May 25, 2018 09:02 PM
https://aeon.co/essays/seeing-is-not-sim...-and-naive
EXCERPT: [...] When we consider scientific observations – those paragons of a purportedly objective gaze – we find in fact that they are often complex, contingent and distributed phenomena, much like human vision itself. Assemblies of high-powered machines that detect the otherwise undetectable, from gravitational waves in the remotest cosmos to the minute signals produced by spinning nuclei within human cells, rely on many forms of ‘sight’ that are neither simple nor unitary. By exploring vision as a metaphor for scientific observation, and scientific observation as a kind of seeing, we might ask: how does prior knowledge about the world affect what we observe? If prior patterns are essential for making sense of things, how can we avoid falling into well-worn channels of perception? And most importantly, how can we learn to see in genuinely new ways?
Scientific objectivity is the achievement of a shared perspective. It requires what the historian of science Lorraine Daston and her colleagues call ‘idealisation’: the creation of some simplified essence or model of what is to be seen, such as the dendrite in neuroscience, the leaf of a species of plant in botany, or the tuning-fork diagram of galaxies in astronomy. Even today, scientific textbooks often use drawings rather than photographs to illustrate categories for students, because individual examples are almost always idiosyncratic; too large, or too small, or not of a typical colouration. The world is profligate in its variability, and the development of stable scientific categories requires much of that visual richness to be simplified and tamed.
[...] Hold up your hand in front of your face: how can you see what’s there? Parsing meaning from randomness – the signal from the noise – is fundamental to both sight and scientific observation. Unless we are blind, our open eyes are flooded with photons at every moment, a ‘noisy’ stream of information that is then launched from the retina, travelling as electrochemical impulses along the optic-nerve pathways. These are taken up by neural assemblies and, in the dark cavern of the skull [...] the brain sifts that welter of data for ‘signals’ that conform to particular patterns. [...] Some neural assemblies specialise in detecting certain shapes, such as edges or corners; others specialise in collecting those shapes into higher-order schemes, such as a coffee cup, the face of a friend, or your hand.
These internal visual elements are a mix of predilections that we are born with and patterns learned from personal experience; how they affect our perception varies according to our understanding and expectations [...] Vision is not only personal and patterned, but also complex and spatially distributed. [...]
In science, seeing things afresh sometimes demands a concerted (and contested) shift in paradigms, such as the move from Ptolemy’s map of the planets to those of Copernicus and Galileo. On other occasions, it happens by accident. In a fundamental sense, all of the output of our instruments is signal; noise is just that part we are not interested in. This means that separating out the signal depends upon who is doing the observing and for what purpose. [...]
Because of the complexity of both visual experience and scientific observation, it is clear that while seeing might be believing, it is also true that believing affects our understanding of what we see. The filter we bring to sensory experience is commonly known as cognitive bias, but in the context of a scientific observation it is called prior knowledge. To call it prior knowledge does not imply that we are certain it is true, only that we assume it is true in order to get to work making predictions. [...]
If we make no prior assumptions, then we have no ground to stand on. The quicksand of radical and unbounded doubt opens beneath our feet and we sink, unable to gain purchase. We remain forever at the base of the sheer rock face of the world, unable to begin our climb. Yet, while we must start with prior knowledge we take as true, we must also remain open to surprise; else we can never learn anything new. In this sense, science is always Janus-headed, like the ancient Roman god of liminal spaces, looking simultaneously to the past and to the future. Learning is essentially about updating our biases, not eliminating them. We always need them to get started, but we also need them to be open to change, otherwise we would be unable to exploit the new vistas that our advancing technology opens to view....
MORE: https://aeon.co/essays/seeing-is-not-sim...-and-naive
EXCERPT: [...] When we consider scientific observations – those paragons of a purportedly objective gaze – we find in fact that they are often complex, contingent and distributed phenomena, much like human vision itself. Assemblies of high-powered machines that detect the otherwise undetectable, from gravitational waves in the remotest cosmos to the minute signals produced by spinning nuclei within human cells, rely on many forms of ‘sight’ that are neither simple nor unitary. By exploring vision as a metaphor for scientific observation, and scientific observation as a kind of seeing, we might ask: how does prior knowledge about the world affect what we observe? If prior patterns are essential for making sense of things, how can we avoid falling into well-worn channels of perception? And most importantly, how can we learn to see in genuinely new ways?
Scientific objectivity is the achievement of a shared perspective. It requires what the historian of science Lorraine Daston and her colleagues call ‘idealisation’: the creation of some simplified essence or model of what is to be seen, such as the dendrite in neuroscience, the leaf of a species of plant in botany, or the tuning-fork diagram of galaxies in astronomy. Even today, scientific textbooks often use drawings rather than photographs to illustrate categories for students, because individual examples are almost always idiosyncratic; too large, or too small, or not of a typical colouration. The world is profligate in its variability, and the development of stable scientific categories requires much of that visual richness to be simplified and tamed.
[...] Hold up your hand in front of your face: how can you see what’s there? Parsing meaning from randomness – the signal from the noise – is fundamental to both sight and scientific observation. Unless we are blind, our open eyes are flooded with photons at every moment, a ‘noisy’ stream of information that is then launched from the retina, travelling as electrochemical impulses along the optic-nerve pathways. These are taken up by neural assemblies and, in the dark cavern of the skull [...] the brain sifts that welter of data for ‘signals’ that conform to particular patterns. [...] Some neural assemblies specialise in detecting certain shapes, such as edges or corners; others specialise in collecting those shapes into higher-order schemes, such as a coffee cup, the face of a friend, or your hand.
These internal visual elements are a mix of predilections that we are born with and patterns learned from personal experience; how they affect our perception varies according to our understanding and expectations [...] Vision is not only personal and patterned, but also complex and spatially distributed. [...]
In science, seeing things afresh sometimes demands a concerted (and contested) shift in paradigms, such as the move from Ptolemy’s map of the planets to those of Copernicus and Galileo. On other occasions, it happens by accident. In a fundamental sense, all of the output of our instruments is signal; noise is just that part we are not interested in. This means that separating out the signal depends upon who is doing the observing and for what purpose. [...]
Because of the complexity of both visual experience and scientific observation, it is clear that while seeing might be believing, it is also true that believing affects our understanding of what we see. The filter we bring to sensory experience is commonly known as cognitive bias, but in the context of a scientific observation it is called prior knowledge. To call it prior knowledge does not imply that we are certain it is true, only that we assume it is true in order to get to work making predictions. [...]
If we make no prior assumptions, then we have no ground to stand on. The quicksand of radical and unbounded doubt opens beneath our feet and we sink, unable to gain purchase. We remain forever at the base of the sheer rock face of the world, unable to begin our climb. Yet, while we must start with prior knowledge we take as true, we must also remain open to surprise; else we can never learn anything new. In this sense, science is always Janus-headed, like the ancient Roman god of liminal spaces, looking simultaneously to the past and to the future. Learning is essentially about updating our biases, not eliminating them. We always need them to get started, but we also need them to be open to change, otherwise we would be unable to exploit the new vistas that our advancing technology opens to view....
MORE: https://aeon.co/essays/seeing-is-not-sim...-and-naive
