AI and Consciousness
Debates about whether artificial systems can have experience.
Explore this guide ↗THE DIGITAL NEXUS
Technology & Futures
Question what machines can do.
Technology changes the tools we use to act, create, decide and communicate. This first collection examines artificial intelligence from two angles: how to evaluate its observable performance, and what that performance cannot settle about subjective experience.
Measure what a model actually does
Our guide to model evaluation explains why overall accuracy can hide important kinds of mistakes. Precision, recall, held-out examples and data shift matter when predictions affect decisions. The Classifier Trade-offs Lab lets you move a threshold across a fixed fictional dataset and see counts change. It is a transparent toy—not a claim about any real model.
Ask what the measurement cannot prove
A system that succeeds on a benchmark may still have other limitations. A strong predictive score does not demonstrate safety, fairness or consciousness. NIST's AI risk guidance highlights that trustworthiness involves reliability, accountability, transparency, privacy and more. Our introductory article on AI and consciousness keeps those practical concerns separate from metaphysical arguments about experience.
Connect design, philosophy and biology
The most useful comparisons do not collapse one field into another. A biological neuron sends electrochemical signals; a software classifier maps inputs to outputs according to a model. Philosophers debate the meaning of subjective experience; scientists measure specific behaviors and mechanisms. Exploring their meeting point can make both the achievements and limits of technology easier to understand.
THE LIBRARY
Start with a question
Original introductory guides with sources and conceptual connections.
Evaluating AI Models Beyond Accuracy
Understand generalization, held-out data and classification tradeoffs through examples.
Explore this guide ↗NEXUS LABS
Learn by experimenting
Interactive demonstrations with transparent assumptions and accessible explanations.
Classifier Trade-offs Lab
Move a decision threshold to observe precision, recall and confusion counts on fictional data.
Explore this lab ↗FIND MORE
Explore the knowledge network
Search published questions or explore the Nexus Graph to follow connections.
NEXUS ACADEMY
Learn across three worlds
Follow a guided reading and lab path through reasoning, the living brain and AI evaluation. Each short module includes a source-linked guide, a working exercise and an explained answer.
Introductory educational material compiled with AI assistance using the linked sources. No specialist or clinical endorsement is implied. Last source check: 11 November 2026.