12 juli 2021
Research Topic: Creating Responsible, Fair, and Reliable Data-driven Applications: Challenges, Methods, and Case Studies Topic editors: Sunil Choenni, Gabriele Lenzini, Mortaza S. Bargh
— Abstract: 15 August 2021
— Manuscript: 17 November 2021
The aim of this Research Topic is to foster research on methodologies, concepts, policies, procedures, and technologies that contribute to a socially attentive approach for data-driven applications (i.e., those applications relying on mining, managing, and analyzing data as well as learning from data). This socially attentive approach requires adopting a holistic and multidisciplinary approach for realizing data-driven applications in their social context and in an ethically responsible way (via, for example, preserving privacy, providing fairness and justice, and being reliable, justifiable, and accountable). We invite contributions that present innovative (applied) research results or novel approaches and methods that respect and emphasize the principles of ethics and social justice by creating responsible, fair, and reliable data-driven applications.
Articles can address, but are not limited to, the following topics:
• System design aspects: security by design, privacy by design, accountability by design, safety by design.
• Risk and resilience management aspects: threat modeling, threat detection, mitigation of risks, mitigation of residual risks.
• Trade-off making aspects: among contending values, realizing the desired functionality while preserving safety, security, privacy, reliability, trust, and ethical values.
• Balance creation aspects: between technical and non-technical measures, putting users in control, automizing routine tasks with sufficient user supervision.
• Data quality management aspects: data quality modeling, assessment, improvement.
• Organizational embedding aspects: developing methods and strategies for adopting data-driven applications by users and organizations.
For the full scope of the article collection and CFP please visit: https://www.frontiersin.org/research-topics/22078/creating-responsible-fair-and-reliable-data-driven-applications-challenges-methods-and-case-studies#overview
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