In-depth interviewing represents a qualitative research approach characterized by conducting comprehensive, open-ended interviews with individuals or subjects. This method is employed to gain profound insights into their perspectives, experiences, and viewpoints regarding a specific subject matter. In-depth interviewing finds application in disciplines such as the social sciences and market research.
Published in Chapter:
An In-Depth Qualitative Interview: The Impact of Artificial Intelligence (AI) on Consent and Transparency
Sharon L. Burton (Capitol Technology University, USA), Darrell N. Burrell (Marymount University, USA), Calvin Nobles (Illinois Institute of Technology, USA),
Yoshino W. White (Florida State University, USA),
Maurice E. Dawson (Illinois Institute of Technology, USA),
Kim L. Brown-Jackson (Capitol Technology University, USA),
S Rachid Muller (Arizona State University, USA), and
Dustin I. Bessette (Mt. Hood Community College, USA)
Copyright: © 2024
|Pages: 22
DOI: 10.4018/979-8-3693-3226-9.ch014
Abstract
AI is impacting consent and transparency adversely. Although AI can potentially augment transparency in decision-making via advanced technology, it is creating new concerns. This chapter focuses on the impact of AI systems on individuals' ability to provide informed consent for using their data, and the relationship between transparency in AI decision-making processes and issues related to accountability and trust. Discussed are GDPR (European Union General Data Protection Regulation), and CCPA (California Consumer Privacy Act) due to their consent and transparency within their broader privacy protection frameworks. Applied is a qualitative methodology and in-depth interview design using a communication and collaboration platform to explain the connection between AI consent and transformation. Research results offer avenues to understanding the challenges of informed consent and legal and ethical considerations regarding consent and transparency. Beneficiaries of this research are practitioners, academics, and learners in AI, cybersecurity, and criminology/criminal justice.