applications in Transportation
Logistics and Warehousing [58.720142291102135]
Computer vision applications in transportation logistics and warehousing have a huge potential for process automation.
We present a structured literature review on research in the field to help leverage this potential.
arXiv Detail & Related papers (2023-04-12T17:33:41Z) - Selected Trends in Artificial Intelligence for Space Applications [69.3474006357492]
This chapter focuses on differentiable intelligence and on-board machine learning.
We discuss a few selected projects originating from the European Space Agency's (ESA) Advanced Concepts Team (ACT)
arXiv Detail & Related papers (2022-12-10T07:49:50Z) - Documenting use cases in the affective computing domain using Unified
Modeling Language [0.0]
There is no standard methodology for use case documentation covering the context of use, scope, functional requirements and risks of an AI system.
Our approach builds upon an assessment of use case information needs documented in the research literature and the recently proposed European regulatory framework for AI.
From this assessment, we adopt and adapt the Unified Modeling Language (UML), which has been used in the last two decades mostly by software engineers.
arXiv Detail & Related papers (2022-09-19T10:04:18Z) - OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer
Learning for Telepresence Robotics [124.08684545010664]
Scene graph generation from images is a task of great interest to applications such as robotics.
We propose an initial approximation to a framework called Ontology-Guided Scene Graph Generation (OG-SGG)
arXiv Detail & Related papers (2022-02-21T13:23:15Z) - Individual Explanations in Machine Learning Models: A Case Study on
Poverty Estimation [63.18666008322476]
Machine learning methods are being increasingly applied in sensitive societal contexts.
The present case study has two main objectives. First, to expose these challenges and how they affect the use of relevant and novel explanations methods.
And second, to present a set of strategies that mitigate such challenges, as faced when implementing explanation methods in a relevant application domain.
arXiv Detail & Related papers (2021-04-09T01:54:58Z) - On the Convergence of Artificial Intelligence and Distributed Ledger
Technology: A Scoping Review and Future Research Agenda [0.0]
Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) lead to lively debates in academia and practice.
DLT has the potential to create consensus over data among a group of participants in uncertain environments.
arXiv Detail & Related papers (2020-01-29T18:57:27Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.