"The discovery of quantitative relationships between retinal appearance and systemic pathophysiology readily aligns with pre-established conceptions of microvascular and degenerative tissue-level insults20. However, deep learning has shown that these algorithms demonstrate capability in tasks which were not previously thought possible21. Harnessing this power, new insights into relationships between retinal structure and systemic pathophysiology could expand existing knowledge of disease mechanisms. A study by Poplin et al. demonstrated a deep-learning learning algorithm which could accurately predict cardiovascular risk factors from fundus photos22; More surprising to ophthalmologists was the successful prediction of demographic information such as age and gender, the latter with an area under the curve (AUC) of 0.97. Here, the physiologic cause and effect relationships are not readily apparent to domain experts21. Predicting gender from fundus photos, previously inconceivable to those who spent their careers looking at retinas, also withstood external validation on an independent dataset of patients with different baseline demographics23. Although not likely to be clinically useful, this finding hints at the future potential of deep learning for the discovery of novel associations through unbiased modelling of high-dimensional data."
This makes me think of a concept I heard once on the Hard Fork podcast called the obsolescence regime.
I'm in the process of writing a historical hard sci-fi book about the future of AI (see note below) and here's the way one of the characters describes obsolescence regime to another:
“The concept behind obsolescence regime is that AI’s sophistication will outstrip our own. Eventually, it would assume greater control over critical decisions that govern human life. At that point, we’d find ourselves relying on AI for strategic guidance, gradually losing our own grasp on how our societies and destinies should be shaped. With AI’s expansive data-processing abilities and its skill at recognizing patterns and forecasting outcomes, there’s a possibility it might become superior to humans in sectors like commerce, governance, and even military operations. Its key advantage, of course, is that AI operates free from emotional influence, creating decisions rooted firmly in logic and evidence. That could undermine the more subjective, bias-driven side of human decision-making.”
This news about AI recognizing sex from retinal scans seems aligned with this idea.
The question is, can we do anything about it?
Could humans catch up to the degree of understanding of the technology we're creating?
Maybe not.
Note: I've been working on the book, titled "Glorified Ants," since June 2023. I should have the first draft ready by the end of this week! Lemme know if you wanna read the first draft and provide edits ;)