Syed AbuMusab

In this paper, we examine the potential integration of artificial intelligence (AI) into capital punishment through lethal autonomous mechanisms (LAMs), an extension of developments in lethal autonomous weapons (LAWs). While most philosophical and ethical research on autonomous weapons systems focuses on warfare and policing, their potential role in capital executions remains unexplored. Through anticipatory analysis of LAMs’ integration into what we term the “death row network,” we show how retentionists might leverage these technologies to counter key abolitionist critiques. We analyze how LAMs could undermine two abolitionist arguments: the harm to corrections personnel and the medicalization of execution protocols. However, we argue that while LAMs resolve these specific challenges, they simultaneously generate new ethical concerns. First, LAMs will not eliminate the moral and psychological burden on corrections personnel entirely but rather redistribute it to networks of AI developers, software engineers, and technology professionals who become implicated in state-sanctioned killings through their work. Similarly, LAMs address the medicalization concern, yet they merely shift ethical scrutiny from the medical sector to the technology corporations developing LAMs and their industrial partners. Second, LAMs’ elimination of human presence undermines the exercise of benevolence through sustained interpersonal engagement, from sharing final conversations to offering comfort during an inmate’s last moments. This human connection, which preserves dignity even within a dehumanizing process, cannot be replicated by automated systems and is a further argument against their adoption.

In this paper, we examine the potential integration of artificial intelligence (AI) into capital punishment through lethal autonomous mechanisms (LAMs), an extension of developments in lethal autonomous weapons (LAWs). While most philosophical and ethical research on autonomous weapons systems focuses on warfare and policing, their potential role in capital executions remains unexplored. Through anticipatory analysis of LAMs’ integration into what we term the “death row network,” we show how retentionists might leverage these technologies to counter key abolitionist critiques. We analyze how LAMs could undermine two abolitionist arguments: the harm to corrections personnel and the medicalization of execution protocols. However, we argue that while LAMs resolve these specific challenges, they simultaneously generate new ethical concerns. First, LAMs will not eliminate the moral and psychological burden on corrections personnel entirely but rather redistribute it to networks of AI developers, software engineers, and technology professionals who become implicated in state-sanctioned killings through their work. Similarly, LAMs address the medicalization concern, yet they merely shift ethical scrutiny from the medical sector to the technology corporations developing LAMs and their industrial partners. Second, LAMs’ elimination of human presence undermines the exercise of benevolence through sustained interpersonal engagement, from sharing final conversations to offering comfort during an inmate’s last moments. This human connection, which preserves dignity even within a dehumanizing process, cannot be replicated by automated systems and is a further argument against their adoption.

The artificiality of AI, while often problematic in Western ethical frameworks, uniquely aligns with Islamic ethics. Where standard criticisms of carebots emphasize dignity, deception, and simulated care, I demonstrate that their artificial nature positions them as 'neutragents' (neutral agents) within Islamic care ethics. Through their neutragential status, carebots transcend the traditional mahram/non-mahram (permissible/non-permissible caretakers) dichotomy while protecting awrah (bodily privacy). However, this advantage becomes compromised if Muslim users' image and video data are exposed to human labelers during AI training, as such exposure would undermine the neutragential status. This analysis reveals a critical implication: the necessity of intercultural value alignment in AI ethics. As AI's global impact grows, integrating diverse ethical perspectives becomes essential, yet current approaches to AI ethics and value alignment have been slow to incorporate non-standard perspectives meaningfully.

The recent advances in Large Language Models (LLMs) and their deployment in social settings prompt an important philosophical question: are LLMs social agents? This question finds its roots in the broader exploration of what engenders sociality. Since AI systems like chatbots, carebots, and sexbots are expanding the pre-theoretical boundaries of our social ontology, philosophers have two options. One is to deny LLMs membership in our social ontology on theoretical grounds by claiming something along the lines that only organic or X-type creatures belong in our social world. Second, expand our ontological boundaries. I take the second route and claim LLMs implemented as social chatbots are social agents. Utilizing Brian Epstein's concepts of grounding and anchoring, alongside Dee Peyton's criteria for what makes a property social, I posit that the capacity for conversations is a social property. Further, within a framework where social agency is considered multi-dimensional, akin to agency, possessing a social property is sufficient for attaining social agency. Thus establishing chatbots as social agents. A helpful concept here is Levels of Abstraction (LoA). The LoA framework allows for extracting relevant and important information from the target domain (the social world). For example, the property of being a 'boy' and the capacity for conversation are social properties; hence, they are part of the social domain. LLMs have the capacity for conversations. So, if we focus on the conversational-LoA and not the gender-LoA, then LLMs occupy a dimension of sociality (i.e., conversational dimensions).

Ethically significant consequences of artificially intelligent artifacts will stem from their effects on existing social relations. Artifacts will serve in a variety of socially important roles—as personal companions, in the service of elderly and infirm people, in commercial, educational, and other socially sensitive contexts. The inevitable disruptions that these technologies will cause to social norms, institutions, and communities warrant careful consideration. As we begin to assess these effects, reflection on degrees and kinds of social agency will be required to make properly informed decisions concerning the deployment of artificially intelligent artifacts in important settings. The social agency of these systems is unlike a human social agency, and this paper provides a methodological framework that is more suited for inquiry into artificial social agents than conventional philosophical treatments of the concept of agency. Separate aspects and dimensions of agency can be studied without assuming that agency must always look like adult human agency. This revised approach to the agency of artifacts is conducive to progress in the topics studied by AI ethics.

In chapter eleven of "On The Foundation of Computing," Primiero takes on the implementation debate in computer science. He contrasts his theory with two other views—the Semantic and the specification—artifact. In this paper, I argue that there is a way to fine-tune the implementation concept further. Firstly, contrary to Primiero, I claim it is problematic to separate the implementation relationship from the conditions which make it correct. Secondly, by taking a pluralistic approach to implementation, I claim it is a mistake to try and provide a general theory of implementation for the entire production cycle of computational systems.