Maksymilian M. Kuźmicz, defends his doctoral thesis “Proactive Balancing: AI-driven Video-based Active Assisted Living Technologies and Balancing of Interests”, at Stockholm University.
Abstract
This thesis aims to propose a method of balancing and identify appropriate legal tools of balancing in the context of AI-
driven video-based Active Assisted Living (AAL) technologies. AAL represents a suite of technologies integrated into
computer systems that leverage AI to assist older adults in their daily lives, enabling them to live independently and remain active.
While numerous studies assert that AAL technologies keep improving their ability to assist individuals in need, this
optimistic prospect must be juxtaposed to several concerns. These concerns are often conflicts of interests, i.e., situations
in which pursuing one interest may hinder another. Conflicts of interest can be approached in many ways, one of which is
balancing. That presents an issue of balancing as a conflict management tool in the AAL context. In the legal context, the
problem is more specific: What is balancing, and how could it be used to prevent or solve conflict?
Consequently, the main subject of this book is structuring balancing as a legal method of conflict management in the
AAL context. The investigation focuses on European law and AAL deployed at private homes. The thesis begins by
identifying stakeholders and their primary interests. Next, the work proposes to merge the risk identification method with a dogmatic analysis of law to provide a method of identification of potential conflicts. Subsequently, the book presents two main approaches to balancing recognised in the case law of the European Court of Human Rights and the Court of Justice of the European Union: proportionality and compromising. Each method is analysed and presented in a structured way, tailored to the AAL context. Building on these findings, a catalogue of legal tools for balancing is constructed. Finally, the thesis examines the possibility of an integrated model of balancing, proposes how it could be constructed, and evaluates its potential role as risk and quality management systems required by the AI Act.
This thesis makes contributions to the field of legal sciences by examining the concept of balance, methods of balancing,and generating a catalogue of balancing tools. Moreover, it advances the research on AAL technologies by proposing a novel stakeholders’ classification that merges analytical categorisations with those grounded in legal frameworks and identifying balancing tools applicable in the AAL context. Furthermore, it proposes possible models of risk and quality management systems under the AI Act.
Supervisor
Peter Wahlgren, Professor
Lianne Colona, Professor
Opponent
Professor Tobias Mahler, Oslo University, Norway.
