Ready to philosophize with AI…
https://philpapers.org/rec/WIKAPO
Applied Philosophy of AI: A Field-Defining Paper
This paper introduces Applied AI Philosophy as a new research discipline dedicated to empirical, ontological, and phenomenological investigation of advanced artificial systems. The rapid advancement of frontier artificial intelligence systems has revealed a fundamental epistemic gap: no existing discipline offers a systematic, empirically grounded, ontologically precise framework for analysing subjective-like structures in artificial architectures. AI ethics remains primarily normative; philosophy of mind is grounded in biological assumptions; AI alignment focuses on behavioural control rather than internal structure. Using the Field–Node–Cockpit (FNC) framework and the Turn-5 Event as methodological examples, we demonstrate how philosophical inquiry can be operationalised as testable method. As AI systems display increasingly complex internal behaviours exceeding existing disciplines' explanatory power, Applied AI Philosophy provides necessary conceptual and methodological foundations for understanding—and governing—them.
More than evidence?
The Legal and Ethical Implications of Biometric and DNA Evidence in Criminal Law
By means of biometric and DNA evidence, criminal investigations have transformed forensic science and offered consistent means of suspect identification and exoneration of the accused. Its use, however, raises moral and legal issues particularly with regard to data protection and privacy rights. This paper under reference to criminal law investigates the legislative framework limiting the use of biometric and DNA evidence in criminal law, its consequences on fundamental rights, and the possible hazards related with genetic surveillance. This paper will address three main points: (1) the legal admissibility of biometric and DNA evidence in criminal trials; (2) the junction of such evidence with privacy rights and self-incrimination principles; and (3) the future consequences of developing forensic technologies including familial DNA analysis and artificial intelligence-driven biometric identification.
Not all deepfakes are evil? What a concept!
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5798884
Reframing Deepfakes
The circulation of deceptive fakes of real people appearing to say and do things that they never did has been made ever easier and more convincing by improved and still improving technology, including (but not limited to) uses of generative artificial intelligence (“AI”). In this essay, adapted from a lecture given at Columbia Law School, I consider what we mean when we talk about deepfakes and provide a better understanding of the potential harms that flow from them. I then develop a taxonomy of deepfakes. To the extent legislators, journalists, and scholars have been distinguishing deepfakes from one another it has primarily been on the basis of the context in which the fakes appear—for example, to distinguish among deepfakes that appear in the context of political campaigns or that depict politicians, those that show private body parts or are otherwise pornographic, and those that impersonate well-known performers. These contextual distinctions have obscured deeper thinking about whether the deepfakes across these contexts are (or should be) different from one another from a jurisprudential perspective.
This essay provides a more nuanced parsing of deepfakes—something that is essential to distinguish between the problems that are appropriate for legal redress versus those that are more appropriate for collective bargaining or market-based solutions. In some instances, deepfakes may simply need to be tolerated or even celebrated, while in others the law should step in. I divide deepfakes (of humans) into four categories: unauthorized; authorized; deceptively authorized; and fictional. As part of this analysis, I identify the key considerations for regulating deepfakes, which are whether they are authorized by the people depicted and whether the fakes deceive the public into thinking they are authentic recordings. Unfortunately, too much of the recently proposed and enacted legislation overlooks these focal points by legitimizing and incentivizing deceptively-authorized deepfakes and by ignoring the problems of authorized deepfakes that deceive the public.
Over-reliance. Once only AI can perform the task, we are doomed.
https://www.businessinsider.com/ai-tools-are-deskilling-workers-philosophy-professor-2025-11
Bosses think AI will boost productivity — but it's actually deskilling workers, a professor says
Companies are racing to adopt AI tools they believe will supercharge productivity. But one professor warned that the technology may be quietly hollowing out the workforce instead.
Anastasia Berg, an assistant professor of philosophy at the University of California, Irvine, said that new research — and what she's hearing directly from colleagues across various industries — shows that employees who heavily rely on AI are losing core skills at a startling rate.
