This link is ONLY for the philosophical buffs. I did try to wrap my head around it but I have enclosed a quick summary below.
The Nooscope is a cartography of the limits of artificial intelligence, intended as a provocation to both computer science and the humanities. Any map is a partial perspective, a way to provoke debate. Similarly, this map is a manifesto — of AI dissidents. Its main purpose is to challenge the mystifications of artificial intelligence. First, as a technical definition of intelligence and, second, as a political form that would be autonomous from society and the humanThe Nooscope Manifested
- The modern project to mechanise human reason has clearly mutated, in the 21st century, into a corporate regime of knowledge extractivism and epistemic colonialism.
- This is unsurprising, since machine learning algorithms are the most powerful algorithms for information compression.
- The purpose of the Nooscope map is to secularize AI from the ideological status of ‘intelligent machine’ to one of knowledge instrument.
Rather than evoking legends of alien cognition, it is more reasonable to consider machine learning as an instrument of knowledge magnification that helps to perceive features, patterns, and correlations through vast spaces of data beyond human reach.
- In the history of science and technology, this is no news: it has already been pursued by optical instruments throughout the histories of astronomy and medicine.
- In the tradition of science, machine learning is just a Nooscope, an instrument to see and navigate the space of knowledge (from the Greek skopein ‘to examine, look’ and noos ‘knowledge’).
- Borrowing the idea from Gottfried Wilhelm Leibniz, the Nooscope diagram applies the analogy of optical media to the structure of all machine learning apparatuses.
- Machine learning is not the ultimate form of intelligence.
In the same way that the lenses of microscopes and telescopes are never perfectly curvilinear and smooth, the logical lenses of machine learning embody faults and biases.
- This is generally known as the debate on bias in AI, but the political implications of the logical form of machine learning are deeper.
This diagram manifesto is another way to say that AI, the king of computation (patriarchal fantasy of mechanised knowledge, ‘master algorithm’ and alpha machine) is naked.
- The assembly line of machine learning: Data, Algorithm, Model.
As an instrument of knowledge, machine learning is composed of an object to be observed (training dataset), an instrument of observation (learning algorithm) and a final representation (statistical model)
- The assemblage of these three elements is proposed here as a spurious and baroque diagram of machine learning, extravagantly termed Nooscope.
- Staying with the analogy of optical media, the information flow of machine learning is like a light beam that is projected by the training data, compressed by the algorithm and diffracted towards the world by the lens of the statistical model.
- The Nooscope diagram aims to illustrate two sides of machine learning at the same time: how it works and how it fails — enumerating its main components, as well as the broad spectrum of errors, limitations, approximations, biases, faults, fallacies and vulnerabilities that are native to its paradigm.
- This double operation stresses that AI is not a monolithic paradigm of rationality but a spurious architecture made of adapting techniques and tricks.
- In the Nooscope diagram the essential components of machine learning are represented at the centre, human biases and interventions on the left, and technical biases and limitations on the right.