There is real AI in the world based on training on real data, especially in medicine. We are starting to see practical AI in every aspect of diabetes of all kinds, brought together in the Lancet paper below. Now I think that we can all agree here that there is too much Artificial Stupidity in the world, aka AI Slop, as though we didn’t have enough of the real thing. We can also agree that thieving data center builders need to be reined in with requirements to provide renewable electricity and industrial heat pump cooling before the computers are turned on.
I can confidently predict that the world of diabetic quackery will go all in on AI, as it has done on the bogus wristwatch blood glucose sensors that we have occasionally looked at here. I will not get started today on RFK jr. claiming that Type 2 diabetes is “curable” except to note that he is proof that Natural Stupidity continues to be more malignant than the artificial kinds.
Artificial intelligence (AI) has the potential to improve primary diabetes care in low-income and middle-income countries (LMICs), where the rising burden of disease contrasts sharply with limited health-care resources. Emerging evidence shows the promise of AI for screening, risk prediction, monitoring, and personalised management of diabetes and its complications. However, substantial barriers remain, including infrastructure deficits, data fragmentation, equity and inclusivity challenges, limited prospective validation, and concerns about the acceptability, sustainability, and regulatory oversight of AI. The effective integration of AI into primary diabetes care will depend on coordinated investment in foundational infrastructure that includes large-scale development and rigorous validation of novel AI models for use by primary care physicians and patients across diverse populations. AI initiatives are also needed to support interdisciplinary and international collaborations spanning clinical, technical, and policy domains to ensure successful implementation. By aligning technological innovation with health care needs, AI could evolve from a proof-of-concept tool to a practical enabler of equitable, scalable, and cost-effective diabetes care in LMICs. In this Personal View, we outline the major opportunities and challenges of applying AI to primary diabetes care in LMICs, and propose directions for future development and implementation.
References
The paper above gives these 80 references. Some of these papers are about the nature of the problems we diabetics face around the world, medical, social, technological, and so on, or look at existing datasets to consider what we need for effective AI training to benefit patients and societies. Some, highlighted in bold, particularly take on AI issues.
I trust that it is clear that I have not read all of them yet. This is a growth field, where what is available today will be dwarfed by developments over the next few years.
I have been an avid reader of science fiction since childhood. Nobody whom I know of foresaw the AI boom. I have seen plenty of space travel and robot science fiction, and a few tales that foretold atomic weapons or Global Warming catastrophes or communications satellites in geosynchronous orbits. There are tales of computers like Skynet or Colossus taking over the world, but not practical AI, nor, for that matter, the current wave of Artificial Stupidity polluting the InterWebz. We could talk about a few Heinlein and Asimov tales of beneficent computer-operated governments, but let’s get back to diabetes, where we currently need all the help we can get.
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