‘The structure of academia rewards people for developing one theory and sticking to it. There are few academic incentives for reaching a consensus or even hashing out the relative probabilities of different views.’
I agree with this, but I just wanted to link out to a new paradigm that I think gets good traction against this problem (and also highlights some ongoing consciousness research). This is being funded by the Templeton Foundation (a large philanthropic science funder), and essentially they’ve got leading advocates of two leading consciousness theories (global workspace theory and integrated information theory; see here) to go head-to-head in a kind of structured adversarial experiment. That is, they’ve together developed a series of experiments, and together agreed beforehand that ‘if the results go [x] way, this supports [x] theory’. Afaik, the results haven’t been published yet.
Disclaimer that in a previous life I was a comparative psychologist, so I am nerdily interested in consciousness. But I do think that there is a tension between taking a strong view that AI is not conscious/ will not be conscious for a long time, versus assuming that animals with very different brain structures do have conscious experience. (A debate that I have seen play out in comparative cognition research, e.g. are animals all using ‘chinese room’ type computations). Perhaps that will turn out to be justified (e.g. maybe consciousness is an inherent property of living systems, and not of non-living ones), but I am a little skeptical that it’s that simple.
Hey Christian, thanks for your comment! I totally agree that ML has great potential for diagnosis (in dentistry but also within the field of medical care more broadly– e.g. I was reading about this grant from Gates the other day, it’s a diagnostic ultrasound for maternal conditions). Caveat that I’m not sure that the average person would trust an ML diagnosis over a ‘real person’ diagnosis (at least, not yet), and I think it would be a while until roll-out in an LMIC type context. Nonetheless, I think this is a promising area which I want to check out in more detail.
Within the field of oral health though, I think that investing in preventative treatment is currently more promising than diagnostics/ curative treatment: i.e. while I think that training up local dentists may be cost-effective, it seems a little borderline. However, preventative treatment (aka fluoride) seems to be extremely cost-effective, and we already know how to do it. This is mainly because salt and milk fluoridation appear to work and are insanely cheap—that’s where my $2 WELLBY/ $9 DALY figures are coming from.