Atay Kozlovski

Digital duplicates (DDs), or artificial intelligence (AI) simulations of individual minds, are AI models designed to emulate real people. Depending on how they are trained, DDs can reproduce aspects or signs of a person’s psychology, values and communication style, enabling interaction with digital approximations of living, recently deceased or historical individuals. Proposed uses include education, advocacy, grief support, medical decision-­ making and the continuation of creative or personal projects. While potentially valuable, these applications also pose ethical risks such as privacy loss, misrepresentation, manipulation and the erosion of authentic human relationships. This paper argues that DDs should be treated as context-­ specific tools rather than general-­ purpose technologies. We outline a two-­ tier ethical framework grounded in considerations of harm and proportionality, supported by the values of information permission, transparency, authenticity and appropriate access. The framework unites diverse moral concerns under a single framework while allowing their relative weight to vary across domains such as medicine, education, memorialisation and entertainment. By situating ethical evaluation within a harm-­ reduction approach that is sensitive to context, we offer a practical basis for the responsible development and governance of human-emulating AI systems.

Recent developments in theories for responsible innovation have focused on the importance of actively accounting for values in our technological designs. Leading among these theories is that of Value Sensitive Design which attempts to guide the design process on the basis of evaluative analysis. However, values often come into conflict and VSD has been criticized for not providing a proper method to resolve such inevitable conflicts. This paper examines three such methods and argues that although each has its merits, they all fail to account for a common source of value conflicts known as value incommensurability. Drawing on literature from the field of axiology, this paper argues that by incorporating the evaluative relation of ‘parity’ each of these three methods, and the VSD framework in general, will be able to properly understand the relation which holds between conflicting design options stemming from the incommensurable of values and be able to guide designers in making rational decision in the face of such conflicts.

The rapid proliferation of AI systems has raised many concerns about safety and responsibility in their design and use. The philosophical framework of Meaningful Human Control (MHC) was developed in response to these concerns, and tries to provide a standard for designing and evaluating such systems. While promising, the framework still requires further theoretical and practical refinement. This paper contributes to that effort by drawing on research in axiology and rational decision theory to identify a critical gap in the framework. Specifically, it argues that while ‘reasons’ play a central role in MHC, there has been little discussion of the possibility that, when weighed against each other, reasons may not always point to a single, rationally preferable course of action. I refer to these cases as instances of reasons underdetermination, and this paper discusses the need to address this issue within the MHC framework. The paper begins by providing an overview of the key concepts of the MHC framework and then examines the role of ‘reasons’ in the framework’s two main conditions - Tracking and Tracing. It then discusses the phenomenon of reasons underdetermination and shows how it poses a challenge for the achievement of both Tracking and Tracing.

Advances in generative AI have given rise to a growing industry centred on interactive representations of deceased individuals. Within this emerging “digital afterlife industry”, interactive deadbots (IDBs) are presented as hyper-realistic avatars that use a person’s likeness, voice, and personal data to simulate conversational interactions with them. Rapidly moving from a niche experiment to a mainstream phenomenon, IDBs are poised to reshape the ethical, social, legal, and governance landscapes surrounding death, mourning, and digital legacy. This paper examines the disruptive nature of IDB technology through a multidisciplinary lens, using the concept of indeterminacy as its guiding analytical framework and a novel way to conceptualise the unstable field. Rather than advancing a unified understanding of indeterminacy, we introduce a structured analytical map and provisional taxonomy that distinguishes technological, social, philosophical, legal, and regulatory manifestations of indeterminacy in IDBs. By offering a tentative and necessarily selective map of this fluid and nascent field, we explore how indeterminacy and IDBs intersect. The paper examines how IDBs amplify existing forms of indeterminacy and how indeterminacy itself shapes the development and use of these systems across five domains: technological, social, philosophical, legal, and regulatory.