In Volume 26, Issue 2 of Sage Journals...
https://journals.sagepub.com/doi/full/1 ... 4231164874
'As a mode of speculation, astrology presents a striking similarity to artificial intelligence: through the observation and study of celestial patterns, it is used to both rationalise and anticipate patterns of individual behavior, societal events and natural phenomena.'
Algorithmic media have adopted and adapted divinatory practices and vernaculars of prediction, prophecy, probability, fortune-telling and forecasting suggesting a possible link between artificial intelligence and pre-scientific modes of speculation.
Statistical thinking and magical thinking, too, can be recognised as closely correlated epistemological systems for governing societies and ways of life. In fact, primitive astrological practices of looking up at the stars may represent one of the earliest statistical projects involving sophisticated calculations and data sets. Such pattern-making techniques could even be considered precursory to machine learning.'
'Astrology, emerging from ancient folk traditions of pattern recognition as an institutionalised system of divination in medieval academia, laid the foundations for astronomy and astrometeorology. Despite the purported disenchantments of science and modernity, the magic associated with astrology was transposed onto our media technologies and computational machines. Humankind never ceased to look at the sky. In fact, the sky continues to elicit wonder and to exert its authority over humans as natural beings, even in our efforts to dominate it. Through imperial and military exploits, the language of the sky has been translated into the climatic sciences of climatology and meteorology. Both the study of the climate and of the weather necessitated comprehensive data, statistical calculations and the capacity for powerful computing. Artificial intelligence materialised from the algorithms and neural networks of these computers, modelled in the image of the rationally psychotic human brain....
Such narratives reveal the underlying instability of knowledge itself and subsequently, that of truth and reality. What do we consider science? What do we consider intelligent? And what happens when we grant divinatory powers to our machines? For all this development, for all this data, the machine has yet to surpass the intelligence of the mind and its speculations remain fundamentally undifferentiated from divination. What has changed, however, is how we believe and what we believe in. Our supernatural fixation on magic as the mediator between experience and reality shifted to a preoccupation with the mind as the locus of objective scientific reasoning, which in turn was superseded by the imaginary of algorithmic cognition.' (p. 144)
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In a recent study at Cornell University, 'Sparks of Artificial Intelligence', the researchers did early experiments with the next generation GPT-4
https://arxiv.org/abs/2303.12712
They explain some processes happening in 'true understanding' of any science (like astrology).
1.
Creative reasoning: The ability to identify which arguments, intermediate steps, calculations or algebraic manipulations are likely to be relevant at each stage, in order to chart a path towards the solution. This component is often based on a heuristic guess (or in the case of humans, intuition), and is often considered to be the most substantial and profound aspect of mathematical problem-solving.
Model training in astrology will thus face the challenge of harnessing information with questionable accuracy, reliability, and truthfulness of the information. The demonstrations of more general AI powers may also raise the need and importance in peoples' minds of controlling the contributions that they make to large-scale general AI systems, and people may ask for the ability and right of humans to decide and specify which content they want or do not want to be crawled and used as training data and which contributions they wish to have marked with provenance information describing the role of individuals and the nature of the data that they have provided.
In short, we will need to improve our language and interpretation of various components of a birth chart. We may have to let go of the doomed and fated interpretations of the Middle Age.
2.
Technical proficiency: The ability to perform routine calculations or manipulations that follow a prescribed set of steps (such as differentiating a function or isolating a term in an equation).
With simple instructions, AI will be able to design the kind of chart we always dreamed of, images beyond memorization. Adding or deleting components.
3.
Critical reasoning: The ability to critically examine each step of the argument, break it down into its sub-components, explain what it entails, how it is related to the rest of the argument and why it is correct. When solving a problem or producing a mathematical argument, this usually comes together with the ability to backtrack when a certain step is realized to be incorrect and modify the argument accordingly.
For example...
'Where is the Profected ASC right now?'
'The Profected ASC is at 6 Pisces 24 conjunct natal and transiting Saturn'
'OK. Could you provide an interpretation of potential manifestations?'
'... Done'
'And can you tell me from the database, who had a similar configuration in the past and what happened. Do a comparison/difference.'
What makes an explanation good? One possible way to evaluate the quality of an explanation is to check output consistency, i.e. whether the explanation is consistent with the output y given the input x and the context c. In other words, an output-consistent explanation provides a plausible causal account of how y was derived from x and c. By this criterion, GPT-4 is remarkably good at generating reasonable and coherent explanations, even when the output is nonsensical or wrong,
