Elon Musk recently announced that his AI, Grok, could read medical brain scans. This got me thinking…..I wonder if he/she/it could also read CT brain scans through the lens of GNM?
I asked the question (which is detailed below), but it came back with some inaccuracies regarding the conflicts affecting the different brain layers, which I duly corrected and Grok accepted. This sparked off a whole line of enquiry into Grok’s current stance on the Biological Laws and whether AI may be useful in the practice of GNM/GHK.
I encourage everyone to ask questions and engage in conversation with Grok and other AI (and correct replies if need be) as it is something that is always evolving and learning, and we can therefore be involved in its training. The more we engage, the more it will learn!
-
Nature of Biological Laws: Unlike the physical sciences where laws like those of gravity or thermodynamics are precise and have universal applicability, biological laws often come with exceptions due to the complexity and variability of living organisms. The search for biological laws has been debated, with some suggesting that biology might not have true laws in the classical sense because of these exceptions (). This complexity means that while certain patterns or principles might be empirically observed, they may not hold universally across all biological contexts, which can make them less appealing for the straightforward application in medical research.
-
Empirical Discovery vs. Applicability: Biological phenomena are often discovered empirically through observation and experimentation. However, the translation of these discoveries into medical practice involves additional layers of complexity such as ethical considerations, practical applicability, and the need for extensive clinical trials. For instance, Mendel’s laws of inheritance were empirically discovered well before the mechanisms of genetics were understood, and even today, they are applied with caveats due to genetic exceptions and complexities like epigenetics ().
-
Focus on Applicability Over Theory: The medical industry primarily focuses on practical applications that can lead to treatments or therapies. While understanding the fundamental laws of biology is crucial, the industry often prioritizes research that can lead directly to health improvements. This means that theoretical or foundational biological laws might not be pursued further if they do not have immediate or foreseeable applications in medical contexts ().
-
Economic and Practical Constraints: Research in medicine is often driven by funding which is influenced by potential economic returns, public health priorities, and regulatory pathways. Fundamental biological research might not yield direct, profitable outcomes in the short term, leading to less investment from the medical industry in pure biological law research unless it clearly aligns with these priorities ().
-
Complexity and Variability: As noted, biological systems are inherently variable, with responses to environmental changes being highly context-dependent. This variability complicates the formulation of laws that can be universally applied in medicine, where treatments need to be both effective and safe across diverse populations ().
-
Current Research Paradigms: Modern medical research tends to focus on specific diseases, mechanisms, or drug development rather than broad, foundational laws of biology. The push towards personalized medicine, for example, looks at individual genetic and molecular profiles, which might overshadow the study of broader biological laws ().