youtube 1978 Bernard Williams and AJ Ayer on Wittgenstein, Truth, and Religion
>knowledge, philosophy, religion, science
bigthink.com 19-1-2023 Science won’t ever make philosophy or religion obsolete – The information we have in the Universe is finite and limited, but our curiosity and wonder is forever insatiable. And always will be. by Ethan Siegel
- As we come to understand the Universe to better precision and more comprehensively, many questions which were previously pondered by philosophical and religious thought-leaders grow to have definitive answers.
- However, the information we possess within our observable Universe is now, and will always be, finite and limited, implying that there’s a fundamental limit to what’s knowable.
- As long as we remain curious about the unknown and the unknowable, there will always be a place for philosophy and religion both, independently of whatever becomes scientifically known. Here’s why.
>brain, cognition, epistemology, knowledge,logic, mind, reason, time
newscientist.com 10 -1- 2023 Logic underpins knowledge – but what if logic itself is flawed? – We use logic to build facts into systems of thought, but paradoxes force us to question what we think we know. And it could be worse, because logic may not be sufficient to comprehend reality – by Abigail Beall
I AM not bald. At least, not as I write this. Yet if a malevolent philosopher were to pluck the hairs out of my head, one by one, I would end up bald. But how many would have to be removed before I went from having a lustrous head of hair to being bald? It is tricky, if not impossible, to say. And if we can’t identify the transition to baldness, am I actually bald at all?
This is a version of a thought experiment favoured by philosophers, first described with reference to grains of sand in a heap, called the sorites paradox (from the Greek word for “heap”). It is often used as evidence that classical logic might be insufficient to describe the world around us.
That is troubling because, though we don’t pay it much attention, logic runs through human knowledge as if it were a stick of rock. We assume that we can build up a sequence of facts into systems of thought. But if logic itself is lacking, where does that leave us? …
read whole article at newscientist – part of a special series on the limits of knowledge
>social science practice, publishing
economist.com 7-1-2023 Papers and patents are becoming less disruptive – Why that is, is a mystery
> science practice, genetics, ethics
>social science practice, economics, statistical artefact, autocorrelation, cognitive bias
economicsfromthetopdown 2022 The Dunning-Kruger Effect is Autocorrelation – by Blair Fix
“Have you heard of the ‘Dunning-Kruger effect’? It’s the (apparent) tendency for unskilled people to overestimate their competence. Discovered in 1999 by psychologists Justin Kruger and David Dunning, the effect has since become famous. And you can see why. It’s the kind of idea that is too juicy to not be true. Everyone ‘knows’ that idiots tend to be unaware of their own idiocy. Or as John Cleese puts it: If you’re very very stupid, how can you possibly realize that you’re very very stupid? …”…
ft.com 31-12-2022 On cognitive bias, overconfidence and uncertainty by Ravi Gurumurthy
>real existing, paradigm, conceptual cohorts, silos
theguardian.com 28-6-2022 Do we need a new theory of evolution? – A new wave of scientists argues that mainstream evolutionary theory needs an urgent overhaul. Their opponents have dismissed them as misguided careerists – and the conflict may determine the future of biology – by Stephen Buranyi
…”….While information piled up at a rate that no scientist could fully digest, the steady thrum of the modern synthesis ran through it all. The theory dictated that, ultimately, genes built everything, and natural selection scrutinised every bit of life for advantage. Whether you were looking at algae blooming in a pond or peacock mating rituals, it could all be understood as natural selection doing its work on genes. The world of life could seem suddenly simple again.
By 1959, when the University of Chicago held a conference celebrating the centennial of the publication of On the Origin of Species, the modern synthesists were triumphant. The venues were packed and national newspaper reporters followed the proceedings. (Queen Elizabeth was invited, but sent her apologies.) Huxley crowed that “this is one of the first public occasions on which it has been frankly faced that all aspects of reality are subject to evolution”. Yet soon enough, the modern synthesis would come under assault from scientists within the very departments that the theory had helped build. …”…
aeon.co/ 2022 Quantum Wittgenstein – Metaphysical debates in quantum physics don’t get at ‘truth’ – they’re nothing but a form of ritual, activity and culture
…”…As a scientist and mathematician, Wittgenstein has challenged my own tendency to seek out interpretations of phenomena that have no scientific value – and to see such explanations as nothing more than narratives. He taught that all that philosophy can do is remind us of what is evidently true. It’s evidently true that the wavefunction has a multiverse interpretation, but one must assume the multiverse first, since it cannot be measured. So the interpretation is a tautology, not a discovery.
I have humbled myself to the fact that we can’t justify clinging to one interpretation of reality over another. In place of my early enthusiastic Platonism, I have come to think of the world not as one filled with sharply defined truths, but rather as a place containing myriad possibilities – each of which, like the possibilities within the wavefunction itself, can be simultaneously true. Likewise, mathematics and its surrounding language don’t represent reality so much as serve as a trusty tool for helping people to navigate the world. They are of human origin and for human purposes.
To shut up and calculate, then, recognises that there are limits to our pathways for understanding. Our only option as scientists is to look, predict and test. This might not be as glamorous an offering as the interpretations we can construct in our minds, but it is the royal road to real knowledge.
>consensus theory of truth, H Ahrendt, J Habermas, JA Schumpeter, communicative competence
journals.sagepub.com / 2020 Truth, lies and tweets: A Consensus Theory of Post-Truth – by Vittorio Bufacchi
Abstract – This article rejects the received view that Post-Truth is a new, unprecedented political phenomenon. By showing that Truth and Post-Truth share the same genesis, this article will submit the idea of a Consensus Theory of Post-Truth. Part 1 looks at the difference between Post-Truth, lies and bullshit. Part 2 suggests reasons behind the current preoccupation with Post-Truth. Part 3 focuses on Habermas’s influential consensus theory of truth to suggest that truth and Post-Truth have more in common than is generally assumed. Part 4 puts forward the Consensus Theory of Post-Truth. Part 5 suggests three ways to emasculate the potentially destructive effect of Post-Truth on democratic society.
…”…Post-Truth’s reliance on consensus is not as radical as it may seem. The idea that consensus can be manufactured has a long history. In Capitalism, Socialism and Democracy, JA Schumpeter offers an analysis of this phenomenon that is as true today as it was in the 1940s when he was writing. Starting from the assumption that the democratic method boils down to a competitive struggle for the people’s vote, and political parties operate in the context of the competitive struggle for political power, Schumpeter (2003 , 263) argues that in politics consent is always manufactured, never authentic: ‘Human Nature in Politics being what it is, they [professional politicians] are able to fashion and, within very wide limits, even to create the will of the people. What we are confronted with in the analysis of political processes is largely not a genuine but a manufactured will…The way in which issues and the popular will on any issue are being manufactured is exactly analogous to the way of commercial advertising’.
Schumpeter’s view on consensus, which could be described as either bleak or realist, resonates with Hannah Arendt’s warning that it is the nature of the political realm to be at war with truth, in all its forms. That is because, as Arendt (2000 , 555) says: ‘truth carries within itself an element of coercion’. This is a powerful statement, worth reflecting on. What Arendt (2000 , 555–56) is telling us here is that anyone in power will do everything to resist truth: ‘Seen from the viewpoint of politics, truth has a despotic character. It is therefore hated by tyrants, who rightly fear the competition of a coercive force they cannot monopolize, and it enjoys a rather precarious status in the eyes of governments that rest on consent and abhor coercion’. …
… There are two ways of cutting the umbilical cord of consensus that ties theories of truth and Post-Truth. The first is to give up on consensus and revert back to a correspondence theory of truth. The logic behind this move is to make truth a much stronger notion, grounded on objective criteria that cannot be refuted. This solution is attractive, in part because of the ontological difference between a fact and an opinion, as Hannah Arendt (2000 , 556) rightly reminds us: ‘facts are beyond agreement and consent, and all talk about them…will contribute nothing to their establishment. Unwelcome opinion can be argued with, rejected, or compromised upon, but unwelcome facts possess an infuriating stubbornness that nothing can move except plain lies’. Although Arendt is right, corresponding facts to truth is marred with pitfalls, since the notions of ‘correspondence’ and ‘facts’ can pose serious problems for the Correspondence Theory of Truth,23 which is precisely why Habermas was keen to find an alternative to the correspondence approach when he embarked on the project of validating truth on the basis of a (hypothetical, ideal, rational) consensus.
An alternative approach is to rethink the way we use the concept of truth. We should certainly not give up on the concept of ‘truth’, at least for two reasons. First of all because it would go against our human nature; as Marcus Tullius Cicero (2000, 7) said more than 2000 years ago in his De Officiis, ‘Especially unique to man is the search and scrutiny into truth’. Secondly, because giving up on truth would be to accept defeat to the champions of Post-truth. Yet we must also recognize the fact that the concept of truth is often abused, inappropriately utilized, being called upon in contexts where truth is not the issue. We must refrain from appealing to ‘truth’ where it is not necessary. Truth is a concept that we increasingly apply to many other contexts apart from science and history, which raises the question of whether ‘truth’ is the correct term to use. While in the context of scientific and historical discourse it is right to stand up for truth and oppose Post-Truth, in politics and ethics to think in terms of this binary dichotomy isn’t helpful. Truth needs to be deflated, and deflating truth will also deflate Post-Truth.
Deflationism stands for the general propensity to reverse the tendency whereby a concept becomes over-inflated, in the sense that it is required to do more than it can reasonably be expected. …
Conclusion -This article wants to accomplish three things. First, it suggests that for the sake of conceptual clarity, the idea of Post-Truth must be distinguished from two other concepts: the mere lie, and bullshit. Secondly, we need to ask ourselves why Post-Truth has become such a big issue: why today? My answer to this question is that Post-Truth is not a new phenomenon, but has a long history. Third, this article defends the view that sees both truth and Post-Truth sharing the same genesis, seeking validation in consensus. Furthermore, it also argues that Post-Truth is characterized by a fundamental paradox: it appeals to consensus (for Post-truth) as a way of undermining another consensus (for truth). Fourthly, there are institutional, moral and philosophical ways of opposing Post-Truth. In particular, an argument is made that it is not helpful to think of truth and Post-Truth in terms of a binary opposition. There is an alternative, which is to deflate truth. The best way to disarm Post-Truth is not to talk about truth unless it is absolutely necessary, and appropriate. Post-Truth is, in part, a consequence of the growing tendency to appeal to truth when, in fact, truth is not the issue.
While Post-Truth poses a serious threat to liberal democracies throughout the world, we ought to take strength from the fact that truth is not easily defeated, and any perceived gains by the priests of Post-Truth are merely temporary. It is perhaps only fitting to give Hannah Arendt (2000 , 570) the last word on this theme: ‘Truth, though powerless and always defeated in a head-on clash with the powers that be, possesses a strength of its own: whatever those in power may contrive, they are unable to discover or invent a viable substitute for it. Persuasion and violence can destroy truth, but they cannot replace it’. ” read pdf here
livescience.com 1-2022 What is a scientific theory? – A scientific theory is based on careful examination of facts. by By Alina Bradford , Ashley Hamer
>knowledge epistemology science idealism realism objectivity
bigthink.com/3-2022 Realism in science needs to be more real – Realism in science cannot be completely unmoored from human experience. Otherwise, realism ends up tortured with unreal paradoxes. by Adam Frank
- Science has a lot to say about the nature of reality.
- However, the problem with realism in science is that it has come to favor abstractions over everyday experience.
- Science is objective because it allows us to create maps that we can test together by comparing them with the results of experiments. This is real realism.
…”From this point of view, science is not objective because it points to some ideal God’s-Eye-View fairyland. Instead, science is objective because it allows us to create maps that we can test together by comparing them with the results of experiments…”…
reusable block > big data, AI, non theory science PHIL O SCIENCE
theguardian.com 9/1/2022 Are we witnessing the dawn of post-theory science? Does the advent of machine learning mean the classic methodology of hypothesise, predict and test has had its day? by Laura Spinney
In 2008, Chris Anderson, the then editor-in-chief of Wired magazine, predicted its demise. So much data had accumulated, he argued, and computers were already so much better than us at finding relationships within it, that our theories were being exposed for what they were – oversimplifications of reality. Soon, the old scientific method – hypothesise, predict, test – would be relegated to the dustbin of history. We’d stop looking for the causes of things and be satisfied with correlations. With the benefit of hindsight, we can say that what Anderson saw is true (he wasn’t alone). The complexity that this wealth of data has revealed to us cannot be captured by theory as traditionally understood. “We have leapfrogged over our ability to even write the theories that are going to be useful for description,” says computational neuroscientist Peter Dayan, director of the Max Planck Institute for Biological Cybernetics in Tübingen, Germany. “We don’t even know what they would look like.”
But Anderson’s prediction of the end of theory looks to have been premature – or maybe his thesis was itself an oversimplification. There are several reasons why theory refuses to die, despite the successes of such theory-free prediction engines as Facebook and AlphaFold. All are illuminating, because they force us to ask: what’s the best way to acquire knowledge and where does science go from here?
The first reason is that we’ve realised that artificial intelligences (AIs), particularly a form of machine learning called neural networks, which learn from data without having to be fed explicit instructions, are themselves fallible. Think of the prejudice that has been documented in Google’s search engines and Amazon’s hiring tools.The second is that humans turn out to be deeply uncomfortable with theory-free science. We don’t like dealing with a black box – we want to know why.
And third, there may still be plenty of theory of the traditional kind – that is, graspable by humans – that usefully explains much but has yet to be uncovered.
So theory isn’t dead, yet, but it is changing – perhaps beyond recognition. “The theories that make sense when you have huge amounts of data look quite different from those that make sense when you have small amounts,” says Tom Griffiths, a psychologist at Princeton University.
Griffiths has been using neural nets to help him improve on existing theories in his domain, which is human decision-making. A popular theory of how people make decisions when economic risk is involved is prospect theory, which was formulated by behavioural economists Daniel Kahneman and Amos Tversky in the 1970s (it later won Kahneman a Nobel prize). The idea at its core is that people are sometimes, but not always, rational.
n Science last June, Griffiths’s group described how they trained a neural net on a vast dataset of decisions people took in 10,000 risky choice scenarios, then compared how accurately it predicted further decisions with respect to prospect theory. They found that prospect theory did pretty well, but the neural net showed its worth in highlighting where the theory broke down, that is, where its predictions failed.
These counter-examples were highly informative, Griffiths says, because they revealed more of the complexity that exists in real life. For example, humans are constantly weighing up probabilities based on incoming information, as prospect theory describes. But when there are too many competing probabilities for the brain to compute, they might switch to a different strategy – being guided by a rule of thumb, say – and a stockbroker’s rule of thumb might not be the same as that of a teenage bitcoin trader, since it is drawn from different experiences.
“We’re basically using the machine learning system to identify those cases where we’re seeing something that’s inconsistent with our theory,” Griffiths says. The bigger the dataset, the more inconsistencies the AI learns. The end result is not a theory in the traditional sense of a precise claim about how people make decisions, but a set of claims that is subject to certain constraints. A way to picture it might be as a branching tree of “if… then”-type rules, which is difficult to describe mathematically, let alone in words.
The final objection to post-theory science is that there is likely to be useful old-style theory – that is, generalisations extracted from discrete examples – that remains to be discovered and only humans can do that because it requires intuition. In other words, it requires a kind of instinctive homing in on those properties of the examples that are relevant to the general rule. One reason we consider Newton brilliant is that in order to come up with his second law he had to ignore some data. He had to imagine, for example, that things were falling in a vacuum, free of the interfering effects of air resistance.
In Nature last month, mathematician Christian Stump, of Ruhr University Bochum in Germany, called this intuitive step “the core of the creative process”. But the reason he was writing about it was to say that for the first time, an AI had pulled it off. DeepMind had built a machine-learning program that had prompted mathematicians towards new insights – new generalisations – in the mathematics of knots.
In 2022, therefore, there is almost no stage of the scientific process where AI hasn’t left its footprint. And the more we draw it into our quest for knowledge, the more it changes that quest. We’ll have to learn to live with that, but we can reassure ourselves about one thing: we’re still asking the questions. As Pablo Picasso put it in the 1960s, “computers are useless. They can only give you answers.”
cantorsparadise.com 2021 Wolfgang Pauli’s *Philosophical* Position on Quantum Mechanics and Angels – Paul Austin Murphy
“[O]ne should no more rack one’s brain about the problem of whether something one cannot know anything about exists all the same, than about the ancient question of how many angels are able to sit on the point of a needle. But it seems to me that Einstein’s questions are ultimately always of this kind.”
Despite the bluntness and irony of that passage, it can still be argued that Pauli had a philosophical position on the reality that some scientists, philosophers and laypeople believe (as it were) hides behind our observations, experiments, tests, etc. So Pauli’s position can itself be interpreted as a philosophical position. In other words, Pauli wasn’t just offering a philistine scream of “shut up and calculate!”. (This is somewhat parallel to, for example, eliminative materialists and ontic structural realists whom are often deemed to offer “anti-philosophical” and “scientistic” positions while at the very same time being philosophers themselves.)
More specifically, Pauli rejected the opposition between reality itself (or “ultimate reality”) and what we can can know about reality (as did Niels Bohr). In other words, knowing “how Nature is” amounts to no more than a metaphysician’s dream. All we actually have is “what we can say about Nature”. And, at the quantum-mechanical level, what we can say is what we can say with the mathematics — in conjunction with experiments, tests, predictions, observations, etc. Consequently, just about everything else is analogical and/or imagistic in nature. Indeed the analogical/imagistic stuff can — and often does — mislead us.
Of course it can be asked whether or not Pauli was really talking about something that “one cannot know anything about” — or just being very impatient. (It must be noted that Pauli wrote these words in 1954 — long after the “quantum revolution” of the 1920s and 1930s.) Similarly, how did Pauli himself know that we could never know these things?..”…
goodreads.com 2001 Human Nature and the Limits of Science – by John A. Dupre
“John Dupré warns that our understanding of human nature is being distorted by two faulty and harmful forms of pseudo-scientific thinking. Not just in the academic world but increasingly in everyday life, we find one set of experts seeking to explain the ends at which humans aim in terms of evolutionary theory, and another set of experts using economic models to give rules of how we act to achieve those ends. Dupré charges this unholy alliance of evolutionary psychologists and rational-choice theorists with scientific imperialism: they use methods and ideas developed for one domain of inquiry in others where they are inappropriate. He demonstrates that these theorists’ explanations do not work, and furthermore that if taken seriously their theories tend to have dangerous social and political consequences. For these reasons, it is important to resist scientism – an exaggerated conception of what science can be expected to do for us. To say this is in no way to be against science – just against bad science. Dupré restores sanity to the study of human nature by pointing the way to a proper understanding of humans in the societies that are our natural and necessary environments. He shows how our distinctively human capacities are shaped by the social contexts in which we are embedded. And he concludes with a bold challenge to one of the intellectual touchstones of modern science: the idea of the universe as causally complete and deterministic. In an impressive rehabilitation of the idea of free human agency, he argues that far from being helpless cogs in a mechanistic universe, humans are rare concentrations of causal power in a largely indeterministic world. Human Nature and the Limits of Science is a provocative, witty, and persuasive corrective to scientism. In its place, Dupré commends a pluralistic approach to science, as the appropriate way to investigate a universe that is not unified in form. Anyone interested in science and human nature will enjoy this book, unless they are its targets.”
economicsfromthetopdown.com 2/7/2021 Essentialism and Traditionalism in Academic Research – CasP – R Kyger, Blair Fix
Civilization and the culture of science: Science and the shaping of modernity, 1795–1935, by Stephen Gaukroger. Reviewed by Gabriel Finkelstein
Anti-scientism, technoscience and philosophy of technology: Wittgenstein and Lyotard by Michael A. Peters 2019
“The truly apocalyptic view of the world is that things do not repeat themselves. It isn’t absurd, e.g., to believe that the age of science and technology is the beginning of the end for humanity; that the idea of great progress is a delusion, along with the idea that the truth will ultimately be known; that there is nothing good or desirable about scientific knowledge and that mankind, in seeking it, is falling into a trap. It is by no means obvious that this is not how things are.”
–Ludwig Wittgenstein (1969), Culture and Value, p. 56e
Jean-Francois Lyotard understood Wittgenstein’s anti-scientism in the context of the Austrian counter-enlightenment tradition which was deeply suspicious of the grand claim that the scientific method is superior to all other means of learning or gaining knowledge. Wittgenstein’s negative cultural outlook was conditioned by Spengler’s (1926) The Decline of the West and a deep pessimism about what science could achieve and what it could not. It could not, for instance, give us moral direction or deal with ethics. Beale and Kidd (2017) suggest that Wittgenstein’s anti-scientism ‘sheds light upon and reveals connections between some of the central areas of his thinking’ (p. 5). Wittgenstein held a negative attitude about the role of science in modern civilization and its overwhelming confidence that it can resolve all problems and that it is only a matter of time before it extends its frontiers to encompass the whole of life. Wittgenstein’s anti-scientism that characterizes his view of modern civilization is the cultural outlook that connects with the broader issues of naturalism and empiricism. As Anna Boncompagni (2018) points out in a review of Beale and Kidd, scientism for Wittgenstein also carries the corollaries:
…science has the right, if not the duty, to extend its dominion into any territory; the scientific method is ‘the’ method of inquiry par excellence; other disciplines, if they are to attain knowledge at all, ought to conform to the scientific method; any domain of human experience can and should be reduced to the natural, empirical domain of science, https://ndpr.nd.edu/news/wittgenstein-and-scientism/
Wittgenstein’s anti-scientism conditions those that embrace his work in philosophy of science. While completing a philosophy of science degree in the 1970s at the University of Canterbury I became interested in the Wittgenstein-inspired philosophers of science, in particular, Stephen Toulmin (1958, 1972), Paul Feyerabend (1975), Russell Norwood Hanson (1958) and Thomas Kuhn (1962). Toulmin was a student of Wittgenstein’s (and the physicist Dirac) and had embraced his skepticism of science and anti-rationalism. Toulmin’s Wittgenstein’s Vienna (Janik & Toulmin, 1973), coauthored with Allan Janik, was a strategic text for me that changed forever my view of Wittgenstein as a placeholder in Cambridge philosophy and the analytic tradition.
Feyerabend published several papers on Wittgenstein discussing The Philosophical Investigations (1953). Elizabeth Anscombe had provided Feyerabend with manuscripts of Wittgenstein’s later work which Feyerabend said ‘exercised a profound influence’ upon him. John Preston (2016) notes:
Feyerabend planned to study with Wittgenstein in Cambridge, and Wittgenstein was prepared to take him on as a student, but he died before Feyerabend arrived in England. Karl Popper became his supervisor instead…
Feyerabend became a strong critic of Popper’s critical rationalism and of any rationalist attempt to lay down rules for scientific method. Feyerabend’s (1975) Against Method proposed that science was based on ‘epistemological anarchism’ (‘anything goes’) which was historically more successful and creative than a rule-based system. As Feyerabend argues:
The idea that science can, and should, be run according to fixed and universal rules, is both unrealistic and pernicious. It is unrealistic, for it takes too simple a view of the talents of man and of the circumstances which encourage, or cause, their development. And it is pernicious, for the attempt to enforce the rules is bound to increase our professional qualifications at the expense of our humanity. In addition, the idea is detrimental to science, for it neglects the complex physical and historical conditions which influence scientific change … Naive falsificationism takes it for granted that the laws of nature are manifest and not hidden beneath disturbances of considerable magnitude. Empiricism takes it for granted that sense experience is a better mirror of the world than pure thought. Praise of argument takes it for granted that the artifices of Reason give better results than the unchecked play of our emotions. Such assumptions may be perfectly plausible and even true. Still, one should occasionally put them to a test. Putting them to a test means that we stop using the methodology associated with them, start doing science in a different way and see what happens. Case studies such as those reported in the preceding chapters show that such tests occur all the time, and that they speak against the universal validity of any rule. All methodologies have their limitations and the only ‘rule’ that survives is ‘anything goes’. https://www.marxists.org/reference/subject/philosophy/works/ge/feyerabe.htm
Kuhn while at the University of California at Berkeley was introduced to the works of Wittgenstein and Feyerabend by Stanley Cavell in the early 1960s and discussed his Structure with Feyerabend. Some scholars have remarked how the recent revival of pragmatism can be understood in the context of Wittgenstein’s anti-foundationalism (Hmiel, 2016). Certainly, this was a feature of Wittgenstein’s thought, along with his anti-representationalism based on a language as use conception. Wittgenstein’s anti-foundationalism also became the basis for social constructivism in sociology developed by the likes of Ernst von Glasersfeld and David Bloor.
When I read Jean-Francois Lyotard’s (1984) The Postmodern Condition entirely by accident the year it was published in English, I was really taken by Lyotard’s use of Wittgenstein’s ‘language games’ to analyze the social bond as a series of ‘phrase regimes’ as he put it later in The Differend (Lyotard, 1988). I saw his interpretation as a form of creative appropriation rather than a scholarly reading based on textual analysis. What interested me was Lyotard’s use of Wittgenstein and the French reception more generally. It seemed to me a way out of the straight jacket of conceptual analysis of the so-called ‘London School’ in philosophy of education led by R. S. Peters and Paul Hirst that was allegedly based on ‘the revolution in philosophy’ introduced by Wittgenstein and others. Yet, I found the London School interpretation totally alien and could not understand how Peters and his colleagues could practice philosophy as a form of foundationalist conceptual analysis or ‘hygiene’ based on the search for necessary and sufficient conditions for the use of educational concepts. At the same time I recognize that this conception and interpretation of Wittgenstein by R. S. Peters and others actually provided and encouraged a robust analysis of concepts and a philosophy of education that while attributed to Wittgenstein against the spirit of his philosophy did achieve some significant gains for the field and provided some now classic texts like Ethics and Education that helped to reestablish the field in the late twentieth century.
In 1989, I wrote a paper entitled ‘Techno-science, Rationality and the University’ (Peters, 1989) as a discussion of Lyotard’s (1984) The Postmodern Condition based on an implicit understanding of Wittgenstein as an antifoundationalist thinker. I used the term ‘technoscience’ based on Lyotard’s use without too much thought at the time. It seemed to follow on quite naturally from Heidegger’s inversion of the traditional science/technology dualism and the model of applied science in his attempts to understand Western metaphysics as a form of techne as part of poesis and its use in connection with the concept of epistemology. (Techne is thus considered a kind of knowing from whence we derive ‘know-how’.) Lyotard’s use of the term also seemed to echo the tradition of French historical epistemology championed by Bachelard (1953) who popularized the term that characterized the long-term history of tool use. On this view technology only became combined with a nascent science during the seventeenth and eighteenth centuries during the European Enlightenment. Both Lyotard (1984) and Bruno Latour (1987) picked up on the term and used it in both a descriptive-analytical sense—the decisive role of technology-led science—and a critical-deconstructive sense to analyze scientific practices.
planetaryconversations.com/ 2021 “Life does not live,” reads the epigram that opens Minima Moralia by Theodor W. Adorno. In the age of its disintegration, in the context of fragmented reality, in which all master narratives have been shaken by an imponderable violence, planetary consciousness encounters existence in its incomprehensible singularity. As fragmented as the world she hopes to experience, cluttered with material and historical debris, philosophy is now faced with totalitarian unanimity, and she now chooses disintegration. To be a fragment among the fragments. A fragment that does not find in the other what interrupts it, but what continues it.
Imagined as a long letter, or as an endless conversation with the Friend, as well as with the Foreigner, philosophy experiences from its very inception the paradoxical condition of being at the same time in the search for a common eccentricity, a remote and unoccupied position, and, together with the other, for an inhabitable planet.