Astrology needs a Revolution – Part 1

Why it’s important for astrology to progress as a protoscience (a science in the making) and ideas on how to get there

Astrology is playing a very small game. Aided by new business, exponential technology (artificial intelligence) and data science it has the potential to contribute in a much more significant way to solving real-world problems to better serve humanity and the earth. The integration of these technologies, represents a bridging of spirituality and science. My intention is not to diminish astrology’s current contribution which is necessary and valuable. Rather, what is required to become a key player and stakeholder in the future, is much more.

Key to unlocking the astrology-science debate, is to understand science as a powerful method of reputable enquiry and credible path to knowledge, rather than the misguided notion of lab experiment or straight-jacket of material reductionism. 2021 has already seen unprecedented inroads into illuminating dark matter (CERN) in physics – the possible realm of understanding the mechanism of astrology – challenging the limited, standard model of science (physics).

Astrology progressed in the 70s with the automation of the ephemeris (the trajectory of naturally occurring astronomical objects over time) and computer-generated birth (natal positions) and transit (current positions) charts. Next came the internet in the late 1980s and social media in the 2000s, leveraging astrology through increased global online accessibility and digital technology.

Since 2010, artificial intelligence (AI), AI algorithms like neural net, machine learning and big data, offer advanced pattern generation, pattern sorting and prediction opportunities. This is the new untapped science and technology to enable astrology to play a bigger game.

While science and technology are progressing at an exponential rate, astrology is not.

Astrology may be flourishing, thanks to the internet, social media and increased uptake by millennials which gives the illusion of progress, when this is not the case. Within the informed general public domain, astrology is becoming more unacceptable and unwelcome. As Jonathan Jarry so succinctly said, “Astrology is a pseudoscience due to its lack of progress and refusal to deal with a large body of critical scientific studies”. Robert Currey, the editor of the peer-reviewed scientific astrology journal Correlation, speaks to this in the Astrology News Service (ANS) video How Sceptics Distort the Truth About Astrology.

With the exception of India, the fact that there is very limited public and corporate (private) interest in sponsorship (investment) of serious astrology research (projects) and only a handful of peer-reviewed scientific astrology research journals in the world, is testimony to astrology’s lack of progress. The reputation and credibility of astrology will not be built on a growing number of individually successful astrologers, but rather by astrology’s socio-cultural contribution to humanity and earth.

The astrology-science debate is an emotionally loaded one for astrologers. I deeply resonate with what Nicholas Campion said in the ANS video The Most Significant Prediction made by an Astrologer, that he takes great personal umbrage in the way in which astrology, as an ancient way of connecting to the wider cosmos, is often ridiculed. Ridicule is an uncomfortable shared-experience for many astrologers.

There is also a concern that Astrology will lose its mysterious and spiritual luminescence if it had to “become a science”.

What is needed is the perspective that astrology can be both an art and a protoscience without losing anything of what it currently is. Science is a credible, reputable method of enquiry, or “coming to know”. Intuition, realisation and logical deduction are other, no less valid and valuable paths to knowledge – but we need to do both.

The challenge of empowering astrology in service to humanity is not going to happen through decades of classical empirical research studies and tests, slowly accumulating evidence to support hypothesis and establish theory – we don’t have time! Astrology needs a revolution – to embrace new business, exponential technology and data science to rapidly produce “quick wins” and success stories and that will thrust astrology as a protoscience into prominence and attract interest and investment.

The difference between ‘classical’ scientific research and artificial intelligence (machine algorithms and machine learning) is that the latter generates patterns and makes correlations, imperceptible to human cognition. In classical scientific research we start with a hypothesis about a correlation which we test through research which is either supported or refuted. What if the astrological patterns on offer are too elusive, too subtle for classical scientific research methods? The sophistication of artificial intelligence technology with its advanced pattern generating and machine learning algorithms is perfectly suited to the complexity of astrology.

Imagine for a moment a headline in Nature or Lancet communicating a breakthrough for humanity in the form of a simple, non-invasive, free test that accurately predicts immunity to SARS-CoV-2! (Note: this is just an example, an idea, a problem worthy of solving, not an absolute astrological possibility or fact). On closer scrutiny, the story reveals the requirement for, together with other information, a person’s birth date, place and time (optional). Everyone is curious to know whether astrology is involved!

How would the simple test predicting immunity to SARS-CoV-2 be created using machine learning, neural net algorithms and astrology?

Machine-learning is the weft that uses big data and advanced pattern generating and sorting algorithms (like neural net algorithms) to build a fabric (advance set of patterns) of what immunity to SARS-CoV-2 would look like. Taking this analogy further, the warp threads of the loom are the foundational structure – this is the machine learning/neural net feature set.

The challenge relating to the feature set for astrology, is that astrology factors using implicitly “loaded” multi-dimensional, multivalent symbolism residing within zodiac degrees, signs and houses are too multifarious for the “mathematical” elegance required for the feature set. Elegance analogous to the type of thinking and method that resulted in André Barbault’s cyclical index is required – although bear in mind that face recognition is also a complex, multi-dimensional phenomenon currently being tackled by the same technology. Astrologer Renay Oshop has some ideas here (feature set), having already achieved some success in this domain. The solution would require an astrological paradigm shift in the form of the creation of a “meta” or “translation” layer that would reside above the zodiac.

The feature set would be customised for each (specific) project (requirement) – or problem-solving challenge. For example, for the immunity to SARS-CoV-2 research project Mercury, Hygiea and Neptune type astrology factors may feature, whereas solving human trafficking problems, predicting suicide vulnerability or predicting a predisposition for addiction at birth, would each use a potentially different feature set (solution).

If we can consistently problem solve and predict (probability rating) using exponential technology with an astrological feature set – in a space where all else being equal, other feature sets are not successful – then in addition to solving real-world problems, we also consistently validate the astrological “as above, so below” maxim.

Exponential technology needs big data. The feature set dictates what type of data is required for the machine learning algorithm.

Collaboration with other research projects has massive benefits – for example, data used by other SARS-CoV-2 research projects trying to solve the same problem – would be ideal. Research project reputation and credibility are important, giving access to this type of collaboration that comes with the benefits of valuable resources like data. If this data is not available from existing sources (or available but incomplete), there would be a requirement to build structures to gather/create/merge data, which can be time-consuming and expensive but sometimes necessary.

Let’s assume data are available from a reputable medical research project working to achieve the same goal. This includes 500 000 random records of SARS-CoV-2-diagnosed-symptomatic-ill-deceased (DSID) humans and 500 000 records of humans exposed to SARS-CoV-2-DSID family members (or friends) but not becoming symptomatic (diagnosed-symptomatic-ill) themselves.

400 000 of the 500 000 records of each group would be used to train the machine learning neural net algorithm to produce a set (fabric) of advanced patterns of what (1) vulnerability (lack of immunity) and (2) resilience (immunity) “looks like”. Once this has been achieved, the remaining 200 000 records (100 000 from each group) would be mixed and run blind through the trained algorithms to generate a probability rating for each record (human). The calculated probability rating is then compared to the actual data which signals whether our algorithm/feature set works or not. This is where the success resides – in whether we can make predictions with significant accuracy. Once we show we can consistently predict (using existing known data), the goal is achieved. There would undoubtedly be other research projects doing the same research and predicting with their own feature sets. We would collaborate and replicate each other’s results, helping each other progress.

I’ve over-simplified the project for the purpose of communicating the AI concept and making a point. The advantage of the AI approach is that it is focused on the challenge of solving a real-world problem. The astrological nature or blend of the feature set is confidential Intellectual Property (IP). All that is required for solution credibility, is to produce consistently significant predictions, initially verified and intermittently verifiable by actual data. These types of initiatives will generate quick wins for astrology research projects and this type of research, leveraged by exponential technology and science is what will drive the revolution of astrology.

If successful, the identity, practice and utility of astrology will be transformed. In its new form, what will remain of astrology is an elusive translation of “as above, so below” nestled deep in the feature set. We will look back and marvel at how we “manually” generated patterns with multi-level integration of complex, multivalent symbolism without the support of advanced machine learning algorithms. Or maybe not? Astrology will need to embrace the revolution to find out.

Selected Sources

Jarry, Jonathan. 2020. McGill.ca. “How Astrology Escaped the Pull of Science”.

Oshop, Renay. 2017. NewThinkingAllowed.org. https://www.newthinkingallowed.org/renay-oshop-peer-reviewed-science-comes-to-astrology-345/.

Steyn, Richelle & Currey, Robert. 2021. Astrology News Service YouTube Channel. How Sceptics Distort the Truth about Astrology.

Steyn, Richelle & Campion, Nicolas. 2021. Astrology News Service YouTube Channel. The Most Significant Prediction made by an Astrologer.