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manhefnawi

Pythagoras on the Purpose of Life and the Meaning of Wisdom - Brain Pickings - 0 views

www.brainpickings.org/...pythagoras-olympic-games

Mathematics Wisdom Purpose Life Philosophy

shared by manhefnawi on 14 Jun 18 - No Cached
  • Abiding insight into the aim of human existence from the man who revolutionized science and coined the word “philosopher.”
  • Alongside his revolutionary science, Pythagoras coined the word philosopher to describe himself as a “lover of wisdom” — a love the subject of which he encapsulated in a short, insightful meditation on the uses of philosophy in human life.
manhefnawi

Neuroscience: Overview, history, major branches - 0 views

www.medicalnewstoday.com/...248680.php

Cognitive Neuroscience

shared by manhefnawi on 12 Jun 18 - No Cached
  • Neuroscience has traditionally been classed as a subdivision of biology. These days, it is an interdisciplinary science that liaises closely with other disciplines, such as mathematics, linguistics, engineering, computer science, chemistry, philosophy, psychology, and medicine.
  • The ancient Egyptians thought the seat of intelligence was in the heart. Because of this belief, during the mummification process, they would remove the brain but leave the heart in the body.
  • Behavioral neuroscience - the study of the biological bases of behavior. Looking at how the brain affects behavior.
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  • Cognitive neuroscience - the study of higher cognitive functions that exist in humans, and their underlying neural basis. Cognitive neuroscience draws from linguistics, psychology, and cognitive science. Cognitive neuroscientists can take two broad directions: behavioral/experimental or computational/modeling, the aim being to understand the nature of cognition from a neural point of view.
sanderk

4 Everyday Items Einstein Helped Create - 0 views

www.nationalgeographic.com/...ty-lasers-solar-genius-science

einstein Knowledge Technology research

shared by sanderk on 13 Jan 20 - No Cached
  • Albert Einstein is justly famous for devising his theory of relativity, which revolutionized our understanding of space, time, gravity, and the universe. Relativity also showed us that matter and energy are just two different forms of the same thing—a fact that Einstein expressed as E=mc2, the most widely recognized equation in history.
  • Credit for inventing paper towels goes to the Scott Paper Company of Pennsylvania, which introduced the disposable product in 1907 as a more hygienic alternative to cloth towels. But in the very first physics article that Einstein ever published, he did analyze wicking: the phenomenon that allows paper towels to soak up liquids even when gravity wants to drag the fluid downward.
  • Again, Einstein didn’t invent solar cells; the first crude versions of them date back to 1839. But he did sketch out their basic principle of operation in 1905. His starting point was a simple analogy: If matter is lumpy—that is, if every substance in the universe consists of atoms and molecules—then surely light must be lumpy as well.
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  • Einstein turned this insight into an equation that described the jittering mathematically. His Brownian motion paper is widely recognized as the first incontrovertible proof that atoms and molecules really exist—and it still serves as the basis for some stock market forecasts.
  • He was trying to explain an odd fact that was first noticed by English botanist Robert Brown in 1827. Brown looked through his microscope and saw that the dust grains in a droplet of water were jittering around aimlessly. This Brownian motion, as it was first dubbed, had nothing to do with the grains being alive, so what kept them moving?
  • If you’ve been to a conference or played with a cat, chances are you’ve seen a laser pointer in action. In the nearly six decades since physicists demonstrated the first laboratory prototype of a laser in 1960, the devices have come to occupy almost every niche imaginable, from barcode readers to systems for hair removal.
  • So Einstein made an inspired guess: Maybe photons like to march in step, so that the presence of a bunch of them going in the same direction will increase the probability of a high-energy atom emitting another photon in that direction. He called this process stimulated emission, and when he included it in his equations, his calculations fit the observations perfectly
  • A laser is just a gadget for harnessing this phenomenon
Javier E

Understanding What's Wrong With Facebook | Talking Points Memo - 0 views

talkingpointsmemo.com/...ding-whats-wrong-with-facebook

evil structural tension 2nd generation internet comparative externality engine tech network manipulation architecture

shared by Javier E on 19 Sep 20 - No Cached
  • to really understand the problem with Facebook we need to understand the structural roots of that problem, how much of it is baked into the core architecture of the site and its very business model
  • much of it is inherent in the core strategies of the post-2000, second wave Internet tech companies that now dominate our information space and economy.
  • Facebook is an ingenious engine for information and ideational manipulation.
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  • Good old fashioned advertising does that to a degree. But Facebook is much more powerful, adaptive and efficient.
  • Facebook is designed to do specific things. It’s an engine to understand people’s minds and then manipulate their thinking.
  • Those tools are refined for revenue making but can be used for many other purposes. That makes it ripe for misuse and bad acting.
  • The core of all second wave Internet commerce operations was finding network models where costs grow mathematically and revenues grow exponentially.
  • The network and its dominance is the product and once it takes hold the cost inputs remained constrained while the revenues grow almost without limit.
  • Facebook is best understood as a fantastically profitable nuclear energy company whose profitability is based on dumping the waste on the side of the road and accepting frequent accidents and explosions as inherent to the enterprise.
  • That’s why these companies employ so few people relative to scale and profitability.
  • That’s why there’s no phone support for Google or Facebook or Twitter. If half the people on the planet are ‘customers’ or users that’s not remotely possible.
  • The core economic model requires doing all of it on the cheap. Indeed, what Zuckerberg et al. have created with Facebook is so vast that the money required not to do it on the cheap almost defies imagination.
  • Facebook’s core model and concept requires not taking responsibility for what others do with the engine created to drive revenue.
  • It all amounts to a grand exercise in socializing the externalities and keeping all the revenues for the owners.
  • Here’s a way to think about it. Nuclear power is actually incredibly cheap. The fuel is fairly plentiful and easy to pull out of the ground. You set up a little engine and it generates energy almost without limit. What makes it ruinously expensive is managing the externalities – all the risks and dangers, the radiation, accidents, the constant production of radioactive waste.
  • managing or distinguishing between legitimate and bad-acting uses of the powerful Facebook engine is one that would require huge, huge investments of money and armies of workers to manage
  • But back to Facebook. The point is that they’ve created a hugely powerful and potentially very dangerous machine
  • The core business model is based on harvesting the profits from the commercial uses of the machine and using algorithms and very, very limited personnel (relative to scale) to try to get a handle on the most outrageous and shocking abuses which the engine makes possible.
  • Zuckerberg may be a jerk and there really is a culture of bad acting within the organization. But it’s not about him being a jerk. Replace him and his team with non-jerks and you’d still have a similar core problem.
  • To manage the potential negative externalities, to take some responsibility for all the dangerous uses the engine makes possible would require money the owners are totally unwilling and in some ways are unable to spend.
blythewallick

What the brains of people with excellent general knowledge look like: Some people seem ... - 0 views

www.sciencedaily.com/...190731102127.htm

knowledge psychology research brain science science education

shared by blythewallick on 25 Oct 19 - No Cached
  • "Although we can precisely measure the general knowledge of people and this wealth of knowledge is very important for an individual's journey through life, we currently know little about the links between general knowledge and the characteristics of the brain,"
  • This makes it possible to reconstruct the pathways of nerve fibres and thus gain an insight into the structural network properties of the brain. By means of mathematical algorithms, the researchers assigned an individual value to the brain of each participant, which reflected the efficiency of his or her structural fibre network.
  • The participants also completed a general knowledge test called the Bochum Knowledge Test, which was developed in Bochum by Dr. Rüdiger Hossiep. It is comprised of over 300 questions from various fields of knowledge such as art and architecture or biology and chemistry. The team led by Erhan Genç finally investigated whether the efficiency of structural networking is associated with the amount of general knowledge stored.
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  • "We assume that individual units of knowledge are dispersed throughout the entire brain in the form of pieces of information," explains Erhan Genç. "Efficient networking of the brain is essential in order to put together the information stored in various areas of the brain and successfully recall knowledge content."
  • To answer the question of which constants occur in Einstein's theory of relativity, you have to connect the meaning of the term "constant" with knowledge of the theory of relativity. "We assume that more efficient networking of the brain contributes to better integration of pieces of information and thus leads to better results in a general knowledge test,
blythewallick

Physical activity in lessons improves students' attainment -- ScienceDaily - 0 views

www.sciencedaily.com/...191015192938.htm

brain science science psychology research knowledge education

shared by blythewallick on 19 Oct 19 - No Cached
  • "These improvements in physical activity levels and educational outcomes are the result of quite basic physical exercises. Teachers can easily incorporate these physical active lessons in the existing curriculum to improve the learning experience of students."
  • In one of the 42 studies analysed, eight- and nine-year-olds simulated travelling the world by running on the spot in between answering questions relating to different countries. The research team, also led by Dr Norris at UCL, concluded that the children were more active and more focused on the task than peers in a control group, following teachers' instructions more closely.
  • In another study in the Netherlands, primary school children who took part in physically active lessons three times a week over two years made significantly better progress in spelling and mathematics than their peers -- equating to four months of extra learning gains.
krystalxu

Psychology's Role in Mathematics and Science Education - 0 views

www.apa.org/...psychology-role.aspx

math sciece

shared by krystalxu on 09 Mar 18 - No Cached
  • as well as research advances in social and motivational issues and assessment, offer new opportunities to help bridge the gap between basic research and classroom practice.
krystalxu

Behavioral economics: Reunifying psychology and economics | Proceedings of the National... - 0 views

www.pnas.org/10575

Behavioral Economics

shared by krystalxu on 09 Mar 18 - No Cached
  • A recent approach, “behavioral economics,” seeks to use psychology to inform economics, while maintaining the emphases on mathematical structure and explanation of field data that distinguish economics from other social sciences (1–3).
kaylynfreeman

How Reliable Are the Social Sciences? - The New York Times - 1 views

opinionator.blogs.nytimes.com/...liable-are-the-social-sciences

psychology science research knowledge brain science

shared by kaylynfreeman on 01 Mar 18 - No Cached
  • How much authority should we give to such work in our policy decisions?  The question is important because media reports often seem to assume that any result presented as “scientific” has a claim to our serious attention.
  • A rational assessment of a scientific result must first take account of the broader context of the particular science involved.  Where does the result lie on the continuum from preliminary studies, designed to suggest further directions of research, to maximally supported conclusions of the science? 
  • Second, and even more important, there is our overall assessment of work in a given science in comparison with other sciences.  The core natural sciences (e.g., physics, chemistry, biology) are so well established that we readily accept their best-supported conclusions as definitive. 
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  • While the physical sciences produce many detailed and precise predictions, the social sciences do not.  The reason is that such predictions almost always require randomized controlled experiments, which are seldom possible when people are involved.  For one thing, we are too complex: our behavior depends on an enormous number of tightly interconnected variables that are extraordinarily difficult to  distinguish and study separately
  • Without a strong track record of experiments leading to successful predictions, there is seldom a basis for taking social scientific results as definitive
  • our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do.
  • Given the limited predictive success and the lack of consensus in social sciences, their conclusions can seldom be primary guides to setting policy.  At best, they can supplement the general knowledge, practical experience, good sense and critical intelligence that we can only hope our political leaders will have.
  • How much authority should we give to such work in our policy decisions?  The question is important because media reports often seem to assume that any result presented as “scientific” has a claim to our serious attention.
  • Without a strong track record of experiments leading to successful predictions, there is seldom a basis for taking social scientific results as definitive
  • our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do
  • our policy discussions should simply ignore social scientific research.  We should, as Manzi himself proposes, find ways of injecting more experimental data into government decisions.  But above all, we need to develop a much better sense of the severely limited reliability of social scientific results.   Media reports of research should pay far more attention to these limitations, and scientists reporting the results need to emphasize what they don’t show as much as what they do.
  • Social sciences may be surrounded by the “paraphernalia” of the natural sciences, such as technical terminology, mathematical equations, empirical data and even carefully designed experiments. 
  • Given the limited predictive success and the lack of consensus in social sciences, their conclusions can seldom be primary guides to setting policy.  At best, they can supplement the general knowledge, practical experience, good sense and critical intelligence that we can only hope our political leaders will have.
Javier E

Covid-19 expert Karl Friston: 'Germany may have more immunological "dark matter"' | Wor... - 0 views

www.theguardian.com/...more-immunological-dark-matter

germany modeling pandemic uk math research Technology

shared by Javier E on 31 May 20 - No Cached
  • Our approach, which borrows from physics and in particular the work of Richard Feynman, goes under the bonnet. It attempts to capture the mathematical structure of the phenomenon – in this case, the pandemic – and to understand the causes of what is observed. Since we don’t know all the causes, we have to infer them. But that inference, and implicit uncertainty, is built into the models
  • That’s why we call them generative models, because they contain everything you need to know to generate the data. As more data comes in, you adjust your beliefs about the causes, until your model simulates the data as accurately and as simply as possible.
  • A common type of epidemiological model used today is the SEIR model, which considers that people must be in one of four states – susceptible (S), exposed (E), infected (I) or recovered (R). Unfortunately, reality doesn’t break them down so neatly. For example, what does it mean to be recovered?
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  • SEIR models start to fall apart when you think about the underlying causes of the data. You need models that can allow for all possible states, and assess which ones matter for shaping the pandemic’s trajectory over time.
  • These techniques have enjoyed enormous success ever since they moved out of physics. They’ve been running your iPhone and nuclear power stations for a long time. In my field, neurobiology, we call the approach dynamic causal modelling (DCM). We can’t see brain states directly, but we can infer them given brain imaging data
  • Epidemiologists currently tackle the inference problem by number-crunching on a huge scale, making use of high-performance computers. Imagine you want to simulate an outbreak in Scotland. Using conventional approaches, this would take you a day or longer with today’s computing resources. And that’s just to simulate one model or hypothesis – one set of parameters and one set of starting conditions.
  • Using DCM, you can do the same thing in a minute. That allows you to score different hypotheses quickly and easily, and so to home in sooner on the best one.
  • This is like dark matter in the universe: we can’t see it, but we know it must be there to account for what we can see. Knowing it exists is useful for our preparations for any second wave, because it suggests that targeted testing of those at high risk of exposure to Covid-19 might be a better approach than non-selective testing of the whole population.
  • Our response as individuals – and as a society – becomes part of the epidemiological process, part of one big self-organising, self-monitoring system. That means it is possible to predict not only numbers of cases and deaths in the future, but also societal and institutional responses – and to attach precise dates to those predictions.
  • How well have your predictions been borne out in this first wave of infections?For London, we predicted that hospital admissions would peak on 5 April, deaths would peak five days later, and critical care unit occupancy would not exceed capacity – meaning the Nightingale hospitals would not be required. We also predicted that improvements would be seen in the capital by 8 May that might allow social distancing measures to be relaxed – which they were in the prime minister’s announcement on 10 May. To date our predictions have been accurate to within a day or two, so there is a predictive validity to our models that the conventional ones lack.
  • What do your models say about the risk of a second wave?The models support the idea that what happens in the next few weeks is not going to have a great impact in terms of triggering a rebound – because the population is protected to some extent by immunity acquired during the first wave. The real worry is that a second wave could erupt some months down the line when that immunity wears off.
  • the important message is that we have a window of opportunity now, to get test-and-trace protocols in place ahead of that putative second wave. If these are implemented coherently, we could potentially defer that wave beyond a time horizon where treatments or a vaccine become available, in a way that we weren’t able to before the first one.
  • We’ve been comparing the UK and Germany to try to explain the comparatively low fatality rates in Germany. The answers are sometimes counterintuitive. For example, it looks as if the low German fatality rate is not due to their superior testing capacity, but rather to the fact that the average German is less likely to get infected and die than the average Brit. Why? There are various possible explanations, but one that looks increasingly likely is that Germany has more immunological “dark matter” – people who are impervious to infection, perhaps because they are geographically isolated or have some kind of natural resistance
  • Any other advantages?Yes. With conventional SEIR models, interventions and surveillance are something you add to the model – tweaks or perturbations – so that you can see their effect on morbidity and mortality. But with a generative model these things are built into the model itself, along with everything else that matters.
  • Are generative models the future of disease modelling?That’s a question for the epidemiologists – they’re the experts. But I would be very surprised if at least some part of the epidemiological community didn’t become more committed to this approach in future, given the impact that Feynman’s ideas have had in so many other disciplines.
Javier E

Technopoly-Chs. 9,10--Scientism, the great symbol drain - 0 views

scientism science social science narrative objectivity advertising morality authority coherence Postman book notes

shared by Javier E on 02 Oct 21 - No Cached
  • By Scientism, I mean three interrelated ideas that, taken together, stand as one of the pillars of Technopoly.
  • The first and indispensable idea is, as noted, that the methods of the natural sciences can be applied to the study of human behavior. This idea is the backbone of much of psychology and sociology as practiced at least in America, and largely accounts for the fact that social science, to quote F. A. Hayek, "has cont~ibuted scarcely anything to our understanding of social phenomena." 2
  • The second idea is, as also noted, that social science generates specific principles which can be used to organize society on a rational and humane basis. This implies that technical meansmostly "invisible technologies" supervised by experts-can be designed to control human behavior and set it on the proper course.
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  • The third idea is that faith in science can serve as a comprehensive belief system that gives meaning to life, as well. as a sense of well-being, morality, and even immortality.
  • the spirit behind this scientific ideal inspired several men to believe that the reliable and predictable knowledge that could be obtained about stars and atoms could also be obtained about human behavior.
  • Among the best known of these early "social scientists" were Claude-Henri de Saint-Simon, Prosper Enfantin, and, of course, Auguste Comte.
  • They held in common two beliefs to which T echnopoly is deeply indebted: that the natural sciences provide a method to unlock the secrets of both the human heart and the direction of social life; that society can be rationally and humanely reorganized according to principles that social science will uncover. It is with these men that the idea of "social engineering" begins and the seeds of Scientism are planted.
  • Information produced by counting may sometimes be valuable in helping a person get an idea, or, even more so, in providing support for an idea. But the mere activity of counting does not make science.
  • Nor does observing th_ings, though it is sometimes said that if one is empirical, one is scientific. To be empirical means to look at things before drawing conclusions. Everyone, therefore, is an empiricist, with the possible exception of paranoid schizophrenics.
  • What we may call science, then, is the quest to find the immutable and universal laws that govern processes, presuming that there are cause-and-effect relations among these processes. It follows that the quest to understand human behavior and feeling can in no sense except the most trivial be called science.
  • Scientists do strive to be empirical and where possible precise, but it is also basic to their enterprise that they maintain a high degree of objectivity, which means that they study things independently of what people think or do about them.
  • I do not say, incidentally, that the Oedipus complex and God do not exist. Nor do I say that to believe in them is harmful-far from it. I say only that, there being no tests that could, in principle, show them to be false, they fall outside the purview Scientism 151 of science, as do almost all theories that make up the content of "social science."
  • in the nineteenth centu~, novelists provided us with most of the powerful metaphors and images of our culture.
  • This fact relieves the scientist of inquiring into their values and motivations and for this reason alone separates science from what is called social science, consigning the methodology of the latter (to quote Gunnar Myrdal) to the status of the "metaphysical and pseudo-objective." 3
  • The status of social-science methods is further reduced by the fact that there are almost no experiments that will reveal a social-science theory to be false.
  • et us further suppose that Milgram had found that 100 percent of his 1 subjecl:s did what they were told, with or without Hannah Arendt. And now let us suppose that I tell you a story of a Scientism 153 group of people who in some real situation refused to comply with the orders of a legitimate authority-let us say, the Danes who in the face of Nazi occupation helped nine thousand Jews escape to Sweden. Would you say to me that this cannot be so because Milgram' s study proves otherwise? Or would you say that this overturns Milgram's work? Perhaps you would say that the Danish response is not relevant, since the Danes did not regard the Nazi occupation as constituting legitimate autho!ity. But then, how would we explain the cooperative response to Nazi authority of the French, the Poles, and the Lithuanians? I think you would say none of these things, because Milgram' s experiment qoes not confirm or falsify any theory that might be said to postulate a law of human nature. His study-which, incidentally, I find both fascinating and terrifying-is not science. It is something else entirely.
  • Freud, could not imagine how the book could be judged exemplary: it was science or it was nothing. Well, of course, Freud was wrong. His work is exemplary-indeed, monumental-but scarcely anyone believes today that Freud was doing science, any more than educated people believe that Marx was doing science, or Max Weber or Lewis Mumford or Bruno Bettelheim or Carl Jung or Margaret Mead or Arnold Toynbee. What these people were doing-and Stanley Milgram was doing-is documenting the behavior and feelings of people as they confront problems posed by their culture.
  • the stories of social r~searchers are much closer in structure and purpose to what is called imaginative literature; that is to say, both a social researcher and a novelist give unique interpretations to a set of human events and support their interpretations with examples in various forms. Their interpretations cannot be proved or disproved but will draw their appeal from the power of their language, the depth of their explanations, the relevance of their examples, and the credibility of their themes.
  • And all of this has, in both cases, an identifiable moral purpose.
  • The words "true" and "false" do not apply here in the sense that they are used in mathematics or science. For there is nothing universally and irrevocably true or false about these interpretations. There are no critical tests to confirm or falsify them. There are no natural laws from which they are derived. They are bound by time, by situation, and above all by the cultural prejudices of the researcher or writer.
  • Both the novelist and the social researcher construct their stories by the use of archetypes and metaphors.
  • Cervantes, for example, gave us the enduring archetype of the incurable dreamer and idealist in Don Quixote. The social historian Marx gave us the archetype of the ruthless and conspiring, though nameless, capitalist. Flaubert gave us the repressed b~urgeois romantic in Emma Bovary. And Margaret Mead gave us the carefree, guiltless Samoan adolescent. Kafka gave us the alienated urbanite driven to self-loathing. And Max Weber gave us hardworking men driven by a mythology he called the Protestant Ethic. Dostoevsky gave us the egomaniac redeemed by love and religious fervor. And B. F. Skinner gave us the automaton redeemed by a benign technology.
  • Why do such social researchers tell their stories? Essentially for didactic and moralistic purposes. These men and women tell their stories for the same reason the Buddha, Confucius, Hillel, and Jesus told their stories (and for the same reason D. H. Lawrence told his).
  • Moreover, in their quest for objectivity, scientists proceed on the assumption that the objects they study are indifferent to the fact that they are being studied.
  • If, indeed, the price of civilization is repressed sexuality, it was not Sigmund Freud who discovered it. If the consciousness of people is formed by their material circumstances, it was not Marx who discovered it. If the medium is the message, it was not McLuhan who discovered it. They have merely retold ancient stories in a modem style.
  • Unlike science, social research never discovers anything. It only rediscovers what people once were told and need to be told again.
  • Only in knowing ~omething of the reasons why they advocated education can we make sense of the means they suggest. But to understand their reas.ons we must also understand the narratives that governed their view of the world. By narrative, I mean a story of human history that gives meaning to the past, explains the present, and provides guidance for the future.
  • In Technopoly, it is not Scientism 159 enough to say, it is immoral and degrading to allow people to be homeless. You cannot get anywhere by asking a judge, a politician, or a bureaucrat to r~ad Les Miserables or Nana or, indeed, the New Testament. Y 01.i must show that statistics have produced data revealing the homeless to be unhappy and to be a drain on the economy. Neither Dostoevsky nor Freud, Dickens nor Weber, Twain nor Marx, is now a dispenser of legitimate knowledge. They are interesting; they are ''.worth reading"; they are artifacts of our past. But as for "truth," we must tum to "science."
  • In Technopoly, it is not enough for social research to rediscover ancient truths or to comment on and criticize the moral behavior of people. In T echnopoly, it is an insult to call someone a "moralizer." Nor is it sufficient for social research to put forward metaphors, images, and ideas that can help people live with some measure of understanding and dignity.
  • Such a program lacks the aura of certain knowledge that only science can provide. It becomes necessary, then, to transform psychology, sociology, and anthropology into "sciences," in which humanity itself becomes an object, much like plants, planets, or ice cubes.
  • That is why the commonplaces that people fear death and that children who come from stable families valuing scholarship will do well in school must be announced as "discoveries" of scientific enterprise. In this way, social resear~hers can see themselves, and can be seen, as scientists, researchers without bias or values, unburdened by mere opinion. In this way, social policies can be claimed to rest on objectively determined facts.
  • given the psychological, social, and material benefits that attach to the label "scientist," it is not hard to see why social researchers should find it hard to give it up.
  • Our social "s'cientists" have from the beginning been less tender of conscience, or less rigorous in their views of science, or perhaps just more confused about the questions their procedures can answer and those they cannot. In any case, they have not been squeamish about imputing to their "discoveries" and the rigor of their procedures the power to direct us in how we ought rightly to behave.
  • It is less easy to see why the rest of us have so willingly, even eagerly, cooperated in perpetuating the same illusion.
  • When the new technologies and techniques and spirit of men like Galileo, Newton, and Bacon laid the foundations of natural science, they also discredited the authority of earlier accounts of the physical world, as found, for example, in the great tale of Genesis. By calling into question the truth of such accounts in one realm, science undermined the whole edifice of belief in sacred stories and ultimately swept away with it the source to which most humans had looked for moral authority. It is not too much to say, I think, that the desacralized world has been searching for an alternative source of moral authority ever since.
  • We welcome them gladly, and the claim explicitly made or implied, because we need so desperately to find some source outside the frail and shaky judgments of mortals like ourselves to authorize our moral decisions and behavior. And outside of the authority of brute force, which can scarcely be called moral, we seem to have little left but the authority of procedures.
  • It is not merely the misapplication of techniques such as quantification to questions where numbers have nothing to say; not merely the confusion of the material and social realms of human experience; not merely the claim of social researchers to be applying the aims and procedures of natural scien\:e to the human world.
  • This, then, is what I mean by Scientism.
  • It is the desperate hope, and wish, and ultimately the illusory belief that some standardized set of procedures called "science" can provide us with an unimpeachable source of moral authority, a suprahuman basis for answers to questions like "What is life, and when, and why?" "Why is death, and suffering?" 'What is right and wrong to do?" "What are good and evil ends?" "How ought we to think and feel and behave?
  • Science can tell us when a heart begins to beat, or movement begins, or what are the statistics on the survival of neonates of different gestational ages outside the womb. But science has no more authority than you do or I do to establish such criteria as the "true" definition of "life" or of human state or of personhood.
  • Social research can tell us how some people behave in the presence of what they believe to be legitimate authority. But it cannot tell us when authority is "legitimate" and when not, or how we must decide, or when it may be right or wrong to obey.
  • To ask of science, or expect of science, or accept unchallenged from science the answers to such questions is Scientism. And it is Technopoly's grand illusion.
  • In the institutional form it has taken in the United States, advertising is a symptom of a world-view 'that sees tradition as an obstacle to its claims. There can, of course, be no functioning sense of tradition without a measure of respect for symbols. Tradition is, in fact, nothing but the acknowledgment of the authority of symbols and the relevance of the narratives that gave birth to them. With the erosion of symbols there follows a loss of narrative, which is one of the most debilitating consequences of Technopoly' s power.
  • What the advertiser needs to know is not what is right about the product but what is wrong about the buyer. And so the balance of business expenditures shifts from product research to market research, which meahs orienting business away from making products of value and toward making consumers feel valuable. The business of business becomes pseudo-therapy; the consumer, a patient reassl.,lred by psychodramas.
  • At the moment, 1t 1s considered necessary to introduce computers to the classroom, as it once was thought necessary to bring closed-circuit television and film to the classroom. To the question "Why should we do this?" the answer is: "To make learning more efficient and more interesting." Such an answer is considered entirely adequate, since in T ~chnopoly efficiency and interest need no justification. It is, therefore, usually not noticed that this answer does not address the question "What is learning for?"
  • What this means is that somewhere near the core of Technopoly is a vast industry with license to use all available symbols to further the interests of commerce, by devouring the psyches of consumers.
  • In the twentieth century, such metaphors and images have come largely from the pens of social historians and researchers. ·Think of John Dewey, William James, Erik Erikson, Alfred Kinsey, Thorstein Veblen, Margaret Mead, Lewis Mumford, B. F. Skinner, Carl Rogers, Marshall McLuhan, Barbara Tuchman, Noam Chomsky, Robert Coles, even Stanley Milgram, and you must acknowledge that our ideas of what we are like and what kind of country we live in come from their stories to a far greater extent than from the stories of our most renowned novelists.
  • social idea that must be advanced through education.
  • Confucius advocated teaching "the Way" because in tradition he saw the best hope for social order. As our first systematic fascist, Plato wished education to produce philosopher kings. Cicero argued that education must free the student from the tyranny of the present. Jefferson thought the purpose of education is to teach the young how to protect their liberties. Rousseau wished education to free the young from the unnatural constraints of a wicked and arbitrary social order. And among John Dewey's aims was to help the student function without certainty in a world of constant change and puzzling· ambiguities.
  • The point is that cultures must have narratives and will find them where they will, even if they lead to catastrophe. The alternative is to live without meaning, the ultimate negation of life itself.
  • It is also to the point to say that each narrative is given its form and its emotional texture through a cluster of symbols that call for respect and allegiance, even devotion.
  • by definition, there can be no education philosophy that does not address what learning is for. Confucius, Plato, Quintilian, Cicero, Comenius, Erasmus, Locke, Rousseau, Jefferson, Russell, Montessori, Whitehead, and Dewey--each believed that there was some transcendent political, spiritual, or
  • The importance of the American Constitution is largely in its function as a symbol of the story of our origins. It is our political equivalent of Genesis. To mock it, to• ignore it, to circwnvent it is to declare the irrelevance of the story of the United States as a moral light unto the world. In like fashion, the Statue of Liberty is the key symbol of the story of America as the natural home of the teeming masses, from anywhere, yearning to be free.
  • There are those who believe--as did the great historian Arnold Toynbee-that without a comprehensive religious narrative at its center a culture must decline. Perhaps. There are, after all, other sources-mythology, politics, philosophy, and science; for example--but it is certain that no culture can flourish without narratives of transcendent orjgin and power.
  • This does not mean that the mere existence of such a narrative ensures a culture's stability and strength. There are destructive narratives. A narrative provides meaning, not necessarily survival-as, for example, the story provided by Adolf Hitler to the German nation in t:he 1930s.
  • What story does American education wish to tell now? In a growing Technopoly, what do we believe education is for?
  • The answers are discouraging, and one of. them can be inferred from any television commercial urging the young to stay in school. The commercial will either imply or state explicitly that education will help the persevering student to get a ·good job. And that's it. Well, not quite. There is also the idea that we educate ourselves to compete with the Japanese or the Germans in an economic struggle to be number one.
  • Young men, for example, will learn how to make lay-up shots when they play basketball. To be able to make them is part of the The Great Symbol Drain 177 definition of what good players are. But they do not play basketball for that purpose. There is usually a broader, deeper, and more meaningful reason for wanting to play-to assert their manhood, to please their fathers, to be acceptable to their peers, even for the sheer aesthetic pleasure of the game itself. What you have to do to be a success must be addressed only after you have found a reason to be successful.
  • Bloom's solution is that we go back to the basics of Western thought.
  • He wants us to teach our students what Plato, Aristotle, Cicero, Saint Augustine, and other luminaries have had to say on the great ethical and epistemological questions. He believes that by acquainting themselves with great books our students will acquire a moral and intellectual foundation that will give meaning and texture to their lives.
  • Hirsch's encyclopedic list is not a solution but a description of the problem of information glut. It is therefore essentially incoherent. But it also confuses a consequence of education with a purpose. Hirsch attempted to answer the question "What is an educated person?" He left unanswered the question "What is an education for?"
  • Those who reject Bloom's idea have offered several arguments against it. The first is that such a purpose for education is elitist: the mass of students would not find the great story of
  • Western civilization inspiring, are too deeply alienated from the past to find it so, and would therefore have difficulty connecting the "best that has been thought and said" to their own struggles to find q1eaning in their lives.
  • A second argument, coming from what is called a "leftist" perspective, is even more discouraging. In a sense, it offers a definition of what is meant by elitism. It asserts that the "story of Western civilization" is a partial, biased, and even oppressive one. It is not the story of blacks, American Indians, Hispanics, women, homosexuals-of any people who are not white heterosexual males of Judea-Christian heritage. This claim denies that there is or can be a national culture, a narrative of organizing power and inspiring symbols which all citizens can identify with and draw sustenance from. If this is true, it means nothing less than that our national symbols have been drained of their power to unite, and that education must become a tribal affair; that is, each subculture must find its own story and symbols, and use them as the moral basis of education.
  • nto this void comes the Technopoly story, with its emphasis on progress without limits, rights without responsibilities, and technology without cost. The T echnopoly story is without a moral center. It puts in its place efficiency, interest, and economic advance. It promises heaven on earth through the conveniences of technological progress. It casts aside all traditional narratives and symbols that· suggest stability and orderliness, and tells, instead, of a life of skills, technical expertise, and the ecstasy of consumption. Its purpose is to produce functionaries for an ongoing Technopoly.
  • It answers Bloom by saying that the story of Western civilization is irrelevant; it answers the political left by saying there is indeed a common culture whose name is T echnopoly and whose key symbol is now the computer, toward which there must be neither irreverence nor blasphemy. It even answers Hirsch by saying that there are items on his list that, if thought about too deeply and taken too seriously, will interfere with the progress of technology.
Javier E

Meet DALL-E, the A.I. That Draws Anything at Your Command - The New York Times - 0 views

www.nytimes.com/...openai-images-dall-e.html

ai drawing meaning semantic web language technology

shared by Javier E on 07 Apr 22 - No Cached
  • A half decade ago, the world’s leading A.I. labs built systems that could identify objects in digital images and even generate images on their own, including flowers, dogs, cars and faces. A few years later, they built systems that could do much the same with written language, summarizing articles, answering questions, generating tweets and even writing blog posts.
  • DALL-E is a notable step forward because it juggles both language and images and, in some cases, grasps the relationship between the two
  • “We can now use multiple, intersecting streams of information to create better and better technology,”
  • ...5 more annotations...
  • when Mr. Nichol tweaked his requests a little, adding or subtracting a few words here or there, it provided what he wanted. When he asked for “a piano in a living room filled with sand,” the image looked more like a beach in a living room.
  • DALL-E is what artificial intelligence researchers call a neural network, which is a mathematical system loosely modeled on the network of neurons in the brain.
  • the same technology that recognizes the commands spoken into smartphones and identifies the presence of pedestrians as self-driving cars navigate city streets.
  • A neural network learns skills by analyzing large amounts of data. By pinpointing patterns in thousands of avocado photos, for example, it can learn to recognize an avocado.
  • DALL-E looks for patterns as it analyzes millions of digital images as well as text captions that describe what each image depicts. In this way, it learns to recognize the links between the images and the words.
peterconnelly

Where Will We Be in 20 Years? - The New York Times - 0 views

www.nytimes.com/...ture-society-demographics.html

new york times

shared by peterconnelly on 01 Jun 22 - No Cached
  • “Demographics are destiny.”It is a phrase, often attributed to the French philosopher Auguste Comte, that suggests much of the future is preordained by the very simple trend lines of populations. Want to understand how the power dynamic between the United States and China will change over the next 20 years? An economist would tell you to look at the demographics of both countries. (China’s economy is likely to overtake the U.S. economy by 2028, but remain smaller on a per capita basis.)
  • Predicting the future may be a fool’s errand. But using demographic data to assess the opportunities and challenges of the next two decades is something that business and political leaders don’t do enough. We’re all too swept up in the here and now, the next quarter and the next year.
  • More people around the world had more disposable income and increasingly chose to live closer to cities with greater access to airports. That, married with the human condition that people like to be around other people, makes forecasting certain elements of the future almost mathematical.
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  • One aspect of the future that demographics can’t help predict are technological innovations.
  • About 70 percent of the world population is expected to live in urban areas by 2050, according to data from the United Nations.
  • The U.S. Energy Information Administration projects that the world will need about 28 percent more energy in 2040 than it did in 2015 based on the number of people in the country and consumption patterns; on our current trajectory, about 42 percent of electricity in the United States will come from renewable sources.
  • Technology has led us to expect that goods and services will be delivered at the push of a button, often within minutes.
  • Entrepreneurs, industry leaders and policymakers are already at work solving some of the problems that demographic data suggest are ahead of us, whether it’s figuring out how to incentivize farmers to sequester carbon, use insurance as a tool for reducing coal production, reinvent the motors that power heavy industry so they use less energy, or write laws that help govern code.
  • What about the metaverse? Or crypto technology? Or robots taking our jobs? Or A.I. taking over everything? Demographics can’t answer those questions. All of those things may happen, but life in 2041 may also look a lot like it does today — maybe with the exception of those flying cars.
Javier E

Strange things are taking place - at the same time - 0 views

edition.pagesuite.com/...dynamic_article_popover.aspx

coincidence miracle randomness fate psychology research

shared by Javier E on 06 Dec 22 - No Cached
  • In February 1973, Dr. Bernard Beitman found himself hunched over a kitchen sink in an old Victorian house in San Francisco, choking uncontrollably. He wasn’t eating or drinking, so there was nothing to cough up, and yet for several minutes he couldn’t catch his breath or swallow.The next day his brother called to tell him that 3,000 miles away, in Wilmington, Del., their father had died. He had bled into his throat, choking on his own blood at the same time as Beitman’s mysterious episode.
  • Overcome with awe and emotion, Beitman became fascinated with what he calls meaningful coincidences. After becoming a professor of psychiatry at the University of Missouri-Columbia, he published several papers and two books on the subject and started a nonprofit, the Coincidence Project, to encourage people to share their coincidence stories.
  • “What I look for as a scientist and a spiritual seeker are the patterns that lead to meaningful coincidences,” said Beitman, 80, from his home in Charlottesville, Va. “So many people are reporting this kind of experience. Understanding how it happens is part of the fun.”
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  • Beitman defines a coincidence as “two events coming together with apparently no causal explanation.” They can be life-changing, like his experience with his father, or comforting, such as when a loved one’s favorite song comes on the radio just when you are missing them most.
  • Although Beitman has long been fascinated by coincidences, it wasn’t until the end of his academic career that he was able to study them in earnest. (Before then, his research primarily focused on the relationship between chest pain and panic disorder.)
  • He started by developing the Weird Coincidence Survey in 2006 to assess what types of coincidences are most commonly observed, what personality types are most correlated with noticing them and how most people explain them. About 3,000 people have completed the survey so far.
  • he has drawn a few conclusions. The most commonly reported coincidences are associated withmass media: A person thinks of an idea and then hears or sees it on TV, the radio or the internet. Thinking of someone and then having that person call unexpectedly is next on the list, followed by being in the right place at the right time to advance one’s work, career or education.
  • People who describe themselves as spiritual or religious report noticing more meaningful coincidences than those who do not, and people are more likely to experience coincidences when they are in a heightened emotional state — perhaps under stress or grieving.
  • The most popular explanation among survey respondents for mysterious coincidences: God or fate. The second explanation: randomness. The third is that our minds are connected to one another. The fourth is that our minds are connected to the environment.
  • “Some say God, some say universe, some say random and I say ‘Yes,’ ” he said. “People want things to be black and white, yes or no, but I say there is mystery.”
  • He’s particularly interested in what he’s dubbed “simulpathity”: feeling a loved one’s pain at a distance, as he believes he did with his father. Science can’t currently explain how it might occur, but in his books he offers some nontraditional ideas, such as the existence of “the psychosphere,” a kind of mental atmosphere through which information and energy can travel between two people who are emotionally close though physically distant.
  • In his new book published in September, “Meaningful Coincidences: How and Why Synchronicity and Serendipity Happen,” he shares the story of a young man who intended to end his life by the shore of an isolated lake. While he sat crying in his car, another car pulled up and his brother got out. When the young man asked for an explanation, the brother said he didn’t know why he got in the car, where he was going, or what he would do when he got there. He just knew he needed to get in the car and drive.
  • David Hand, a British statistician and author of the 2014 book “The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day,” sits at the opposite end of the spectrum from Beitman. He says most coincidences are fairly easy to explain, and he specializes in demystifying even the strangest ones.
  • “When you look closely at a coincidence, you can often discover the chance of it happening is not as small as you think,” he said. “It’s perhaps not a 1-in-a-billion chance, but in fact a 1-in-a-hundred chance, and yeah, you would expect that would happen quite often.”
  • the law of truly large numbers. “You take something that has a very small chance of happening and you give it lots and lots and lots of opportunities to happen,” he said. “Then the overall probability becomes big.”
  • But just because Hand has a mathematical perspective doesn’t mean he finds coincidences boring. “It’s like looking at a rainbow,” he said. “Just because I understand the physics behind it doesn’t make it any the less wonderful.
  • Paying attention to coincidences, Osman and Johansen say, is an essential part of how humans make sense of the world. We rely constantly on our understanding of cause and effect to survive.
  • “Coincidences are often associated with something mystical or supernatural, but if you look under the hood, noticing coincidences is what humans do all the time,”
  • Zeltzer has spent 50 years studying the writings of Carl Jung, the 20th century Swiss psychologist who introduced the modern Western world to the idea of synchronicity. Jung defined synchronicity as “the coincidence in time of two or more causally unrelated events which have the same meaning.”
  • One of Jung’s most iconic synchronistic stories concerned a patient who he felt had become so stuck in her rationality that it interfered with her ability to understand her psychology and emotional life.
  • One day, the patient was recounting a dream in which she’d received a golden scarab. Just then, Jung heard a gentle tapping at the window. He opened the window and a scarab-like beetle flew into the room. Jung plucked the insect out of the air and presented it to his patient. “Here is your scarab,” he said.The experience proved therapeutic because it demonstrated to Jung’s patient that the world is not always rational, leading her to break her own identification with rationality and thus become more open to her emotional life, Zeltzer explained
  • Like Jung, Zeltzer believes meaningful coincidences can encourage people to acknowledge the irrational and mysterious. “We have a fantasy that there is always an answer, and that we should know everything,”
  • Honestly, I’m not sure what to believe, but I’m not sure it matters. Like Beitman, my attitude is “Yes.”
Javier E

'The Godfather of AI' Quits Google and Warns of Danger Ahead - The New York Times - 0 views

www.nytimes.com/...bot-engineer-quits-hinton.html

danger AI pioneer industry warning technology research

shared by Javier E on 01 May 23 - No Cached
  • he officially joined a growing chorus of critics who say those companies are racing toward danger with their aggressive campaign to create products based on generative artificial intelligence, the technology that powers popular chatbots like ChatGPT.
  • Dr. Hinton said he has quit his job at Google, where he has worked for more than decade and became one of the most respected voices in the field, so he can freely speak out about the risks of A.I. A part of him, he said, now regrets his life’s work.
  • “I console myself with the normal excuse: If I hadn’t done it, somebody else would have,”
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  • Industry leaders believe the new A.I. systems could be as important as the introduction of the web browser in the early 1990s and could lead to breakthroughs in areas ranging from drug research to education.
  • But gnawing at many industry insiders is a fear that they are releasing something dangerous into the wild. Generative A.I. can already be a tool for misinformation. Soon, it could be a risk to jobs. Somewhere down the line, tech’s biggest worriers say, it could be a risk to humanity.
  • “It is hard to see how you can prevent the bad actors from using it for bad things,” Dr. Hinton said.
  • After the San Francisco start-up OpenAI released a new version of ChatGPT in March, more than 1,000 technology leaders and researchers signed an open letter calling for a six-month moratorium on the development of new systems because A.I technologies pose “profound risks to society and humanity.
  • Several days later, 19 current and former leaders of the Association for the Advancement of Artificial Intelligence, a 40-year-old academic society, released their own letter warning of the risks of A.I. That group included Eric Horvitz, chief scientific officer at Microsoft, which has deployed OpenAI’s technology across a wide range of products, including its Bing search engine.
  • Dr. Hinton, often called “the Godfather of A.I.,” did not sign either of those letters and said he did not want to publicly criticize Google or other companies until he had quit his job
  • Dr. Hinton, a 75-year-old British expatriate, is a lifelong academic whose career was driven by his personal convictions about the development and use of A.I. In 1972, as a graduate student at the University of Edinburgh, Dr. Hinton embraced an idea called a neural network. A neural network is a mathematical system that learns skills by analyzing data. At the time, few researchers believed in the idea. But it became his life’s work.
  • Dr. Hinton is deeply opposed to the use of artificial intelligence on the battlefield — what he calls “robot soldiers.”
  • In 2012, Dr. Hinton and two of his students in Toronto, Ilya Sutskever and Alex Krishevsky, built a neural network that could analyze thousands of photos and teach itself to identify common objects, such as flowers, dogs and cars.
  • In 2018, Dr. Hinton and two other longtime collaborators received the Turing Award, often called “the Nobel Prize of computing,” for their work on neural networks.
  • Around the same time, Google, OpenAI and other companies began building neural networks that learned from huge amounts of digital text. Dr. Hinton thought it was a powerful way for machines to understand and generate language, but it was inferior to the way humans handled language.
  • Then, last year, as Google and OpenAI built systems using much larger amounts of data, his view changed. He still believed the systems were inferior to the human brain in some ways but he thought they were eclipsing human intelligence in others.
  • “Maybe what is going on in these systems,” he said, “is actually a lot better than what is going on in the brain.”
  • As companies improve their A.I. systems, he believes, they become increasingly dangerous. “Look at how it was five years ago and how it is now,” he said of A.I. technology. “Take the difference and propagate it forwards. That’s scary.”
  • Until last year, he said, Google acted as a “proper steward” for the technology, careful not to release something that might cause harm. But now that Microsoft has augmented its Bing search engine with a chatbot — challenging Google’s core business — Google is racing to deploy the same kind of technology. The tech giants are locked in a competition that might be impossible to stop, Dr. Hinton said.
  • His immediate concern is that the internet will be flooded with false photos, videos and text, and the average person will “not be able to know what is true anymore.”
  • He is also worried that A.I. technologies will in time upend the job market. Today, chatbots like ChatGPT tend to complement human workers, but they could replace paralegals, personal assistants, translators and others who handle rote tasks. “It takes away the drudge work,” he said. “It might take away more than that.”
  • Down the road, he is worried that future versions of the technology pose a threat to humanity because they often learn unexpected behavior from the vast amounts of data they analyze. This becomes an issue, he said, as individuals and companies allow A.I. systems not only to generate their own computer code but actually run that code on their ow
  • And he fears a day when truly autonomous weapons — those killer robots — become reality.
  • “The idea that this stuff could actually get smarter than people — a few people believed that,” he said. “But most people thought it was way off. And I thought it was way off. I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that.”
  • Many other experts, including many of his students and colleagues, say this threat is hypothetical. But Dr. Hinton believes that the race between Google and Microsoft and others will escalate into a global race that will not stop without some sort of global regulation.
  • But that may be impossible, he said. Unlike with nuclear weapons, he said, there is no way of knowing whether companies or countries are working on the technology in secret. The best hope is for the world’s leading scientists to collaborate on ways of controlling the technology. “I don’t think they should scale this up more until they have understood whether they can control it,” he said.
  • Dr. Hinton said that when people used to ask him how he could work on technology that was potentially dangerous, he would paraphrase Robert Oppenheimer, who led the U.S. effort to build the atomic bomb: “When you see something that is technically sweet, you go ahead and do it.”
  • He does not say that anymore.
Javier E

An Existential Problem in the Search for Alien Life - The Atlantic - 0 views

www.theatlantic.com/...676238

life problem essence controversy n=1 definition explanation science research knowledge

shared by Javier E on 06 Dec 23 - No Cached
  • The fact is, we still don’t know what life is.
  • since the days of Aristotle, scientists and philosophers have struggled to draw a precise line between what is living and what is not, often returning to criteria such as self-organization, metabolism, and reproduction but never finding a definition that includes, and excludes, all the right things.
  • If you say life consumes fuel to sustain itself with energy, you risk including fire; if you demand the ability to reproduce, you exclude mules. NASA hasn’t been able to do better than a working definition: “Life is a self-sustaining chemical system capable of Darwinian evolution.”
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  • it lacks practical application. If humans found something on another planet that seemed to be alive, how much time would we have to sit around and wait for it to evolve?
  • The only life we know is life on Earth. Some scientists call this the n=1 problem, where n is the number of examples from which we can generalize.
  • Cronin studies the origin of life, also a major interest of Walker’s, and it turned out that, when expressed in math, their ideas were essentially the same. They had both zeroed in on complexity as a hallmark of life. Cronin is devising a way to systematize and measure complexity, which he calls Assembly Theory.
  • What we really want is more than a definition of life. We want to know what life, fundamentally, is. For that kind of understanding, scientists turn to theories. A theory is a scientific fundamental. It not only answers questions, but frames them, opening new lines of inquiry. It explains our observations and yields predictions for future experiments to test.
  • Consider the difference between defining gravity as “the force that makes an apple fall to the ground” and explaining it, as Newton did, as the universal attraction between all particles in the universe, proportional to the product of their masses and so on. A definition tells us what we already know; a theory changes how we understand things.
  • the potential rewards of unlocking a theory of life have captivated a clutch of researchers from a diverse set of disciplines. “There are certain things in life that seem very hard to explain,” Sara Imari Walker, a physicist at Arizona State University who has been at the vanguard of this work, told me. “If you scratch under the surface, I think there is some structure that suggests formalization and mathematical laws.”
  • Walker doesn’t think about life as a biologist—or an astrobiologist—does. When she talks about signs of life, she doesn’t talk about carbon, or water, or RNA, or phosphine. She reaches for different examples: a cup, a cellphone, a chair. These objects are not alive, of course, but they’re clearly products of life. In Walker’s view, this is because of their complexity. Life brings complexity into the universe, she says, in its own being and in its products, because it has memory: in DNA, in repeating molecular reactions, in the instructions for making a chair.
  • He measures the complexity of an object—say, a molecule—by calculating the number of steps necessary to put the object’s smallest building blocks together in that certain way. His lab has found, for example, when testing a wide range of molecules, that those with an “assembly number” above 15 were exclusively the products of life. Life makes some simpler molecules, too, but only life seems to make molecules that are so complex.
  • I reach for the theory of gravity as a familiar parallel. Someone might ask, “Okay, so in terms of gravity, where are we in terms of our understanding of life? Like, Newton?” Further back, further back, I say. Walker compares us to pre-Copernican astronomers, reliant on epicycles, little orbits within orbits, to make sense of the motion we observe in the sky. Cleland has put it in terms of chemistry, in which case we’re alchemists, not even true chemists yet
  • Walker’s whole notion is that it’s not only theoretically possible but genuinely achievable to identify something smaller—much smaller—that still nonetheless simply must be the result of life. The model would, in a sense, function like biosignatures as an indication of life that could be searched for. But it would drastically improve and expand the targets.
  • Walker would use the theory to predict what life on a given planet might look like. It would require knowing a lot about the planet—information we might have about Venus, but not yet about a distant exoplanet—but, crucially, would not depend at all on how life on Earth works, what life on Earth might do with those materials.
  • Without the ability to divorce the search for alien life from the example of life we know, Walker thinks, a search is almost pointless. “Any small fluctuations in simple chemistry can actually drive you down really radically different evolutionary pathways,” she told me. “I can’t imagine [life] inventing the same biochemistry on two worlds.”
  • Walker’s approach is grounded in the work of, among others, the philosopher of science Carol Cleland, who wrote The Quest for a Universal Theory of Life.
  • she warns that any theory of life, just like a definition, cannot be constrained by the one example of life we currently know. “It’s a mistake to start theorizing on the basis of a single example, even if you’re trying hard not to be Earth-centric. Because you’re going to be Earth-centric,” Cleland told me. In other words, until we find other examples of life, we won’t have enough data from which to devise a theory. Abstracting away from Earthliness isn’t a way to be agnostic, Cleland argues. It’s a way to be too abstract.
  • Cleland calls for a more flexible search guided by what she calls “tentative criteria.” Such a search would have a sense of what we’re looking for, but also be open to anomalies that challenge our preconceptions, detections that aren’t life as we expected but aren’t familiar not-life either—neither a flower nor a rock
  • it speaks to the hope that exploration and discovery might truly expand our understanding of the cosmos and our own world.
  • The astrobiologist Kimberley Warren-Rhodes studies life on Earth that lives at the borders of known habitability, such as in Chile’s Atacama Desert. The point of her experiments is to better understand how life might persist—and how it might be found—on Mars. “Biology follows some rules,” she told me. The more of those rules you observe, the better sense you have of where to look on other worlds.
  • In this light, the most immediate concern in our search for extraterrestrial life might be less that we only know about life on Earth, and more that we don’t even know that much about life on Earth in the first place. “I would say we understand about 5 percent,” Warren-Rhodes estimates of our cumulative knowledge. N=1 is a problem, and we might be at more like n=.05.
  • who knows how strange life on another world might be? What if life as we know it is the wrong life to be looking for?
  • We understand so little, and we think we’re ready to find other life?
Javier E

Peter Higgs, physicist who discovered Higgs boson, dies aged 94 | Peter Higgs | The Gua... - 0 views

www.theguardian.com/...vered-higgs-boson-dies-aged-94

physicist physics universe model higgs boson

shared by Javier E on 09 Apr 24 - No Cached
  • Peter Higgs, the Nobel prize-winning physicist who discovered a new particle known as the Higgs boson, has died.Higgs, 94, who was awarded the Nobel prize for physics in 2013 for his work in 1964 showing how the boson helped bind the universe together by giving particles their mass
  • “A giant of particle physics has left us,” Ellis told the Guardian. “Without his theory, atoms could not exist and radioactivity would be a force as strong as electricity and magnetism.
  • “His prediction of the existence of the particle that bears his name was a deep insight, and its discovery at Cern in 2012 was a crowning moment that confirmed his understanding of the way the Universe works.”
  • ...2 more annotations...
  • The particle that carries his name is perhaps the single most stunning example of how seemingly abstract mathematical ideas can make predictions which turn out to have huge physical consequences.”
  • The Royal Swedish Academy of Sciences, which awards the Nobel, said at the time the standard model of physics which underpins the scientific understanding of the universe “rests on the existence of a special kind of particle: the Higgs particle. This particle originates from an invisible field that fills up all space.“Even when the universe seems empty this field is there. Without it, we would not exist, because it is from contact with the field that particles acquire mass. The theory proposed by Englert and Higgs describes this process.”
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