There is no magic to AI. Today's AI is a collection of methodologies that apply extreme reductionism to Big Data in order to elicit patterns, calculate probabilities or make predictions.
Tools which may be used in such a comprehensive research, including molecular biology applied to field studies, require a methodological shift from the reductionism that has been used until recently as a basic axiom in interpretation of data.
Scientific reductionism is an undeniably powerful tool, but it can mislead us too, especially when applied to something as complex as, on the one side, a food, and on the other, a human eater.
Even if reductionism should fail to apply to our world and our scientific history, it might be of interest to consider what reality would be like in other worlds where reductionism does hold, worlds similar to ours in containing many different theories or conceptual frameworks but ones tied together by reductive links.
Navigating a lively intellectual voyage between the shoals of strict reductionism and relativism, Rabins maps a three-facet model of causality and applies it to a variety of questions in science, medicine, economics, and more.
Reductionism as a vague doctrine exerts a strong hold over those who would never dream of actually applying it to the full extent its creators envisaged.
But even if one accepts reductionism, and so abandons appeal to some further fact about separately existing entities to explain personal identity, and even if one also believes that identity is not what matters in survival, one still has much work to do before being able to apply the theory to ethics.
Reductionism as a way of understanding food or drugs may be harmless, even necessary, but reductionism in practice can lead to problems.
This involves a crude reductionism.
