Light Truth and Illusion

The talk I gave yesterday at the MPA Nanotech conference had plenty of normal attributes to criticize and then even some more. Mainly I was speaking about regenerative medicine, which is something I didn’t even know existed last year at this time. I admitted this the second I started talking as way to disarm the attendees from shooting it back at me later. I talked about what I know with some authority. When I spoke about new topics I became like a child discovering the wonders of the sea his first time at the beach. In this case those are new body parts made of silly putty, which I must admit sounds even more childish than I mean it to. When questions came around  I got one which was completely different, and to me must have come out of a philosophical wing of the nanotech community that I didn’t know of. The question surrounds some images I had taken at high resolution of the surface of a pig’s stomach called ECM, and of a piece of rubber (this is the silly putty). These are two kinds of scaffolds that can be used to regenerate organs. The man, who I later learned was not a philosopher at all but rather a material scientist at a Polish technical university, asked me “how do you know those images are real?” I was certain that this was a language issue, so I spoke slowly to him in a condescending way that I  try to avoid in complicated technical talks with people who come from different linguistic origins. I told him that I used a highly repeatable microscope and special image recognition software that my company actually made, and that indeed I could assure him that the images were in fact real. That wasn’t the question he was asking exactly however. He wanted to know how I could trust imaging for evaluating nanoporosity, which was what I was showing. This was far deeper, and I became defensive, telling him with even more superiority than before that light had been well established for a long time as a reality of physics. “But they are just grey pixel values. You should use other methods such as absorption of nanoparticles to verify your findings” he told me. The fight went on for some time with the rest of the room joining the debate with a surprising number, I thought, agreeing with the Polish scientist. I had truly entered a debate about what type of physics was more real. Was a photon less real than a carbon particle? Were pixels more removed from direct observation than weight measurements after absorbing nanoparticles? I didn’t agree with his argument, but appreciated it all the same.

Right after I sat down from the debate I started thinking about something my wife Marine had shown me. She is a speech and language pathologist. She showed me an example of something called the McGurk effect. (see video below)This is an illusion of sorts. A man repeats a sound and we watch him. We then see him with a different mouth movement than the word uses. We hear a change in sound, even though he has not changed the sound at all.  This is because our visual sensation over powers our auditory sensation. This is verified when we close our eyes, and the sounds are clearly perceived as being the same. Marine works with children with autism and told me that with autism the McGurk effect is not always present, which is a fascinating look at the symptoms of the different neural structures of people.

So what does the McGurk effect have to do with my experience at the conference? Maybe nothing. Maybe it is as simple as Polish material scientists view the world differently than American physicists. That however is only part of it. It is true that different disciplines in science see things differently. We are trained differently and it makes us skeptical of other approaches. Looking at it this way both he and I were objectively wrong. We should have realized that it was just a matter of perception. From another perceptive however it could be like the other aspect of the McGurk effect, and that is not the difference between autistic and non-autistic observation, but rather the accuracy of the autistic observation. It is likely that the McGurk effect points to an important survival skill. Perhaps vision is a more urgent sense to rely on. What the McGurk effect shows however is that the non-autistic sense is not as accurate as the autistic perception. So both views of the world have a subjective truth, but only the autistic view is actually the objective truth.

So what about using microscopes with sensors and image processing rather than weighing nanoparticles after absorption? Is one more objectively real than the other? Perhaps the Polish scientist is right in one way. We are programming our computers and designing our sensors with our human minds. These are the same minds that survive well due to the misinformation as shown in the McGurk effect. But science is more of an autistic style endeavor in some respects. We avoid human variability whenever possible in order to see what is really going on. The answer still remains unclear to me however. When working in domains such as the nanoscale, we are forced to create information using algorithms. We make an artificial vision of the invisible. We use computers to model what we expect is happening on a scale we can see with our eyes. When creating these models, more and more we use a form of AI which tries to learn as we do, taking into account variability and disregarding what is not important. In essence we are programing a McGurk effect style response into our machines, and those machines then tell us about a reality which is similar to the subjective one we experience. We don’t often even admit to ourselves that this is what we are doing, but it really is. Maybe this is the point of the Polish scientist, but if it was he is also missing the McGurk style effect in his own measurements which are also designed by humans, and involve several steps of extrapolation where we are likely blinded by our own errors the way that we are when viewing McGurk.

All of this leads to an important point though. Science must aim to observe as independently as possible, or when not, to acknowledge what it is doing. Bio mimicry for example is a technological human activity which embraces and acknowledges perception as the basis for creating AI. The problem is that we remain stuck in a loop of thought on this topic. We have our always compensating brains deciding what to do, even when we allow our machines to learn.