Digital Consent Design for Human-Centered Data-Collection Systems

Elena Fischer

Digital Consent Design for Human-Centered Data-Collection Systems

Author(s)	Dr. Elena Fischer
Country	United States
Abstract	Digital data-collection systems routinely request permission to process personal information through cookie banners, mobile-app permissions, account-registration interfaces, research portals, connected devices, artificial-intelligence applications, and platform privacy controls. Although these interfaces are commonly described as consent mechanisms, a user action such as selecting an “accept” button does not necessarily establish meaningful understanding, voluntariness, or control. Human-centered consent requires an interface to communicate what data will be collected, for which purposes, by whom, for how long, and with what consequences, while preserving a realistic ability to refuse, modify, and later withdraw authorization. Regulatory guidance similarly emphasizes that valid consent must be freely given, specific, informed, and unambiguous, while withdrawal must remain practically accessible. This study develops a human-centered framework for digital consent design and evaluates four interface approaches through an explicitly simulation-based methodology: manipulative consent, notice-heavy consent, simplified layered consent, and human-centered granular consent. A synthetic corpus of 360 hypothetical consent interactions was modeled across five dimensions: comprehension, voluntariness, granularity of control, withdrawal accessibility, and user trust. The simulated Consent Quality Index increases from 31 for manipulative interfaces to 88 for human-centered granular designs. The results illustrate that improved consent quality is associated not merely with greater information quantity but with understandable presentation, balanced choice architecture, purpose-specific controls, persistent preference management, and easy reversal. The study argues that consent should be designed as an ongoing relationship between individuals and data-processing systems rather than as a single transactional click. Human-centered consent architecture should therefore combine privacy engineering, interface usability, legal requirements, accessibility, data minimization, and accountable governance while actively excluding deceptive or coercive design practices.
Keywords	digital consent, human-centered design, data collection, privacy engineering, informed consent, dark patterns, privacy interface, data governance
Field	Engineering
Published In	Volume 2, Issue 6, November-December 2021
Published On	2021-11-08

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American Journal of Advanced Multidisciplinary Innovation and Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Digital Consent Design for Human-Centered Data-Collection Systems

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