The brain, the artificial neural network and the snake: why we see what we see
- PDF / 701,362 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 76 Downloads / 187 Views
ORIGINAL ARTICLE
The brain, the artificial neural network and the snake: why we see what we see Carloalberto Treccani1 Received: 29 July 2019 / Accepted: 18 August 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract For millions of years, biological creatures have dealt with the world without being able to see it; however, the change in the atmospheric condition during the Cambrian period and the subsequent increase of light, triggered the sudden evolution of vision and the consequent evolutionary benefits. Nevertheless, how from simple organisms to more complex animals have been able to generate meaning from the light who fell in their eyes and successfully engage the visual world remains unknown. As shown by many psychophysical experiments, biological visual systems cannot measure the physical properties of the world. The light projected onto the retina is, in fact, unable to specify the physical properties of the world in which humans and other visually ‘intelligent’ animals behave; however, visual behaviours are habitually successful. Through psychophysical evidence, examples of the functioning of Artificial Neural Networks (ANNs) and a reflection upon visual appreciation in the cultural and artistic context, this paper shows (a) how vision emerged by random trial and error during evolution and lifetime learning; (b) how the functioning of ANNs may provide evidence and insights on how machine and human vision works; and (c) how rethinking vision theory in terms of trial and error may offer a new approach to better understand vision—biological and artificial—and reveal new insights into why we like what we like. Keywords Human vision · Machine vision · Brain · Artificial neural network · Visual appreciation
1 Introduction It is possible to consider metaphors as a way to attribute human characteristics to an animal, object or any other subject. At the same time, it is important to consider that abstract (non-physical) phenomena are understood through the attribution of physical features to the phenomena. For instance, the sentence inflation rose in July is interpreted using two concrete physical phenomena: inflation (an increase in size) and rising (a change in position) (Pinker 2013). Metaphors are used in science and philosophy to explain the unknown, as well as a tool to generate new knowledge and provide a better understanding of many phenomena (Zarkadakis 2015). Every century, perhaps even every decade, has its own metaphors, and “when the use of a specific metaphor ceases and a new metaphor takes its place, we have
a ‘paradigm shift’ in the way science explains the world” (Zarkadakis 2015). One main source of metaphors is the human brain and body. In the Book of Genesis Adam, for instance, is created out of dust and then life is infused into it—interestingly, the word human comes from the Latin humus, which means ground or earth. Later on, in the third century BCE, the invention of hydraulic and pneumatic systems provided a new paradigm to understand the human body as a “dynamica
Data Loading...
