I feel as though they are talking about me (and no that isn’t paranoia).
I feel as though they are talking about me (and no that isn’t paranoia).
Editor’s pick: Excluded from the uncanny valley
From Bob Cockshott
New Scientist. Issue 3100. November 19th 2016. p.60.
The experience described in the letter seems to suggest that there is more to face recognition than simple memory or faces, or could it be that there are aspects of the perception of faces in particular that make them especially memorable? Faces are easy to personify because they are usually found on people. Perhaps it is the ability to detect the person behind the face that has become amiss in the letter’s author following his stroke, and maybe this ability feeds into face memory? Such a relationship would explain the author’s inability to notice the uncanny valley, and it would also explain why a personifying synaesthete like myself is also a super-recognizer.
I’ve had a read of the interesting article by Laura Spinney that this letter was a comment about, and I think the Perceptual Mismatch Theory of the Uncanny Valley Effect probably offers a more plausible explanation of my a prosopagnosic might be unable to detect the uncanny valley than the competing Category Uncertainty Theory. The article explained the two theories and evidence supporting them. To summarise, the CUT explains the UVE as the result of confusion about what type of thing one is looking at (for example robot or human?), while the PMT explains the UVE as resulting from unease or perceptual confusion when different features or parts of the thing or being viewed have dissimilar levels of human-like appearance (for example the face and skin look realistic but the eyes do not move like human eyes). I think the case of a prosopagnosic not detecting the UVE when people with normal face perception do is support for the PMT theory rather than the other because as far as I know, prosopagnosia does not involve inability to classify faces or bodies as human or non-human, while I believe there is evidence supporting the idea that prosopagnosia can be the result of not being able to perceptually integrate the features of the face as a whole that is recognizable as a unique or distinctive mix of many attributes and features. A non-prosopagnosic person should be able to perceive a face or body as a whole made up of parts, and notice if one or more elements has a level of humanity that does not match other parts, as in the PMT, while a prosopagnosic might not. Of course, research is needed to investigate my armchair speculations.
I’d love to be reading and writing about fascinating and largely unexplored topics in neuroscience and psychology such as superagers, super-visualisers and aphantasia, but Christmas and all the associated this and that, and the everyday business of parenting in the summer holidays and housekeeping takes up my time.
Interesting to read that aphantasia was apparently first identified by Sir Francis Galton in 1880, even though it has only recently been given the name aphantasia and come to the attention of contemporary researchers. Galton was also one of the earliest researchers to describe various varieties of synaesthesia, before they were all named as such. Galton was one hell of a scientist, back in the days when a man of means could spend his days exploring vast unknown territories of psychology. Is research so different these days? Science is now a bit more open to women researchers, and there’s still much to explore.
Zeman, A., Dewar, M., & Della Sala, S. Lives without imagery–Congenital aphantasia. Cortex, 3.
Revell, Timothy Concerns as face recognition tech used to ‘identify’ criminals. New Scientist. December 1st 2016.
Garvie, Clare, Bedoya, Alvaro and Frankle, Jonathan The perpetual line-up: unregulated police face recognition in America. Center on Privacy & Technology at Georgetown Law. OCTOBER 18th 2016.
Is there really a criminal face? I don’t think the research discussed in the New Scientist article settles the debate by any means, but at least the controversial idea is opened up for investigation. If there is one my guess is that it is a look that coincides with the Australian face (every race and nation has a distinctive averaged facial type, apparently). European colonisation of Australia began as a penal colony and thus a good part of the white genetics of Australians arrived in this country through people identified as criminals. My best guess is that the crim face has a large straight nose, thin lips and puffy, small eyes. I’d guess this unattractive face could in itself be a social and economic disadvantage, or could be symptomatic of a phenotype that includes some degree of intellectual impairment. I think if there is a crim face it might have little to do with personality but a lot to do with disadvantage, but this is all speculation.
I think it is worth noting that claims made in the print version of this article about supposed advantages of AI over humans in face recognition skills such as identifying age, gender, ethnicity and tiredness by looking at faces presumably only apply to humans of average face recognition ability who maybe are not as exhaustively trained in these skills as the AI systems have been. One cannot compare human ability with AI in face recognition until appropriately trained super-recognizers (representing the top end of human ability) have been pitted against machines. I’m guessing this hasn’t been done.
Perhaps the most important part of this article is right at the end; “…the majority of US police departments using face recognition do little to ensure that the software is accurate.” That certainly is not good enough. Human super-recognizers have abilities that have been proven in scientific testing and also in practice in policing in the UK. Why do so many people persist in the assumption that machines must be better than humans in visual processing, in the face of an abundance of evidence? The link in the New Scientist article to the website of the researchers who have criticized the use of face recognition technology in law enforcement in the United States of America is worth a look for sure.
I didn’t expect to be reading this but I can recognize that this discovery seems to explain why face recognition is human cognitive ability that hits its peak surprisingly late in human development, and I’m now wondering how this fits into my theories about the relationship between my super-recognition and my synaesthesia, and that includes wondering how this discovery fits with my immune hypothesis of synaesthesia (which is all about pruning rather than proliferation), and of course I’m wondering how this fits in with what is known about super-recognizers. I guess I should just calm down and read the full text.
Coghlan, Andy Brain’s face recognition area grows much bigger as we get older. New Scientist. January 5th 2017.
Jesse Gomez, Michael A. Barnett, Vaidehi Natu, Aviv Mezer, Nicola Palomero-Gallagher, Kevin S. Weiner, Katrin Amunts, Karl Zilles, Kalanit Grill-Spector Microstructural proliferation in human cortex is coupled with the development of face processing. Science. January 6th 2017.
I think it is worth noting that this article and a similar one in a November issue of New Scientist have announced the commencement of use of this technology, rather than reviewing the performance of it or reporting the proven effectiveness of it. I’m skeptical.
Vincent , James Baidu swaps tickets for facial recognition in historic Chinese ‘water town’. Verge. November 17th 2016.
Wardrop, Ian and Neave, Richard I know that face. New Scientist. No 3101 November 26th 2016.
Just what I’ve been writing about for yonks now.
Thomson, Helen Synaesthetes who ‘see’ calendar hint how our brains handle time. New Scientist. November 16th 2016.
Revell, Timothy Glasses make face recognition tech think you’re Milla Jovovich. New Scientist. November 1st 2016.
Hodson, Hal Police mass face recognition in the US will net innocent people. New Scientist. October 20th 2016.
United States Government Accountability Office Face Recognition Technology: FBI Should Better Ensure Privacy and Accuracy. May 2016.
Had you assumed that hiring human super-recognizers to perform face recognition tasks would be less effective, less accurate and more open to bias than using technology? Think again.