Eliciting the Double-edged Impact of Digitalisation: a Case Study in Rural Areas

• URL: http://arxiv.org/abs/2306.05078v1
• Date: Thu, 8 Jun 2023 10:01:35 GMT
• Title: Eliciting the Double-edged Impact of Digitalisation: a Case Study in Rural Areas
• Authors: Alessio Ferrari, Fabio Lepore, Livia Ortolani, Gianluca Brunori
• Abstract summary: This paper reports a case study about the impact of digitalisation in remote mountain areas, in the context of a system for ordinary land management and hydro-geological risk control. We highlight the higher stress due to the excess of connectivity, the partial reduction of decision-making abilities, and the risk of marginalisation for certain types of stakeholders. Our study contributes to the literature with: a set of impacts specific to the case, which can apply to similar contexts; an effective approach for impact elicitation; and a list of lessons learned from the experience.
• Score: 1.8707139489039097
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Designing systems that account for sustainability concerns demands for a better understanding of the \textit{impact} that digital technology interventions can have on a certain socio-technical context. However, limited studies are available about the elicitation of impact-related information from stakeholders, and strategies are particularly needed to elicit possible long-term effects, including \textit{negative} ones, that go beyond the planned system goals. This paper reports a case study about the impact of digitalisation in remote mountain areas, in the context of a system for ordinary land management and hydro-geological risk control. The elicitation process was based on interviews and workshops. In the initial phase, past and present impacts were identified. In a second phase, future impacts were forecasted through the discussion of two alternative scenarios: a dystopic, technology-intensive one, and a technology-balanced one. The approach was particularly effective in identifying negative impacts. Among them, we highlight the higher stress due to the excess of connectivity, the partial reduction of decision-making abilities, and the risk of marginalisation for certain types of stakeholders. The study posits that before the elicitation of system goals, requirements engineers need to identify the socio-economic impacts of ICT technologies included in the system, as negative effects need to be properly mitigated. Our study contributes to the literature with: a set of impacts specific to the case, which can apply to similar contexts; an effective approach for impact elicitation; and a list of lessons learned from the experience.

Related papers

• Estimating Causal Effects of Text Interventions Leveraging LLMs [7.2937547395453315]
  This paper proposes a novel approach to estimate causal effects using text transformations facilitated by large language models (LLMs) Unlike existing methods, our approach accommodates arbitrary textual interventions and leverages text-level classifiers with domain adaptation ability to produce robust effect estimates against domain shifts. This flexibility in handling various text interventions is a key advancement in causal estimation for textual data, offering opportunities to better understand human behaviors and develop effective policies within social systems.
  arXiv  Detail & Related papers  (2024-10-28T19:19:35Z)
• The Impact of Human Aspects on the Interactions Between Software Developers and End-Users in Software Engineering: A Systematic Literature Review [10.307654003138401]
  We present a systematic review of studies on human aspects affecting developer-user interactions. We identified various human aspects affecting developer-user interactions in 46 studies. Our findings suggest the importance of leveraging positive effects and addressing negative effects in developer-user interactions.
  arXiv  Detail & Related papers  (2024-05-08T03:38:36Z)
• A Scalable and Automated Framework for Tracking the likely Adoption of Emerging Technologies [3.4530027457862]
  This paper presents a scalable and automated framework for tracking likely adoption and/or rejection of new technologies from a large landscape of adopters. A large corpus of social media texts containing references to emerging technologies was compiled. The expression of positive sentiment infers an increase in the likelihood of impacting a technology user's acceptance to adopt, integrate, and/or use the technology, and negative sentiment infers an increase in the likelihood of impacting the rejection of emerging technologies by adopters.
  arXiv  Detail & Related papers  (2024-01-16T16:42:14Z)
• Anticipating Impacts: Using Large-Scale Scenario Writing to Explore Diverse Implications of Generative AI in the News Environment [3.660182910533372]
  We aim to broaden the perspective and capture the expectations of three stakeholder groups about the potential negative impacts of generative AI. We apply scenario writing and use participatory foresight to delve into cognitively diverse imaginations of the future. We conclude by discussing the usefulness of scenario-writing and participatory foresight as a toolbox for generative AI impact assessment.
  arXiv  Detail & Related papers  (2023-10-10T06:59:27Z)
• Predictable Artificial Intelligence [77.1127726638209]
  This paper introduces the ideas and challenges of Predictable AI. It explores the ways in which we can anticipate key validity indicators of present and future AI ecosystems. 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)
• Social Influence Dialogue Systems: A Scoping Survey of the Efforts Towards Influence Capabilities of Dialogue Systems [50.57882213439553]
  Social influence dialogue systems are capable of persuasion, negotiation, and therapy. There exists no formal definition or category for dialogue systems with these skills. This study serves as a comprehensive reference for social influence dialogue systems to inspire more dedicated research and discussion in this emerging area.
  arXiv  Detail & Related papers  (2022-10-11T17:57:23Z)
• Aggression and "hate speech" in communication of media users: analysis of control capabilities [50.591267188664666]
  Authors studied the possibilities of mutual influence of users in new media. They found a high level of aggression and hate speech when discussing an urgent social problem - measures for COVID-19 fighting. Results can be useful for developing media content in a modern digital environment.
  arXiv  Detail & Related papers  (2022-08-25T15:53:32Z)
• Counterfactual Explanations as Interventions in Latent Space [62.997667081978825]
  Counterfactual explanations aim to provide to end users a set of features that need to be changed in order to achieve a desired outcome. Current approaches rarely take into account the feasibility of actions needed to achieve the proposed explanations. We present Counterfactual Explanations as Interventions in Latent Space (CEILS), a methodology to generate counterfactual explanations.
  arXiv  Detail & Related papers  (2021-06-14T20:48:48Z)
• Unpacking the Expressed Consequences of AI Research in Broader Impact Statements [23.3030110636071]
  We present the results of a thematic analysis of a sample of statements written for the 2020 Neural Information Processing Systems conference. The themes we identify fall into categories related to how consequences are expressed and areas of impacts expressed. In light of our results, we offer perspectives on how the broader impact statement can be implemented in future iterations to better align with potential goals.
  arXiv  Detail & Related papers  (2021-05-11T02:57:39Z)
• Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments [73.7716728492574]
  We study the effectiveness of various recommendation strategies in the mobile channel and their impact on consumers' utility and demand levels for individual products. We find significant differences in effectiveness among various recommendation strategies. We develop novel econometric instruments that capture product differentiation (isolation) based on deep-learning models of user-generated reviews.
  arXiv  Detail & Related papers  (2021-02-20T22:58:54Z)
• Overcoming Failures of Imagination in AI Infused System Development and Deployment [71.9309995623067]
  NeurIPS 2020 requested that research paper submissions include impact statements on "potential nefarious uses and the consequences of failure" We argue that frameworks of harms must be context-aware and consider a wider range of potential stakeholders, system affordances, as well as viable proxies for assessing harms in the widest sense.
  arXiv  Detail & Related papers  (2020-11-26T18:09:52Z)

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.