8 citations · 18 across the 5 of their papers we have counts for
5 papers
A Quantifiable Information-Processing Hierarchy Provides a Necessary Condition for Detecting Agency
Brett J. Kagan, Valentina Baccetti, Brian D. Earp +3
As intelligent systems are developed across diverse substrates - from machine learning models and neuromorphic hardware to in vitro neural cultures - understanding what gives a sys…
Authorship Without Writing: Large Language Models and the Senior Author Analogy
Clint Hurshman, Sebastian Porsdam Mann, Julian Savulescu +1
The use of large language models (LLMs) in bioethical, scientific, and medical writing remains controversial. While there is broad agreement in some circles that LLMs cannot count…
AI and the Future of Academic Peer Review
Sebastian Porsdam Mann, Mateo Aboy, Joel Jiehao Seah +7
Peer review remains the central quality-control mechanism of science, yet its ability to fulfill this role is increasingly strained. Empirical studies document serious shortcomings…
Development of Application-Specific Large Language Models to Facilitate Research Ethics Review
Sebastian Porsdam Mann, Joel Seah Jiehao, Stephen R. Latham +3
Institutional review boards (IRBs) play a crucial role in ensuring the ethical conduct of human subjects research, but face challenges including inconsistency, delays, and ineffici…
Relational Norms for Human-AI Cooperation
Brian D. Earp, Sebastian Porsdam Mann, Mateo Aboy +59
How we should design and interact with social artificial intelligence depends on the socio-relational role the AI is meant to emulate or occupy. In human society, relationships suc…