The physicist and philosopher Hermann von Helmholtz, whose foundational contributions to physics you all know very well, also invented “psychophysics,” a paradigm for phenomenology by
– inferring minimal predictive quantitative models;
– combining physical calculations and behavioral studies to establish that human color vision is trichromatic.
Detailed mechanisms were confirmed a century later by electro/neurophysiological, genetic/genomic and biochemical methods. Now phenomenology can drive development of novel AI/machine learning technology by elucidating the neuroscience, principles and computational algorithms of cognitive processing in humans and animals. Think of, for example, generalized adversarial networks [GAN], the state of the art in deconstructing human visual processing.
Cephalopods (octopus, cuttlefish, and squid) modulate their skin color and texture to match their marine backgrounds on millisecond timescales; in this sense, they “report” to us their perceptions. I will describe how biologists in my unit at OIST have developed a flexible model organism ideal for deconstructing this process. Living organisms are wetware, and as such one role of science is to establish their device characteristics. My unit is pursuing the development of customized physical hardware, algorithms, and software to quantitatively probe the i/o response function of this model organism, and to reverse engineer the biophysics and neural algorithms of its cognition and consciousness.