TL;DR
The central thesis is that AI, by processing vast “Data Lakes,” generates a “hyper-vision” that makes previously unattainable patterns visible, dramatically expanding the domain of what is “reasonably predictable” and creates AI-Augmented Consequentialism, where the agent's moral duty comes to include consideration of the predictive potential of available technology.
In order to live well in an AI-based society, designing technically ethical systems, in the spirit of consequentialism, is not enough; rather, it is essential to cultivate citizens who, as AI users, are endowed with virtues and, first and foremost, the virtue of prudence.
This paper examines artificial intelligence (AI) as a distinctive epistemic regime through the lens of Martin Heidegger's philosophy of technology. While contemporary AI discourse emphasizes performance, ethics, and applications, it often neglects the underlying assumptions about knowledge and truth. Drawing on Heidegg...
The central ethical problem raised by artificial intelligence is not whether AI systems can "reason" in a functional sense, but whether their use preserves a centre of judgment that can be held responsible. Beginning with large language models, it distinguishes linguistic fluency from scientific validity, ethical commi...
This chapter offers a conceptual and philosophical analysis of the ontological, epistemological, and ethical issues associated with the design, development, and use of Agentic AI in moral and legal decision-making. Its aim is to map, classify, and bring into focus the principal philosophical problems raised by the auto...
The concept of “alienated intelligence” is introduced to critically examine contemporary cultural perceptions of artificial intelligence to argue that certain visions of AI function as cultural projections of human cognitive capacities that become externalized, idealized, and reified in technological systems.
The article argues that many contemporary AI alignment practices risk a mistaken assimilation of moral agency to statistical learning. Techniques such as reinforcement learning from human feedback and constitutional AI often treat morality as a behavioral function that can be approximated from human discourse, behavior...
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