Mapping acceptance: micro scenarios as a dual-perspective approach for assessing public opinion and individual differences in technology perception

• URL: http://arxiv.org/abs/2402.01551v2
• Date: Wed, 16 Oct 2024 19:32:45 GMT
• Title: Mapping acceptance: micro scenarios as a dual-perspective approach for assessing public opinion and individual differences in technology perception
• Authors: Philipp Brauner,
• Abstract summary: This article introduces micro scenarios as an integrative method to evaluate mental models and social acceptance across numerous technologies and concepts. Average evaluations of each participant can be seen as individual differences, providing reflexive measurements across technologies or topics. This paper aims to bridge the gap between technological advancement and societal perception, offering a tool for more informed decision-making in technology development and policy-making.
• Score: 0.0
• License:
• Abstract: Understanding public perception of technology is crucial to aligning research, development, and governance of technology. This article introduces micro scenarios as an integrative method to evaluate mental models and social acceptance across numerous technologies and concepts using a few single-item scales within a single comprehensive survey. This approach contrasts with traditional methods that focus on detailed assessments of as few as one scenario. The data can be interpreted in two ways: Perspective (1): Average evaluations of each participant can be seen as individual differences, providing reflexive measurements across technologies or topics. This helps in understanding how perceptions of technology relate to other personality factors. Perspective (2): Average evaluations of each technology or topic can be interpreted as technology attributions. This makes it possible to position technologies on visuo-spatial maps to simplify identification of critical issues, conduct comparative rankings based on selected criteria, and to analyze the interplay between different attributions. This dual approach enables the modeling of acceptance-relevant factors that shape public opinion. It offers a framework for researchers, technology developers, and policymakers to identify pivotal factors for acceptance at both the individual and technology levels. I illustrate this methodology with examples from my research, provide practical guidelines, and include R code to enable others to conduct similar studies. This paper aims to bridge the gap between technological advancement and societal perception, offering a tool for more informed decision-making in technology development and policy-making.

Related papers

• Explainability in AI Based Applications: A Framework for Comparing Different Techniques [2.5874041837241304]
  In business applications, the challenge lies in selecting an appropriate explainability method that balances comprehensibility with accuracy. This paper proposes a novel method for the assessment of the agreement of different explainability techniques. By providing a practical framework for understanding the agreement of diverse explainability techniques, our research aims to facilitate the broader integration of interpretable AI systems in business applications.
  arXiv  Detail & Related papers  (2024-10-28T09:45:34Z)
• A review on data-driven constitutive laws for solids [0.0]
  This review article highlights state-of-the-art data-driven techniques to discover, encode, surrogate, or emulate laws. Our objective is to provide an organized taxonomy to a large spectrum of methodologies developed in the past decades.
  arXiv  Detail & Related papers  (2024-05-06T17:33:58Z)
• 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)
• Intersectional Inquiry, on the Ground and in the Algorithm [1.0923877073891446]
  We argue that methods in this field must account for intersections of social difference, such as race, class, ethnicity, culture, and disability. We consider the complexities of bringing together computational and qualitative methods in an intersectional methodological approach.
  arXiv  Detail & Related papers  (2023-08-29T23:43:58Z)
• 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)
• Image Quality Assessment in the Modern Age [53.19271326110551]
  This tutorial provides the audience with the basic theories, methodologies, and current progresses of image quality assessment (IQA) We will first revisit several subjective quality assessment methodologies, with emphasis on how to properly select visual stimuli. Both hand-engineered and (deep) learning-based methods will be covered.
  arXiv  Detail & Related papers  (2021-10-19T02:38:46Z)
• Holistically Placing the ICT Artefact in Capability Approach [0.0]
  This paper proposes a framework that holistically places the Information and Communication Technology (ICT) Artefact in Capability Approach (CA) The framework harmonises the different conceptualisations of technology within CA-based frameworks in ICT4D.
  arXiv  Detail & Related papers  (2021-08-22T16:49:20Z)
• Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective [69.44384540002358]
  We provide a comprehensive and holistic 2D-to-3D perspective to tackle this problem. We categorize the mainstream and milestone approaches since the year 2014 under unified frameworks. We also summarize the pose representation styles, benchmarks, evaluation metrics, and the quantitative performance of popular approaches.
  arXiv  Detail & Related papers  (2021-04-23T11:07:07Z)
• 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)
• Survey on Visual Sentiment Analysis [87.20223213370004]
  This paper reviews pertinent publications and tries to present an exhaustive overview of the field of Visual Sentiment Analysis. The paper also describes principles of design of general Visual Sentiment Analysis systems from three main points of view. A formalization of the problem is discussed, considering different levels of granularity, as well as the components that can affect the sentiment toward an image in different ways.
  arXiv  Detail & Related papers  (2020-04-24T10:15:22Z)
• Neuro-symbolic Architectures for Context Understanding [59.899606495602406]
  We propose the use of hybrid AI methodology as a framework for combining the strengths of data-driven and knowledge-driven approaches. Specifically, we inherit the concept of neuro-symbolism as a way of using knowledge-bases to guide the learning progress of deep neural networks.
  arXiv  Detail & Related papers  (2020-03-09T15:04:07Z)

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.