Location
Online
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2022 12:00 AM
End Date
7-1-2022 12:00 AM
Description
Cross disciplinary research is essential for technological innovation. For decades, computer science (Comp Sci) has leveraged behavior science (Behav Sci) research to create innovative products and improve end user experience. Despite the natural challenges that come with cross disciplinary work, there are no published manuscripts outlining how to responsibly integrate Behav Sci into Comp Sci research and development. This publication fills this critical gap by discussing important differences between Behav Sci and Comp Sci, particularly with regard to how each field fits under the umbrella of science and how each field conceptualizes data. We then discuss the consequences of misusing Behav Sci and provide examples of technology efforts that drew inappropriate or unethical conclusions about their behavioral data. We discuss in detail common errors to avoid at each stage of the research process, which we condensed into a useful checklist to use as a tool for teams integrating Behav Sci in their work. Finally, we include examples of good applications of Behav Sci into Comp Sci research, the design of which can inform and strengthen digital government, e-commerce, defense, and many other areas of information technology.
Responsible Integration of Behavioral Science in Computer Science Research and Development
Online
Cross disciplinary research is essential for technological innovation. For decades, computer science (Comp Sci) has leveraged behavior science (Behav Sci) research to create innovative products and improve end user experience. Despite the natural challenges that come with cross disciplinary work, there are no published manuscripts outlining how to responsibly integrate Behav Sci into Comp Sci research and development. This publication fills this critical gap by discussing important differences between Behav Sci and Comp Sci, particularly with regard to how each field fits under the umbrella of science and how each field conceptualizes data. We then discuss the consequences of misusing Behav Sci and provide examples of technology efforts that drew inappropriate or unethical conclusions about their behavioral data. We discuss in detail common errors to avoid at each stage of the research process, which we condensed into a useful checklist to use as a tool for teams integrating Behav Sci in their work. Finally, we include examples of good applications of Behav Sci into Comp Sci research, the design of which can inform and strengthen digital government, e-commerce, defense, and many other areas of information technology.
https://aisel.aisnet.org/hicss-55/dg/cyber_deception/5