"I used to think great teachers inspire you. Now I think I had it wrong. Good teachers inspire you; great teachers show you how to inspire yourself every day of your life. They don't show you their magic. They show you how to make magic of your own." - Alfred Doblin
"In library and information science (LIS), we seek to understand the nature, organization, and use of information in life. Scholarship, to this end, has been unevenly distributed. Research has predominantly focused on academic or professional contexts, which are a narrow slice of the human experience. There are a minority of studies of information phenomena within everyday situations, and only a few about the universally cherished realm of leisure. As a result, theoretical insights about the engagement with information are unduly narrow and rational in character, and information provision to everyday life and leisure settings may fall short of potential. To broaden understanding and to better serve leisure audiences, I am exploring information phenomena in the context of serious leisure (Stebbins, 2001). To organize my research career, I draw upon the Serious Leisure Perspective (SLP), a grounded theory of leisure introduced in 1973 by sociologist Robert A. Stebbins. Serious leisure is the systematic pursuit of, "an activity that participants find so substantial and interesting that, in the typical case, they launch themselves on a leisure career centered on acquiring and expressing its special skills, knowledge, and experience" (Stebbins, 1992, p. 3)."
Mihai Nadin - Adventures in Semiotics and Anticipation
Mihai Nadinis a scholar and researcher in electrical engineering, computer science, aesthetics, semiotics, human-computer interaction (HCI), computational design, post-industrial society, and anticipatory systems. His publications on these topics number over 200, and he has lectured throughout the world. Currently Mihai Nadin is a professor at the University of Texas at Dallas. He is director of the Institute for Research in Anticipatory Systems.
Abstract: There is no way to acquire, store, and disseminate knowledge other than semiotically. Yet semiotics is hardly acknowledged in science, and not at all as science. Were it not for the fame of a few writers (Barthes, Derrida, and especially Eco), associated more with the semiotics of culture, few would even know that such a knowledge domain exists. In the age of computers, genetics, and networks—all of underlying semiotic condition—semiotics would at best qualify as pertinent to an obscure past, but insignificant for current endeavors. Gnoseologically, there is little to gain from acknowledging the shortcomings of semiotics. Epistemologically, quite a bit is at stake in grounding semiotics among the fundamental sciences. For this to come about, new interrogations become necessary: Why knowledge? What is knowledge? What kind of knowledge? How is knowledge acquired? One way or another, the answer will acknowledge semiotic processes as a necessary factor. The perspective advanced in this chapter relies on an understanding of the living, and, in particular, of the human being, that ascertains anticipation as definitory. The future is made part of the present via semiotic processes. This is significant because in the age of neurons, suggestive of brain activity and of attempts to emulate it, to distinguish between knowledge supporting human activity, embodied in new technologies, and knowledge essential to the unfolding of the living becomes very difficult
Quotes from the paper:
"Semiotics is the awareness of change captured in representations. In terms of its meaning, it is the actions it informs."
"Nietzsche (cf. Colli & Montinari, 1975, p. 3) observed that “Our writing tools are also working, forming our thoughts.” As we program the world, we reprogram ourselve. [...] Associated with meaning, data becomes information."
"Semiotic awareness, which instantiates metacognition (knowing what we know) is nothing other than the realization that acting upon representations enhances the outcome of human activity."
"The human being “reads” nature as a “language” expression, and, in the process of knowing, generates new representations. Let us recall Lewis Mumford’s observations: No computer can make a new symbol out of its own resources,” (1967, p. 29)"
"From the perspective of knowledge, the following needs to be stated: If we could aggregate all representations we would still not capture the reality in its infinite level of detail; nor could we capture dynamics in its openendedness (not to say without affecting it). The living unfolds beyond our epistemological boundaries. We are part of it. Our change is part of a broader change, which, again, influences our own. The sequence is infinite. Therefore every representation contains the observed and the observer. If the representation is only a sign, dynamics is left out."
“The human brain has not changed at the anatomical level, but now it works differently,” (Togo & Cantelmi, 2012).
Expressed differently, semiotics is relevant for “engineering” interactions: recipes are the “shorthand” of cooking. They carry explicit instructions and implicit rules, that is, assumptions of shared experiences. Semiotics embodies the sharing, but does not substitute for the experience. The informational level corresponds to “fueling” the process, providing the energy. [...] Semiotics encodes in generating representations, and decodes in interpreting representations.
In this respect, law is a repetitive pattern. Physical phenomena are acceptably described in mathematical descriptions called laws. This is what Windelband (1894) defined as the nomothetic (derived from nomothé in Plato’s Cratylus, 360 BCE). The same cannot be said of living interactions, even if we acknowledge repetitive patterns. No living entity is identical with another. The living is infinitely diverse. Therefore, semiotics could qualify as the attempt to acknowledge diversity unfolding over time as the background for meaning, not for scientific truth. This is what Windelband defined as the idiographic. [...] Semiotic knowledge is about meaning as process.
Signs are “alive,” interacting with each other, self-reproducing as the context requires. Consequently, one might be inclined to see interaction processes mirrored into sign processes—or what Peirce called semiosis. But interactions are more than sign processes. Better yet: sign processes describe only the meaning of interactions, but not the energy processes under girding them.
When vitalism, as the doctrine of the élan vital (which some equate with the soul) was debunked, the questions of causality associated with the realization that the biosphere is not reducible to the physical were simply brushed aside. Over time, every scientist claiming that the living and non-living have a different dynamics was eliminated from the list of potential Nobel Prize nominees (and avoided). In recent years, this has started to change
Focusing on signs caused semiotics to miss its broader claim to legitimacy: to provide not only descriptions of the meaning of interactions, but also knowledge regarding the meaning of the outcome of interactions, the future.
As information theory—based on the en-compassing view that all there is, is subject to energy change—emerged (Shannon & Weaver, 1949), it took away from semiotics even the appearance of legitimacy. [...] But there is also a plus side to what Shannon suggested: Information theory made it so much more clear than any speculative approach that semiotics should focus on meaning and significance rather than on truth.
Parallel to this recognition is the need to assess meaning in such a manner that it becomes relevant to human activity. So far, methods have been developed for the experimental sciences: those based on proof, i.e., the expectation of confirmation and generalization. But there is nothing similar in respect to meaning, not even the realization that generalization is not possible; or that semiotic knowledge is not subject to proof, rather to an inquiry of its singularity. The nomothetic comprises positivism; the idiographic is the foundation of the constructivist understanding of the world (cf. Piaget, 1955; von Foerster, 1981).
Given the epistemological condition of mathematics, new evidence is not in the jargon of mathematics. A new mathematical concept or theorem is evidence. Probably more than science, mathematics is art. It is idiographic, not nomothetic knowledge. As we know from Turing and Gödel, it cannot be derived through machine operations (Hilbert’s challenge). If there is a cause for mathematics, it is the never-ending questioning of the world appropriated by the mind at the most concrete level: its representation. The outcome is abstraction. This is what informed Hausdorff (alias Paul Mongré) as he described human nature. There is, of course, right and wrong in mathematics, as there is right and wrong in art. But neither a Beethoven symphony nor Fermat’s conjecture (proven or not) is meant as a hypothesis to be experimentally confirmed. Each has an identity, i.e., a semiotic condition. Each establishes its own reality, and allows for further elaborations. Not to have heard Beethoven’s symphonies or not to have understood Fermat’s law does not cause bridges to collapse, or airplanes to miss their destinations.
Semiotics is not a discipline of proofs: The ambiguity of disease is reflected in the ambiguity of representations associated with disease. Better doctors are still “artists,” which is not the case with software programs that analyze test results. Diagnosis is semiotics, i.e., representation and interpretation of symptoms. They are both art and science. Machine diagnosis is information processing at work. Human diagnosis is the unity of information and meaning.
The goal is to make the reader aware of why even the most enthusiastic semioticians end up questioning the legitimacy of their pursuit.
15. INSIGNIFICANCE IS THE RESULT OF FAILED PRAGMATICS.
There are no evaluation criteria to help distinguish the “wheat” from the “chaff.” In the democratic model of science (semiotics and other fields), “Anything goes.” [...] What strikes the possible reader is the feeling that semiotics deals more with its own questions than with questions relevant to science, philosophy, or to today’s world.
Take only the still not concluded attempts to prove Fermat’s Theorem (most recently Colin McClarty, 2013). Fundamentally, the approach extends deep into the notion of representation. The very elaborate mathematical apparatus, at a level of abstraction that mathematics never reached before, makes the whole enterprise semiotically very relevant.[...] A question that begs the attention of semioticians is, “How far from the initial mathematical statement (Fermat’s Theorem) can the proof take place?” That is, how far can the representation of representation of representation, and so on extend the semiotic process before it becomes incoherent or incomprehensible?
Never before has language—in its general sense, not only as the language we speak—been as central to research as it is today. [...] Natural language is the most ubiquitous medium of interaction. It is involved in knowledge acquisition, in its expression, communication, and validation. Semiotics, if founded not around the sign concept—quite counter-intuitive when it comes to language (Where is the sign: the alphabet, the word, the sentence?)—but with the understanding of the interactions languages make possible, would contribute more than descriptions, usually of no consequence to anyone, and post facto explanations.
The subject ought to be understood as broadly as possible. This means that within the realm of the living, there is a whole gamut—from the mono-cell to homo faber—of representations to consider. Is there anything that qualifies as semiotically relevant across the various forms of the living? As already stated in the preliminaries, interaction is probably the most obvious aspect. At a closer look, the making of the living consists of integrated interactions—from the level of the cell to that of organisms. At all these levels, representations are exchanged. Therefore, semiotic processes appear as a characteristic of the whole (organism), but also as one among organisms (same or different).
Success and failure depend decisively more upon interpretation than upon the amount of data. An infinite amount of data cannot compensate for an error in interpretation. Machines are, by many orders of magnitude, better in processing information, but not really better than humans in interpreting it. They can handle way more data than the people who build them; but quantity does not automatically lead to improved comprehension. In a changing context, interpretation becomes consubstantial with dynamics. Machines do not change; humans (the living) change.
No information process (e.g., computer, sensor-based information harvesting, intelligent agents-based activities) is possible without representation. Representation is the definitory subject of semiotics. While electrons move through circuits, and while logic is emulated in hardware (circuits performing logical operations), operations on representations are the prerequisite for any information processing.
Brain imaging revealed that taxi drivers in some of the big cities (London was the first address researched), difficult to navigate, developed in the process measurable new faculties Indeed, the plasticity of the brains of those who navigate under the influence of GPS data changes (not always for the better). Of course, these changes are semiotic in nature: Understanding of representations and the ability to match goals and means (a request such as “Get me to Piccadilly in the shortest time,” involves quite a number of parameters) are semiotic processes. The emergence of GPS-based navigation might lead to the loss of some faculties. Semioticians should be aware of the fact that the world before maps and the world after maps became available are very different realities.
Indian Buddhism and Brahman-ism, the Christian infatuation with signs (St. Augustine’s De Doctrina Cristiana, 397 CE, and St. Anselm’s Monologion, 1075-1076; see Hopkins, 1986), and Avicenna’s explorations in medicine and theology remain documentary repositories of the many questions posed by two very simple questions: How can something in the world be “duplicated” in the mind? Take note: the question is not about signs, but about re-presentation.
Edward O. Wilson (1984) came up with a provocative statement of significance to semiotics: “Scientists do not discover in order to know, they know in order to discover.”
22. TAROT CARD READING IS NOT (YET) AN ACADEMIC DISCIPLINE. But it might become one. [...] Semiotics became the stage for literary critics, art historians, confused structuralists, and even for some linguists, mathematicians, and sociologists. Some philosophers also ventured on the stage. Before too late, we had the semiotics of feminism, multiculturalism, human rights, sexuality, food, and even the semiotics of wine; we had gay and lesbian semiotics, environmental semiotics, and even global warming or sustainability semiotics. But no semiotics!
23. THERE IS MORE TO INTERACTION THAN LANGUAGE
Preoccupation with what is called natural language affected the focus on the sign. It informed the reading of past attempts in semiotics in such a manner that what actually lies behind the sign is cast aside, never really recognized. All this rendered the notion of sign captive to an ideology that dominated semiotics from its beginnings. Simply stated, this ideology is logocratic. That is, it ascertains that every sign can be reduced to a language sign; moreover, that any interaction is language dependent.
If, finally, semiotics could in our days free itself from the obsession with sign-based language as object of its inquiry, it could help debunk quite a number of dogmatic positions.
The broad agreement that knowledge is expressed more and more in computational form could translate into a well-defined goal: express semiotic knowledge computationally. As such, the goal deserves attention because even though deterministic machines are inadequate for capturing nondeterministic processes, we can work towards conceiving new forms of processing that either mimic the living or even integrate the living (hybrid computation).
Computational semiotics (making reference to Dmitri Pospelov and Eugene Pendergraft, to James Albus, to “language games” behind which Wittgenstein is suspected, to Luis Rocha and Cliff Joslyn, and even to Leonid Perlovsky and his intelligent target tracker) is more than looking for justification for AI research, or for some computer-based terminology associated with signs. It would be encouraging to engage those interested in foundational aspects of semiotics in a computational effort. One possible result could be a semiotic engine conceived as a procedure for generating representations and for supporting interpretation processes. [...]However, if machine-generated representations were to trigger the claim of replacing the living processes leading to comprehensive dynamic representations of a changing world, we would face a real danger. In representing something, the living simultaneously re-presents itself. This contributes to the knowledge the outlook and the sense of future derived through human representations. Each representation, after all, embodies anticipation. Machines, regardless of their level of sophistication, do not anticipate.
24. IS THERE A SEMIOTIC METHOD? [...] This is an opportunity, as good as any, to spell out the alternative to the semiotics focused on the sign. I suggest that, instead of the atomistic view of a sign obsessed with semiotics, we adopt a dynamic view, of events succeeding in time. The notion that each event—such as perceiving an image, hear-ing a sound, experiencing a texture, etc.—is “made up” of signs is less important than the determination to integrate successive experi-ences. Narration is a historic record: event1, event2, event3. .
In this view, the series is made up of suc-ceeding signs. While each event is relevant, the focus is on the integrated series, more precisely, on its meaning. But more on a narration-based semiotics in the concluding part of this study.
27. NARRATION AND STORY: The most intuitive description of the narra-tive is the following: the record of a sequence of events as they succeed in time. The word (from the Latin narrare) means to recount. It suggests that a record of succeeding events in time, a time series, describes what individuals or groups accomplish and how. Therefore, each narrative adds up to knowledge, at least in the sense of documenting successful and less successful activities.
With the exception of Windelband (1915), almost no one has tried to define the distinction between narrative knowledge, corresponding to a historic record of change (idiographic), and scientific knowledge (nomothetic), cor-responding to our attempts to describe how reality works. The idiographic captures patterns of events; the nomothetic focuses on scientific law. Of course, those who accept the religion of determinism would like to transform the uniqueness of experience captured in the narration into laws, thus opening the avenue towards automating whatever we do.
Thesis 1: Narration is a record of change. Thesis 2: Story is an open-ended process of interpreting narration. Thesis 3: Narrations are representations of change. Thesis 4: Stories are interpretations of the narration of change. Thesis 5: The clock of narration and the clock of interpretation are different.
Premise: Complement the cause-and-effect description of physical reality by a description characteristic of living systems. In living systems, the current state is determined not only by past and present, but also by their possible future states. Scientists are discovering more and more the significance of anticipatory characteristics (from the molecular level to the level of complex systems). As scientists try to endow matter and various mechanisms with intelligence, anticipation becomes more important, involving new forms of computation. Anticipation can be seen as a "second Cartesian revolution." (via http://anteinstitute.org)
Why is it a subject of research? Anticipation occurs in all spheres of life. It complements the physics of reaction with the pro-active quality of the living. Nature evolves in a continuous anticipatory fashion targeted at survival. The dynamics of stem cells demonstrate this mechanism. Through entailment from a basic stem cell an infinite variety of biological expression becomes possible.
Sometimes we humans are aware of anticipation, as when we plan. Often, we are not aware of it, as when processes embedded in our body and mind take place before we realize their finality. In tennis, for example, the return of a professional serve can be successful only through anticipatory mechanisms. A conscious reaction takes too long to process. Anticipation is the engine driving the stock market. Creativity in art and design are fired by anticipation. “The end is where we start from,” T. S. Eliot once wrote. Before the archer draws his bow, his mind has already hit the target. Motivation mechanisms in learning, the arts, and all types of research are dominated by the underlying principle that a future state—the result—controls present action, aimed at success. The entire subject of prevention entails anticipatory mechanisms. (via http://anticipation.info)
Exploring Abductive Reasoning - The Logic of Maybe
Abductive reasoning is a form of logical inference which starts with an observation or set of observations then seeks to find the simplest and most likely explanation for the observations. This process, unlike deductive reasoning, yields a plausible conclusion but does not positively verify it. Abductive conclusions are thus qualified as having a remnant of uncertainty or doubt, which is expressed in retreat terms such as "best available" or 'most likely.
Put differently, Abduction is drawing a conclusion using a heuristic that is likely, but not inevitable given some foreknowledge.e.g., I observe sheep in a field, and they appear white from my viewing angle, so sheep are white. Contrast with the deductive statement: "Some sheep are white on at least one side". To simplify and summaries: Deductive = Top down logic - Inductive = Bottom up logic - Abductive = What seems most probably?
The American philosopher Charles Sanders Peirce (1839–1914) introduced abduction into modern logic. Over the years he called such inference hypothesis, abduction, presumption, and retroduction. He considered it a topic in logic as a normative field in philosophy, not in purely formal or mathematical logic, and eventually as a topic also in economics of research. (wikipedia)
In later years his view came to be:
Abduction is guessing. It is "very little hampered" by rules of logic. Even a well-prepared mind's individual guesses are more frequently wrong than right. But the success of our guesses far exceeds that of random luck and seems born of attunement to nature by instinct (some speak of intuition in such contexts).
Abduction guesses a new or outside idea so as to account in a plausible, instinctive, economical way for a surprising or very complicated phenomenon. That is its proximate aim.
Its longer aim is to economize inquiry itself. Its rationale is inductive: it works often enough, is the only source of new ideas, and has no substitute in expediting the discovery of new truths.
Pragmatism is the logic of abduction. Upon the generation of an explanation, the pragmatic maxim gives the necessary and sufficient logical rule to abduction in general. The hypothesis, being insecure, needs to have conceivable implications for informed practice, so as to be testable and, through its trials, to expedite and economize inquiry. The economy of research is what calls for abduction and governs its art.
"The interest in the use of abductive, analogic and intuitive problem-solving has major roots in the “design studies” movement of the late 1960’s & 1970’s.
This movement started in the UK, primarily thanks to the work of Leslie Martin and Lionel March at the Cambridge Centre at the Cambridge School of Architecture.March and Martin were at the head of a generation of scholars seeking to systematise and understand how architects and designers thought about the world. This paralleled research into cybernetics & AI in the states by Herbert Simon, but for some reason it seems that there was a critical confluence of design thinkers in the UK at that time, and most of the literature around induction, abduction, etc. seems to come from this period.
The key ideas: The original intention of this group was to understand and document the design process. The hope was that if you understood how architects and designers perceived the world, you could replicate this in computer or expert-systems (and then do away with or “improve” the designer). Because replicability was one of the key goals, a natural sciences approach was taken to observing designers. A lot of controlled experiments were set up in laboratories to test “design problem solving”, most of which failed miserably. This led to a more ethnographic approach, including some of the first anthropological approaches to knowledge elicitation that I’ve ever seen.
What they found was that:
“Scientists adopt a problem-focused strategy and architects a solution-focused strategy.” (Lawson, 1979)
“The scientific method is a pattern of problem-solving behaviour employed in finding out the nature of what existis, whereas the design method is a pattern of behaviour employed in inventing things of value which do not yet exists. Science is analytic, design is constructive.” (Gregory, 1966)
This places a heavy emphasis on action, testing, and observation, in that order, and highlights the essentially creative nature of design. Nigel Cross, who is still teaching at the Open University, suggests that design is “a process of pattern-synthesis, when the solution is not simply ‘lying there in the data’ but has to be actively constructed by the designer’s own efforts.”. You can see how this relates to the notion of abduction. Peirce suggests that, “the whole fabric of our knowledge is one matted felt of pure hypothesis confirmed and refined by induction.” This is very similar to design. In other words,
“[Architects] learn about the nature of the problem largely as a result of trying out solutions, whereas the scientists set out specifically to study the problem.” (Lawson, 1980)
Schum notes that if Peirce is correct, “new ideas emerge as we combine, marshal or organize thoughts and evidence in different ways.” Because the design method is fundamentally exploratory, it is about hypothesis generation based on the most uncertain and sketchy forms of data. It uses both abductive and constructive reasoning to show “what might be”, instead of deductive reasoning to show “what is”." Read more..
In recent decades, Abductive Logic and Reasoning has been extensively studied in the context of Artificial Intelligence and Machine Learning research. A few links, old & new:
Related Ideas by Abductive Logic pioneer Charles Sanders Peirce, on Semiotics:
"The essence of belief is the establishment of a habit; and different beliefs are distinguished by the different modes of action to which they give rise." - Charles Sanders Peirce
BASED ON TRUE EVENTS: "I have been teaching Geometry this year,and trying my best to explain logic,deduction vs induction, and the ever present, always faulty, always useful, abductive “reasoning.”Without abductive reasoning, life itself would not be possible for humans. Induction and deduction? Entirely optional. Our car, (which only had 3 out 4 cyliders working) started to turn itself off, at apparently random intervals. There you’d be, changing lanes, in what you thought was a car,and poof no car, just a large metal box that looked like a car,with a seat belt, a driver’s seat, and a silent engine,rolling to a final velocity of zero. I drove the box / car to five dealerships in town,while searching for the best replacement for the box.I can now say, what others have noted before;
“Pure logic, when considering a car, (or any thing else other than numbers) does not exist.”
Notes on the Historical Division between "Logical thinking" and "Visuals"
Rudolf Arnheim suggested a historical division between "Logical thinking" and "Visuals" in his ground-breaking book, Visual Thinking (1969).
He pointed out that philosophers in ancient Greek credited the direct vision as the start and end source of wisdom although they also learned possible distortion in human’s visual perception (Arnheim, 1969. pp. 12). However, hundreds of years later, the potential of using sketching in creative problem solving are still paid less attention. Sketching is often not considered as a form of thinking. (found via viz-up-the-world)
In his book, Arnheim (1969. pp. 2-3) reflected on the issue as the followed:
“Today, the prejudicial discrimination between perception and thinking is still with us. We shall find it in examples from philosophy and psychology. Our entire educational system continues to be based on the study of words and numbers … More and more the arts are considered as a training in agreeable skills, as entertainment and mental release."
"As the ruling disciplines stress more rigorously the study of words and numbers, their kinship with the arts is increasingly obscured, and the arts are reduced to a desirable supplement…. The arts are neglected because they are based on perception, and perception is disdained because it is not assumed to involve thought. In fact, educators and administrators cannot justify giving the arts an important position in the curriculum unless they understand that the arts are the most powerful means of strengthening the perceptual component without which productive thinking is impossible in any field of endeavor. The neglect of the arts is only the most tangible symptom of the widespread unemployment of the senses….”
"All perceiving is also thinking, all reasoning is also intuition, all observation is also invention." - Rudolf Arnheim
"My teachers Max Wertheimer and Wolfgang Köhler were laying the theoretical and practical foundations of gestalt theory at the Psychological Institute of the Uni of Berlin, and I found myself fastening on to what may be called a Kantian turn of the new doctrine, according to which even the most elementary processes of vision do not produce mechanical recordings of the outer world but organize the sensory raw material according to principles of simplicity, regularity, and balance, which govern the receptor mechanism. This discovery of the gestalt school fitted the notion that the work of art, too, is not simply an imitation or selective duplication of reality but a translation of observed characteristics into the forms of a given medium" (from Film as Art)
"We have been trained to think of perception as the recording of shapes, distances, hues, motions. The awareness of these measurable characteristics is really a fairly late accomplishment of the human mind. Even in the Western man of the twentieth century it presupposes special conditions. It is the attitude of the scientist and the engineer or of the salesman who estimates the size of a customer’s waist, the shade of a lipstick, the weight of a suitcase. But if I sit in front of a fireplace and watch the flames, I do not normally register certain shades of red, various degrees of brightness, geometrically defined shapes moving at such and such a speed. I see the graceful play of aggressive tongues, flexible striving, lively color. The face of a person is more readily perceived and remembered as being alert, tense, concentrated rather than being triangularly shaped, having slanted eyebrows, straight lips, and so on" (from Art and Visual Perception, first ed., 430).
"Without the flourishing of visual expression no culture can function productively" - Rudolf Arnheim
The average players are working just as many hours as the elite players (around 50 hours a week spent on music),
but they’re not dedicating these hours to the right type of work (spending almost 3 times less hours than the elites on crucial deliberate practice),
and furthermore, they spread this work haphazardly throughout the day. So even though they’re not doing more work than the elite players, they end up sleeping less and feeling more stressed. Not to mention that they remain worse at the violin.
#Comment: A far more interesting question is if angels and disembodied spirits can own the content they create. Generative copyright is peak late capitalist madness at its finest - the works of greedy petty lost souls. I spoke previously about related topics here & here.
"Good taste is the most obvious resource of the insecure. People of good taste eagerly buy the Emperor's old clothes. Good taste is the first refuge of the non-creative. It is the last-ditch stand of the artist. Good taste is the anaesthetic of the public." - Harley Parker
"The old categories of composer, performer and audience are oversimplifications. There can be an infinite number of gradations between and combinations of them". - Laurie Spiegel