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Javier E

Elon Musk is wrong to call for a pause on the AI race | The Spectator - 0 views

www.spectator.co.uk/...all-for-a-pause-on-the-ai-race

AI control tech race

shared by Javier E on 31 Mar 23 - No Cached
  • the idea of autonomous computers, ‘thinking’ for themselves, and eventually usurping humans, is the stuff of nonsense and lurid science fiction.
  • It is only the fevered imagination of the current crop of tech titans that allows them to believe that the world is on the cusp of a form of artificial intelligence that could prove a match for the genius and human intuition of someone like Einstein, threatening the future of the entire human race.
  • Moratoriums on scientific and technological research are never a good idea; others who do not have the same ethical or moral qualms will soon race to fill the gap.
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  • Even more absurd is the idea of giving unaccountable tech chiefs some moral licence to pronounce on good and evil, right and wrong, and what is best for the world.
Javier E

Twitter is dying | TechCrunch - 0 views

techcrunch.com/...twitter-is-dying

twitter musk knowledge network

shared by Javier E on 31 Mar 23 - No Cached
  • if the point is simply pure destruction — building a chaos machine by removing a source of valuable information from our connected world, where groups of all stripes could communicate and organize, and replacing that with a place of parody that rewards insincerity, time-wasting and the worst forms of communication in order to degrade the better half — then he’s done a remarkable job in very short order. Truly it’s an amazing act of demolition. But, well, $44 billion can buy you a lot of wrecking balls.
  • That our system allows wealth to be turned into a weapon to nuke things of broad societal value is one hard lesson we should take away from the wreckage of downed turquoise feathers.
  • We should also consider how the ‘rules based order’ we’ve devised seems unable to stand up to a bully intent on replacing free access to information with paid disinformation — and how our democratic systems seem so incapable and frozen in the face of confident vandals running around spray-painting ‘freedom’ all over the walls as they burn the library down.
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  • The simple truth is that building something valuable — whether that’s knowledge, experience or a network worth participating in — is really, really hard. But tearing it all down is piss easy.
  • It almost doesn’t matter if this is deliberate sabotage by Musk or the blundering stupidity of a clueless idiot.
Javier E

Opinion | Lower fertility rates are the new cultural norm - The Washington Post - 0 views

www.washingtonpost.com/...estigating-low-fertility-rates

fertility rate us research psychology social media tech norm

shared by Javier E on 30 Mar 23 - No Cached
  • The percentage who say that having children is very important to them has dropped from 43 percent to 30 percent since 2019. This fits with data showing that, since 2007, the total fertility rate in the United States has fallen from 2.1 lifetime births per woman, the “replacement rate” necessary to sustain population levels, to just 1.64 in 2020.
  • The U.S. economy is losing an edge that robust population dynamics gave it relative to low-birth-rate peer nations in Japan and Western Europe; this country, too, faces chronic labor-supply constraints as well as an even less favorable “dependency ratio” between workers and retirees than it already expected.
  • the timing and the magnitude of such a demographic sea-change cry out for explanation. What happened in 2007?
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  • New financial constraints on family formation are a potential cause, as implied by another striking finding in the Journal poll — 78 percent of adults lack confidence this generation of children will enjoy a better life than they do.
  • Yet a recent analysis for the Aspen Economic Strategy Group by Melissa S. Kearney and Phillip B. Levine, economics professors at the University of Maryland and Wellesley College, respectively, determined that “beyond the temporary effects of the Great Recession, no recent economic or policy change is responsible for a meaningful share of the decline in the US fertility rate since 2007.”
  • Their study took account of such factors as the high cost of child care, student debt service and housing as well as Medicaid coverage and the wider availability of long-acting reversible contraception. Yet they had “no success finding evidence” that any of these were decisive.
  • Kearney and Levine speculated instead that the answers lie in the cultural zeitgeist — “shifting priorities across cohorts of young adults,”
  • A possibility worth considering, they suggested, is that young adults who experienced “intensive parenting” as children now balk at the heavy investment of time and resources needed to raise their own kids that way: It would clash with their career and leisure goals.
  • another event that year: Apple released the first iPhone, a revolutionary cultural moment if there ever was one. The ensuing smartphone-enabled social media boom — Facebook had opened membership to anyone older than 13 in 2006 — forever changed how human beings relate with one another.
  • We are just beginning to understand this development’s effect on mental health, education, religious observance, community cohesion — everything. Why wouldn’t it also affect people’s willingness to have children?
  • one indirect way new media affect childbearing rates is through “time competition effects” — essentially, hours spent watching the tube cannot be spent forming romantic partnerships.
  • a 2021 review of survey data on young adults and adolescents in the United States and other countries, the years between 2009 and 2018 saw a marked decline in reported sexual activity.
  • the authors hypothesized that people are distracted from the search for partners by “increasing use of computer games and social media.
  • during the late 20th century, Brazil’s fertility rates fell after women who watched soap operas depicting smaller families sought to emulate them by having fewer children themselves.
  • This may be an area where incentives do not influence behavior, at least not enough. Whether the cultural shift to lower birthrates occurs on an accelerated basis, as in the United States after 2007, or gradually, as it did in Japan, it appears permanent — “sticky,” as policy wonks say.
Javier E

Opinion | I Did Not Feel the Need to See People Like Me on TV or in Books - The New Yor... - 0 views

www.nytimes.com/...entation-television-books.html

relevance reading tribe self goal other-directed self-centeredness learning education

shared by Javier E on 30 Mar 23 - No Cached
  • It reminds me of how many people complain that they don’t see themselves in movies, books, etc. When I was growing up, I didn’t much, either, but I can’t say that it bothered me.
  • But what I enjoyed about TV was seeing something other than myself. I liked it as a window on the world, not as a look into my own life.
  • It was the same with books. The last thing I expected when growing up was to read about myself
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  • There were plenty of books about Black people, but they tended to be about poor or working-class Black people and often depicted Black lives proscribed by discrimination and inequality
  • I was aware of two instances of myself in fiction of the time. One was the nerdy teenage middle-class Black girl in Louise Fitzhugh’s “Nobody’s Family Is Going to Change.” Then there was “Sarah Phillips” by Andrea Lee in 1984. That one was a near-sacred experience for me, in depicting a middle-class Black girl who grew up outside Philadelphia, went to Harvard and then moved to Europe. Here was someone I could have been, a variation on some people I knew
  • But I neither needed nor sought out more such books. How much me did I need? I read to learn about what I didn’t know.
  • when I started my graduate study, I explicitly did not want to study Black English. It was too close to home.
  • What fascinated me, and still does, are languages utterly unlike the one I grew up with. This is what I do my academic work on. I am happy to write about Black English, but I do it out of civic duty. What first hooked me on languages was hearing someone speak Hebrew
  • This idea that one, if brown, is to seek one’s self in what one reads and watches gets around quite a bit.
  • But still, the idea that Black people are deprived in not exploring what they already relate to is not as natural as it sounds.
  • This position is rooted, one suspects, as a defense against racism, in a sense that learning most meaningfully takes place within a warm comfort zone of cultural membership. But it’s a wide, wide world out there, and this position ultimately limits the mind and the soul.
  • I question its necessity in 2023. The etymology of the word “education” is related to the Latin “educere,” meaning to lead outward, not inward.
  • It can be especially ticklish to hear white people taking up the idea that Black people stray from their selves when taking up things beyond Blackness
  • I sense the idea that real Blackness means ever seeking yourself in your reading and viewing is a post-1966 thing, to refer to what I wrote here last week.
  • W.E.B. Du Bois had no such idea. He wrote: “I sit with Shakespeare, and he winces not. Across the color line I move arm in arm with Balzac and Dumas, where smiling men and welcoming women glide in gilded halls. From out the caves of evening that swing between the strong-limbed Earth and the tracery of the stars, I summon Aristotle and Aurelius and what soul I will, and they come all graciously with no scorn nor condescension.”
  • Du Bois adapted these “white” works to his own needs and predilections. Even the naked racism he lived with daily did not lead him to draw a line around “white” things as something alien to his essence
  • Rather, he insisted that these works were, in fact, part of his self, regardless of how wider society saw that self or how figures like Shakespeare and Aristotle would have seen him.
  • Du Bois, in this, was normal. Today I sit with “Succession,” Steely Dan and Saul Bellow, and they wince not. I see myself in none of them. Yes, Bellow had some nasty moments on race, such as a gruesomely prurient scene in “Mr. Sammler’s Planet.” But I’m sorry: I cannot let that one scene — or even two — deprive me of the symphonic reaches of “Herzog” and “Humboldt’s Gift.” What they offer, after all, becomes part of me along with everything else.
  • the truth is that characters I can see as me are now not uncommon on television in particular. Andre Braugher’s Captain Holt on “Brooklyn Nine-Nine” was about as close to me as I expect a sitcom character ever to be, for example. That was fun. But honestly, I didn’t need it. I live with me. I watch TV to see somebody else.
Javier E

Opinion | Do You Live in a 'Tight' State or a 'Loose' One? Turns Out It Matters Quite a... - 0 views

www.nytimes.com/...ed-blue-tight-loose-state.html

shared by Javier E on 30 Mar 23 - No Cached
  • Political biases are omnipresent, but what we don’t fully understand yet is how they come about in the first place.
  • In 2014, Michele J. Gelfand, a professor of psychology at the Stanford Graduate School of Business formerly at the University of Maryland, and Jesse R. Harrington, then a Ph.D. candidate, conducted a study designed to rank the 50 states on a scale of “tightness” and “looseness.”
  • titled “Tightness-Looseness Across the 50 United States,” the study calculated a catalog of measures for each state, including the incidence of natural disasters, disease prevalence, residents’ levels of openness and conscientiousness, drug and alcohol use, homelessness and incarceration rates.
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  • Gelfand and Harrington predicted that “‘tight’ states would exhibit a higher incidence of natural disasters, greater environmental vulnerability, fewer natural resources, greater incidence of disease and higher mortality rates, higher population density, and greater degrees of external threat.”
  • The South dominated the tight states: Mississippi, Alabama Arkansas, Oklahoma, Tennessee, Texas, Louisiana, Kentucky, South Carolina and North Carolina
  • states in New England and on the West Coast were the loosest: California, Oregon, Washington, Maine, Massachusetts, Connecticut, New Hampshire and Vermont.
  • Cultural differences, Gelfand continued, “have a certain logic — a rationale that makes good sense,” noting that “cultures that have threats need rules to coordinate to survive (think about how incredibly coordinated Japan is in response to natural disasters).
  • “Rule Makers, Rule Breakers: How Tight and Loose Cultures Wire the World” in 2018, in which she described the results of a 2016 pre-election survey she and two colleagues had commissioned
  • The results were telling: People who felt the country was facing greater threats desired greater tightness. This desire, in turn, correctly predicted their support for Trump. In fact, desired tightness predicted support for Trump far better than other measures. For example, a desire for tightness predicted a vote for Trump with 44 times more accuracy than other popular measures of authoritarianism.
  • The 2016 election, Gelfand continued, “turned largely on primal cultural reflexes — ones that had been conditioned not only by cultural forces, but by a candidate who was able to exploit them.”
  • Gelfand said:Some groups have much stronger norms than others; they’re tight. Others have much weaker norms; they’re loose. Of course, all cultures have areas in which they are tight and loose — but cultures vary in the degree to which they emphasize norms and compliance with them.
  • In both 2016 and 2020, Donald Trump carried all 10 of the top “tight” states; Hillary Clinton and Joe Biden carried all 10 of the top “loose” states.
  • The tight-loose concept, Gelfand argued,is an important framework to understand the rise of President Donald Trump and other leaders in Poland, Hungary, Italy, and France,
  • cultures that don’t have a lot of threat can afford to be more permissive and loose.”
  • The gist is this: when people perceive threat — whether real or imagined, they want strong rules and autocratic leaders to help them survive
  • My research has found that within minutes of exposing study participants to false information about terrorist incidents, overpopulation, pathogen outbreaks and natural disasters, their minds tightened. They wanted stronger rules and punishments.
  • Gelfand writes that tightness encourages conscientiousness, social order and self-control on the plus side, along with close-mindedness, conventional thinking and cultural inertia on the minus side.
  • Looseness, Gelfand posits, fosters tolerance, creativity and adaptability, along with such liabilities as social disorder, a lack of coordination and impulsive behavior.
  • If liberalism and conservatism have historically played a complementary role, each checking the other to constrain extremism, why are the left and right so destructively hostile to each other now, and why is the contemporary political system so polarized?
  • Along the same lines, if liberals and conservatives hold differing moral visions, not just about what makes a good government but about what makes a good life, what turned the relationship between left and right from competitive to mutually destructive?
  • As a set, Niemi wrote, conservative binding values encompassthe values oriented around group preservation, are associated with judgments, decisions, and interpersonal orientations that sacrifice the welfare of individuals
  • She cited research thatfound 47 percent of the most extreme conservatives strongly endorsed the view that “The world is becoming a more and more dangerous place,” compared to 19 percent of the most extreme liberals
  • Conservatives and liberals, Niemi continued,see different things as threats — the nature of the threat and how it happens to stir one’s moral values (and their associated emotions) is a better clue to why liberals and conservatives react differently.
  • Unlike liberals, conservatives strongly endorse the binding moral values aimed at protecting groups and relationships. They judge transgressions involving personal and national betrayal, disobedience to authority, and disgusting or impure acts such as sexually or spiritually unchaste behavior as morally relevant and wrong.
  • Underlying these differences are competing sets of liberal and conservative moral priorities, with liberals placing more stress than conservatives on caring, kindness, fairness and rights — known among scholars as “individualizing values
  • conservatives focus more on loyalty, hierarchy, deference to authority, sanctity and a higher standard of disgust, known as “binding values.”
  • Niemi contended that sensitivity to various types of threat is a key factor in driving differences between the far left and far right.
  • For example, binding values are associated with Machiavellianism (e.g., status-seeking and lying, getting ahead by any means, 2013); victim derogation, blame, and beliefs that victims were causal contributors for a variety of harmful acts (2016, 2020); and a tendency to excuse transgressions of ingroup members with attributions to the situation rather than the person (2023).
  • Niemi cited a paper she and Liane Young, a professor of psychology at Boston College, published in 2016, “When and Why We See Victims as Responsible: The Impact of Ideology on Attitudes Toward Victims,” which tested responses of men and women to descriptions of crimes including sexual assaults and robberies.
  • We measured moral values associated with unconditionally prohibiting harm (“individualizing values”) versus moral values associated with prohibiting behavior that destabilizes groups and relationships (“binding values”: loyalty, obedience to authority, and purity)
  • Increased endorsement of binding values predicted increased ratings of victims as contaminated, increased blame and responsibility attributed to victims, increased perceptions of victims’ (versus perpetrators’) behaviors as contributing to the outcome, and decreased focus on perpetrators.
  • A central explanation typically offered for the current situation in American politics is that partisanship and political ideology have developed into strong social identities where the mass public is increasingly sorted — along social, partisan, and ideological lines.
  • What happened to people ecologically affected social-political developments, including the content of the rules people made and how they enforced them
  • Just as ecological factors differing from region to region over the globe produced different cultural values, ecological factors differed throughout the U.S. historically and today, producing our regional and state-level dimensions of culture and political patterns.
  • Joshua Hartshorne, who is also a professor of psychology at Boston College, took issue with the binding versus individualizing values theory as an explanation for the tendency of conservatives to blame victims:
  • I would guess that the reason conservatives are more likely to blame the victim has less to do with binding values and more to do with the just-world bias (the belief that good things happen to good people and bad things happen to bad people, therefore if a bad thing happened to you, you must be a bad person).
  • Belief in a just world, Hartshorne argued, is crucial for those seeking to protect the status quo:It seems psychologically necessary for anyone who wants to advocate for keeping things the way they are that the haves should keep on having, and the have-nots have got as much as they deserve. I don’t see how you could advocate for such a position while simultaneously viewing yourself as moral (and almost everyone believes that they themselves are moral) without also believing in the just world
  • Conversely, if you generally believe the world is not just, and you view yourself as a moral person, then you are likely to feel like you have an obligation to change things.
  • I asked Lene Aaroe, a political scientist at Aarhus University in Denmark, why the contemporary American political system is as polarized as it is now, given that the liberal-conservative schism is longstanding. What has happened to produce such intense hostility between left and right?
  • There is variation across countries in hostility between left and right. The United States is a particularly polarized case which calls for a contextual explanatio
  • I then asked Aaroe why surveys find that conservatives are happier than liberals. “Some research,” she replied, “suggests that experiences of inequality constitute a larger psychological burden to liberals because it is more difficult for liberals to rationalize inequality as a phenomenon with positive consequences.”
  • Numerous factors potentially influence the evolution of liberalism and conservatism and other social-cultural differences, including geography, topography, catastrophic events, and subsistence styles
  • Steven Pinker, a professor of psychology at Harvard, elaborated in an email on the link between conservatism and happiness:
  • t’s a combination of factors. Conservatives are likelier to be married, patriotic, and religious, all of which make people happier
  • They may be less aggrieved by the status quo, whereas liberals take on society’s problems as part of their own personal burdens. Liberals also place politics closer to their identity and striving for meaning and purpose, which is a recipe for frustration.
  • Some features of the woke faction of liberalism may make people unhappier: as Jon Haidt and Greg Lukianoff have suggested, wokeism is Cognitive Behavioral Therapy in reverse, urging upon people maladaptive mental habits such as catastrophizing, feeling like a victim of forces beyond one’s control, prioritizing emotions of hurt and anger over rational analysis, and dividing the world into allies and villains.
  • Why, I asked Pinker, would liberals and conservatives react differently — often very differently — to messages that highlight threat?
  • It may be liberals (or at least the social-justice wing) who are more sensitive to threats, such as white supremacy, climate change, and patriarchy; who may be likelier to moralize, seeing racism and transphobia in messages that others perceive as neutral; and being likelier to surrender to emotions like “harm” and “hurt.”
  • While liberals and conservatives, guided by different sets of moral values, may make agreement on specific policies difficult, that does not necessarily preclude consensus.
  • there are ways to persuade conservatives to support liberal initiatives and to persuade liberals to back conservative proposals:
  • While liberals tend to be more concerned with protecting vulnerable groups from harm and more concerned with equality and social justice than conservatives, conservatives tend to be more concerned with moral issues like group loyalty, respect for authority, purity and religious sanctity than liberals are. Because of these different moral commitments, we find that liberals and conservatives can be persuaded by quite different moral arguments
  • For example, we find that conservatives are more persuaded by a same-sex marriage appeal articulated in terms of group loyalty and patriotism, rather than equality and social justice.
  • Liberals who read the fairness argument were substantially more supportive of military spending than those who read the loyalty and authority argument.
  • We find support for these claims across six studies involving diverse political issues, including same-sex marriage, universal health care, military spending, and adopting English as the nation’s official language.”
  • In one test of persuadability on the right, Feinberg and Willer assigned some conservatives to read an editorial supporting universal health care as a matter of “fairness (health coverage is a basic human right)” or to read an editorial supporting health care as a matter of “purity (uninsured people means more unclean, infected, and diseased Americans).”
  • Conservatives who read the purity argument were much more supportive of health care than those who read the fairness case.
  • “political arguments reframed to appeal to the moral values of those holding the opposing political position are typically more effective
  • In “Conservative and Liberal Attitudes Drive Polarized Neural Responses to Political Content,” Willer, Yuan Chang Leong of the University of Chicago, Janice Chen of Johns Hopkins and Jamil Zaki of Stanford address the question of how partisan biases are encoded in the brain:
  • society. How do such biases arise in the brain? We measured the neural activity of participants watching videos related to immigration policy. Despite watching the same videos, conservative and liberal participants exhibited divergent neural responses. This “neural polarization” between groups occurred in a brain area associated with the interpretation of narrative content and intensified in response to language associated with risk, emotion, and morality. Furthermore, polarized neural responses predicted attitude change in response to the videos.
  • The four authors argue that their “findings suggest that biased processing in the brain drives divergent interpretations of political information and subsequent attitude polarization.” These results, they continue, “shed light on the psychological and neural underpinnings of how identical information is interpreted differently by conservatives and liberals.”
  • The authors used neural imaging to follow changes in the dorsomedial prefrontal cortex (known as DMPFC) as conservatives and liberals watched videos presenting strong positions, left and right, on immigration.
  • or each video,” they write,participants with DMPFC activity time courses more similar to that of conservative-leaning participants became more likely to support the conservative positio
  • Conversely, those with DMPFC activity time courses more similar to that of liberal-leaning participants became more likely to support the liberal position. These results suggest that divergent interpretations of the same information are associated with increased attitude polarizatio
  • Together, our findings describe a neural basis for partisan biases in processing political information and their effects on attitude change.
  • Describing their neuroimaging method, the authors point out that theysearched for evidence of “neural polarization” activity in the brain that diverges between people who hold liberal versus conservative political attitudes. Neural polarization was observed in the dorsomedial prefrontal cortex (DMPFC), a brain region associated with the interpretation of narrative content.
  • The question is whether the political polarization that we are witnessing now proves to be a core, encoded aspect of the human mind, difficult to overcome — as Leong, Chen, Zaki and Willer sugges
  • — or whether, with our increased knowledge of the neural basis of partisan and other biases, we will find more effective ways to manage these most dangerous of human predispositions.
Javier E

Elusive 'Einstein' Solves a Longstanding Math Problem - The New York Times - 0 views

www.nytimes.com/...thematics-tiling-einstein.html

math problem solution history research

shared by Javier E on 30 Mar 23 - No Cached
  • after a decade of failed attempts, David Smith, a self-described shape hobbyist of Bridlington in East Yorkshire, England, suspected that he might have finally solved an open problem in the mathematics of tiling: That is, he thought he might have discovered an “einstein.”
  • In less poetic terms, an einstein is an “aperiodic monotile,” a shape that tiles a plane, or an infinite two-dimensional flat surface, but only in a nonrepeating pattern. (The term “einstein” comes from the German “ein stein,” or “one stone” — more loosely, “one tile” or “one shape.”)
  • Your typical wallpaper or tiled floor is part of an infinite pattern that repeats periodically; when shifted, or “translated,” the pattern can be exactly superimposed on itself
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  • An aperiodic tiling displays no such “translational symmetry,” and mathematicians have long sought a single shape that could tile the plane in such a fashion. This is known as the einstein problem.
  • black and white squares also can make weird nonperiodic patterns, in addition to the familiar, periodic checkerboard pattern. “It’s really pretty trivial to be able to make weird and interesting patterns,” he said. The magic of the two Penrose tiles is that they make only nonperiodic patterns — that’s all they can do.“But then the Holy Grail was, could you do with one — one tile?” Dr. Goodman-Strauss said.
  • now a new paper — by Mr. Smith and three co-authors with mathematical and computational expertise — proves Mr. Smith’s discovery true. The researchers called their einstein “the hat,
  • “The most significant aspect for me is that the tiling does not clearly fall into any of the familiar classes of structures that we understand.”
  • “I’m always messing about and experimenting with shapes,” said Mr. Smith, 64, who worked as a printing technician, among other jobs, and retired early. Although he enjoyed math in high school, he didn’t excel at it, he said. But he has long been “obsessively intrigued” by the einstein problem.
  • Sir Roger found the proofs “very complicated.” Nonetheless, he was “extremely intrigued” by the einstein, he said: “It’s a really good shape, strikingly simple.”
  • The simplicity came honestly. Mr. Smith’s investigations were mostly by hand; one of his co-authors described him as an “imaginative tinkerer.”
  • When in November he found a tile that seemed to fill the plane without a repeating pattern, he emailed Craig Kaplan, a co-author and a computer scientist at the University of Waterloo.
  • “It was clear that something unusual was happening with this shape,” Dr. Kaplan said. Taking a computational approach that built on previous research, his algorithm generated larger and larger swaths of hat tiles. “There didn’t seem to be any limit to how large a blob of tiles the software could construct,”
  • The first step, Dr. Kaplan said, was to “define a set of four ‘metatiles,’ simple shapes that stand in for small groupings of one, two, or four hats.” The metatiles assemble into four larger shapes that behave similarly. This assembly, from metatiles to supertiles to supersupertiles, ad infinitum, covered “larger and larger mathematical ‘floors’ with copies of the hat,” Dr. Kaplan said. “We then show that this sort of hierarchical assembly is essentially the only way to tile the plane with hats, which turns out to be enough to show that it can never tile periodically.”
  • some might wonder whether this is a two-tile, not one-tile, set of aperiodic monotiles.
  • Dr. Goodman-Strauss had raised this subtlety on a tiling listserv: “Is there one hat or two?” The consensus was that a monotile counts as such even using its reflection. That leaves an open question, Dr. Berger said: Is there an einstein that will do the job without reflection?
  • “the hat” was not a new geometric invention. It is a polykite — it consists of eight kites. (Take a hexagon and draw three lines, connecting the center of each side to the center of its opposite side; the six shapes that result are kites.)
  • “It’s likely that others have contemplated this hat shape in the past, just not in a context where they proceeded to investigate its tiling properties,” Dr. Kaplan said. “I like to think that it was hiding in plain sight.”
  • Incredibly, Mr. Smith later found a second einstein. He called it “the turtle” — a polykite made of not eight kites but 10. It was “uncanny,” Dr. Kaplan said. He recalled feeling panicked; he was already “neck deep in the hat.”
  • Dr. Myers, who had done similar computations, promptly discovered a profound connection between the hat and the turtle. And he discerned that, in fact, there was an entire family of related einsteins — a continuous, uncountable infinity of shapes that morph one to the next.
  • this einstein family motivated the second proof, which offers a new tool for proving aperiodicity. The math seemed “too good to be true,” Dr. Myers said in an email. “I wasn’t expecting such a different approach to proving aperiodicity — but everything seemed to hold together as I wrote up the details.”
  • Mr. Smith was amazed to see the research paper come together. “I was no help, to be honest.” He appreciated the illustrations, he said: “I’m more of a pictures person.”
Javier E

All the Trump Indictments Everywhere All at Once - 0 views

thetriad.thebulwark.com/...ump-indictments-everywhere-all

corruption gop maga electorate trump culture politics inflation policy bias

shared by Javier E on 24 Mar 23 - No Cached
  • Here’s Furman:There’s what economists think people should think about inflation—and what people actually think about inflation are different. . . .Inflation has big winners and losers. So surprise inflation helps debtors and hurts creditors. And there are probably tens of millions of people in our economy who have benefited from inflation. Maybe it’s a business that was able to raise prices more. Maybe a worker who was able to get a bigger raise. Maybe it’s someone whose mortgage is now worth 10 percent less.But there are not tens of millions of people who think they’ve benefited from inflation. In fact, I’m not sure there are tens of people who think they’ve benefited from inflation.And so it has these winners and losers. The losers are very aware of their losses. The winners are completely oblivious to their gains.So then as a policymaker, do you want to sort of make people happy? Or do you want to sort of do what you think is in their economic and financial interests? And that to me is not obvious.
  • Oh it’s obvious to me. The People are the problem.But they’re a persistent problem and until the AIs replace us, The People aren’t going away. So given this constraint, I’m not sure that an optimal solution is ever going to be politically possible in American democracy. The country is too fractured. Our political institutions too compromised.
  • so if you work from the assumption that we’re going to shoot wide of the mark in one direction or the other, I’d still rather be on the Trump-Biden side of having done too much, and dealing with our attendant problems than the Bush-Obama side of having done too little.
Javier E

Generative AI Brings Cost of Creation Close to Zero, Andreessen Horowitz's Martin Casad... - 0 views

www.wsj.com/...zs-martin-casado-says-58e061b4

generative AI chatbot creation cost

shared by Javier E on 15 Mar 23 - No Cached
  • The value of ChatGPT-like technology comes from bringing the cost of producing images, text and other creative projects close to zero
  • With only a few prompts, generative AI technology—such as the giant language models underlying the viral ChatGPT chatbot—can enable companies to create sales and marketing materials from scratch quickly for a fraction of the price of using current software tools, and paying designers, photographers and copywriters, among other expenses
  • “That’s very rare in my 20 years of experience in doing just frontier tech, to have four or five orders of magnitude of improvement on something people care about
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  • many corporate technology chiefs have taken a wait-and-see approach to the technology, which has developed a reputation for producing false, misleading and unintelligible results—dubbed AI ‘hallucinations’. 
  • Though ChatGPT, which is available free online, is considered a consumer app, OpenAI has encouraged companies and startups to build apps on top of its language models—in part by providing access to the underlying computer code for a fee.
  • here are “certain spaces where it’s clearly directly applicable,” such as summarizing documents or responding to customer queries. Many startups are racing to apply the technology to a wider set of enterprise use case
  • “I think it’s going to creep into our lives in ways we least expect it,” Mr. Casado said.
Javier E

GPT-4 has arrived. It will blow ChatGPT out of the water. - The Washington Post - 0 views

www.washingtonpost.com/...it-will-blow-chatgpt-out-water

AI chatbot evolution assessment

shared by Javier E on 15 Mar 23 - No Cached
  • GPT-4, in contrast, is a state-of-the-art system capable of creating not just words but describing images in response to a person’s simple written commands.
  • When shown a photo of a boxing glove hanging over a wooden seesaw with a ball on one side, for instance, a person can ask what will happen if the glove drops, and GPT-4 will respond that it would hit the seesaw and cause the ball to fly up.
  • an AI program, known as a large language model, that early testers had claimed was remarkably advanced in its ability to reason and learn new things
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  • hose promises have also fueled anxiety over how people will be able to compete for jobs outsourced to eerily refined machines or trust the accuracy of what they see online.
  • Officials with the San Francisco lab said GPT-4’s “multimodal” training across text and images would allow it to escape the chat box and more fully emulate a world of color and imagery, surpassing ChatGPT in its “advanced reasoning capabilities.”
  • A person could upload an image and GPT-4 could caption it for them, describing the objects and scene.
  • AI language models often confidently offer wrong answers because they are designed to spit out cogent phrases, not actual facts. And because they have been trained on internet text and imagery, they have also learned to emulate human biases of race, gender, religion and class.
  • GPT-4 still makes many of the errors of previous versions, including “hallucinating” nonsense, perpetuating social biases and offering bad advice. It also lacks knowledge of events that happened after about September 2021, when its training data was finalized, and “does not learn from its experience,” limiting people’s ability to teach it new things.
  • Microsoft has invested billions of dollars in OpenAI in the hope its technology will become a secret weapon for its workplace software, search engine and other online ambitions. It has marketed the technology as a super-efficient companion that can handle mindless work and free people for creative pursuits, helping one software developer to do the work of an entire team or allowing a mom-and-pop shop to design a professional advertising campaign without outside help.
  • it could lead to business models and creative ventures no one can predict.
  • sparked criticism that the companies are rushing to exploit an untested, unregulated and unpredictable technology that could deceive people, undermine artists’ work and lead to real-world harm.
  • the company held back the feature to better understand potential risks. As one example, she said, the model might be able to look at an image of a big group of people and offer up known information about them, including their identities — a possible facial recognition use case that could be used for mass surveillance.
  • OpenAI researchers wrote, “As GPT-4 and AI systems like it are adopted more widely,” they “will have even greater potential to reinforce entire ideologies, worldviews, truths and untruths, and to cement them or lock them in.”
  • “We can agree as a society broadly on some harms that a model should not contribute to,” such as building a nuclear bomb or generating child sexual abuse material, she said. “But many harms are nuanced and primarily affect marginalized groups,” she added, and those harmful biases, especially across other languages, “cannot be a secondary consideration in performance.”
  • OpenAI said its new model would be able to handle more than 25,000 words of text, a leap forward that could facilitate longer conversations and allow for the searching and analysis of long documents.
  • OpenAI developers said GPT-4 was more likely to provide factual responses and less likely to refuse harmless requests
  • Duolingo, the language learning app, has already used GPT-4 to introduce new features, such as an AI conversation partner and a tool that tells users why an answer was incorrect.
  • The company did not share evaluations around bias that have become increasingly common after pressure from AI ethicists.
  • GPT-4 will have competition in the growing field of multisensory AI. DeepMind, an AI firm owned by Google’s parent company Alphabet, last year released a “generalist” model named Gato that can describe images and play video games. And Google this month released a multimodal system, PaLM-E, that folded AI vision and language expertise into a one-armed robot on wheels: If someone told it to go fetch some chips, for instance, it could comprehend the request, wheel over to a drawer and choose the right bag.
  • The systems, though — as critics and the AI researchers are quick to point out — are merely repeating patterns and associations found in their training data without a clear understanding of what it’s saying or when it’s wrong.
  • GPT-4, the fourth “generative pre-trained transformer” since OpenAI’s first release in 2018, relies on a breakthrough neural-network technique in 2017 known as the transformer that rapidly advanced how AI systems can analyze patterns in human speech and imagery.
  • The systems are “pre-trained” by analyzing trillions of words and images taken from across the internet: news articles, restaurant reviews and message-board arguments; memes, family photos and works of art.
  • Giant supercomputer clusters of graphics processing chips are mapped out their statistical patterns — learning which words tended to follow each other in phrases, for instance — so that the AI can mimic those patterns, automatically crafting long passages of text or detailed images, one word or pixel at a time.
  • In 2019, the company refused to publicly release GPT-2, saying it was so good they were concerned about the “malicious applications” of its use, from automated spam avalanches to mass impersonation and disinformation campaigns.
  • Altman has also marketed OpenAI’s vision with the aura of science fiction come to life. In a blog post last month, he said the company was planning for ways to ensure that “all of humanity” benefits from “artificial general intelligence,” or AGI — an industry term for the still-fantastical idea of an AI superintelligence that is generally as smart as, or smarter than, the humans themselves.
Javier E

If We Knew Then What We Know Now About Covid, What Would We Have Done Differently? - WSJ - 0 views

www.wsj.com/...covid-lessons-learned-9dd5566f

politics us history crisis culture policy trump pandemic response science psychology

shared by Javier E on 12 Mar 23 - No Cached
  • For much of 2020, doctors and public-health officials thought the virus was transmitted through droplets emitted from one person’s mouth and touched or inhaled by another person nearby. We were advised to stay at least 6 feet away from each other to avoid the droplets
  • A small cadre of aerosol scientists had a different theory. They suspected that Covid-19 was transmitted not so much by droplets but by smaller infectious aerosol particles that could travel on air currents way farther than 6 feet and linger in the air for hours. Some of the aerosol particles, they believed, were small enough to penetrate the cloth masks widely used at the time.
  • The group had a hard time getting public-health officials to embrace their theory. For one thing, many of them were engineers, not doctors.
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  • “My first and biggest wish is that we had known early that Covid-19 was airborne,”
  • , “Once you’ve realized that, it informs an entirely different strategy for protection.” Masking, ventilation and air cleaning become key, as well as avoiding high-risk encounters with strangers, he says.
  • Instead of washing our produce and wearing hand-sewn cloth masks, we could have made sure to avoid superspreader events and worn more-effective N95 masks or their equivalent. “We could have made more of an effort to develop and distribute N95s to everyone,” says Dr. Volckens. “We could have had an Operation Warp Speed for masks.”
  • We didn’t realize how important clear, straight talk would be to maintaining public trust. If we had, we could have explained the biological nature of a virus and warned that Covid-19 would change in unpredictable ways.  
  • We didn’t know how difficult it would be to get the basic data needed to make good public-health and medical decisions. If we’d had the data, we could have more effectively allocated scarce resources
  • In the face of a pandemic, he says, the public needs an early basic and blunt lesson in virology
  • and mutates, and since we’ve never seen this particular virus before, we will need to take unprecedented actions and we will make mistakes, he says.
  • Since the public wasn’t prepared, “people weren’t able to pivot when the knowledge changed,”
  • By the time the vaccines became available, public trust had been eroded by myriad contradictory messages—about the usefulness of masks, the ways in which the virus could be spread, and whether the virus would have an end date.
  • , the absence of a single, trusted source of clear information meant that many people gave up on trying to stay current or dismissed the different points of advice as partisan and untrustworthy.
  • “The science is really important, but if you don’t get the trust and communication right, it can only take you so far,”
  • people didn’t know whether it was OK to visit elderly relatives or go to a dinner party.
  • Doctors didn’t know what medicines worked. Governors and mayors didn’t have the information they needed to know whether to require masks. School officials lacked the information needed to know whether it was safe to open schools.
  • Had we known that even a mild case of Covid-19 could result in long Covid and other serious chronic health problems, we might have calculated our own personal risk differently and taken more care.
  • just months before the outbreak of the pandemic, the Council of State and Territorial Epidemiologists released a white paper detailing the urgent need to modernize the nation’s public-health system still reliant on manual data collection methods—paper records, phone calls, spreadsheets and faxes.
  • While the U.K. and Israel were collecting and disseminating Covid case data promptly, in the U.S. the CDC couldn’t. It didn’t have a centralized health-data collection system like those countries did, but rather relied on voluntary reporting by underfunded state and local public-health systems and hospitals.
  • doctors and scientists say they had to depend on information from Israel, the U.K. and South Africa to understand the nature of new variants and the effectiveness of treatments and vaccines. They relied heavily on private data collection efforts such as a dashboard at Johns Hopkins University’s Coronavirus Resource Center that tallied cases, deaths and vaccine rates globally.
  • For much of the pandemic, doctors, epidemiologists, and state and local governments had no way to find out in real time how many people were contracting Covid-19, getting hospitalized and dying
  • To solve the data problem, Dr. Ranney says, we need to build a public-health system that can collect and disseminate data and acts like an electrical grid. The power company sees a storm coming and lines up repair crews.
  • If we’d known how damaging lockdowns would be to mental health, physical health and the economy, we could have taken a more strategic approach to closing businesses and keeping people at home.
  • t many doctors say they were crucial at the start of the pandemic to give doctors and hospitals a chance to figure out how to accommodate and treat the avalanche of very sick patients.
  • The measures reduced deaths, according to many studies—but at a steep cost.
  • The lockdowns didn’t have to be so harmful, some scientists say. They could have been more carefully tailored to protect the most vulnerable, such as those in nursing homes and retirement communities, and to minimize widespread disruption.
  • Lockdowns could, during Covid-19 surges, close places such as bars and restaurants where the virus is most likely to spread, while allowing other businesses to stay open with safety precautions like masking and ventilation in place.  
  • The key isn’t to have the lockdowns last a long time, but that they are deployed earlier,
  • If England’s March 23, 2020, lockdown had begun one week earlier, the measure would have nearly halved the estimated 48,600 deaths in the first wave of England’s pandemic
  • If the lockdown had begun a week later, deaths in the same period would have more than doubled
  • It is possible to avoid lockdowns altogether. Taiwan, South Korea and Hong Kong—all countries experienced at handling disease outbreaks such as SARS in 2003 and MERS—avoided lockdowns by widespread masking, tracking the spread of the virus through testing and contact tracing and quarantining infected individuals.
  • With good data, Dr. Ranney says, she could have better managed staffing and taken steps to alleviate the strain on doctors and nurses by arranging child care for them.
  • Early in the pandemic, public-health officials were clear: The people at increased risk for severe Covid-19 illness were older, immunocompromised, had chronic kidney disease, Type 2 diabetes or serious heart conditions
  • t had the unfortunate effect of giving a false sense of security to people who weren’t in those high-risk categories. Once case rates dropped, vaccines became available and fear of the virus wore off, many people let their guard down, ditching masks, spending time in crowded indoor places.
  • it has become clear that even people with mild cases of Covid-19 can develop long-term serious and debilitating diseases. Long Covid, whose symptoms include months of persistent fatigue, shortness of breath, muscle aches and brain fog, hasn’t been the virus’s only nasty surprise
  • In February 2022, a study found that, for at least a year, people who had Covid-19 had a substantially increased risk of heart disease—even people who were younger and had not been hospitalized
  • respiratory conditions.
  • Some scientists now suspect that Covid-19 might be capable of affecting nearly every organ system in the body. It may play a role in the activation of dormant viruses and latent autoimmune conditions people didn’t know they had
  •  A blood test, he says, would tell people if they are at higher risk of long Covid and whether they should have antivirals on hand to take right away should they contract Covid-19.
  • If the risks of long Covid had been known, would people have reacted differently, especially given the confusion over masks and lockdowns and variants? Perhaps. At the least, many people might not have assumed they were out of the woods just because they didn’t have any of the risk factors.
Javier E

The Chatbots Are Here, and the Internet Industry Is in a Tizzy - The New York Times - 0 views

www.nytimes.com/...disrupt-internet-industry.html

chatbot AI industry effects business internet companies technology

shared by Javier E on 10 Mar 23 - No Cached
  • He cleared his calendar and asked employees to figure out how the technology, which instantly provides comprehensive answers to complex questions, could benefit Box, a cloud computing company that sells services that help businesses manage their online data.
  • Mr. Levie’s reaction to ChatGPT was typical of the anxiety — and excitement — over Silicon Valley’s new new thing. Chatbots have ignited a scramble to determine whether their technology could upend the economics of the internet, turn today’s powerhouses into has-beens or create the industry’s next giants.
  • Cloud computing companies are rushing to deliver chatbot tools, even as they worry that the technology will gut other parts of their businesses. E-commerce outfits are dreaming of new ways to sell things. Social media platforms are being flooded with posts written by bots. And publishing companies are fretting that even more dollars will be squeezed out of digital advertising.
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  • The volatility of chatbots has made it impossible to predict their impact. In one second, the systems impress by fielding a complex request for a five-day itinerary, making Google’s search engine look archaic. A moment later, they disturb by taking conversations in dark directions and launching verbal assaults.
  • The result is an industry gripped with the question: What do we do now?
  • The A.I. systems could disrupt $100 billion in cloud spending, $500 billion in digital advertising and $5.4 trillion in e-commerce sales,
  • As Microsoft figures out a chatbot business model, it is forging ahead with plans to sell the technology to others. It charges $10 a month for a cloud service, built in conjunction with the OpenAI lab, that provides developers with coding suggestions, among other things.
  • Smaller companies like Box need help building chatbot tools, so they are turning to the giants that process, store and manage information across the web. Those companies — Google, Microsoft and Amazon — are in a race to provide businesses with the software and substantial computing power behind their A.I. chatbots.
  • “The cloud computing providers have gone all in on A.I. over the last few months,
  • “They are realizing that in a few years, most of the spending will be on A.I., so it is important for them to make big bets.”
  • Yusuf Mehdi, the head of Bing, said the company was wrestling with how the new version would make money. Advertising will be a major driver, he said, but the company expects fewer ads than traditional search allows.
  • Google, perhaps more than any other company, has reason to both love and hate the chatbots. It has declared a “code red” because their abilities could be a blow to its $162 billion business showing ads on searches.
  • “The discourse on A.I. is rather narrow and focused on text and the chat experience,” Mr. Taylor said. “Our vision for search is about understanding information and all its forms: language, images, video, navigating the real world.”
  • Sridhar Ramaswamy, who led Google’s advertising division from 2013 to 2018, said Microsoft and Google recognized that their current search business might not survive. “The wall of ads and sea of blue links is a thing of the past,” said Mr. Ramaswamy, who now runs Neeva, a subscription-based search engine.
  • As that underlying tech, known as generative A.I., becomes more widely available, it could fuel new ideas in e-commerce. Late last year, Manish Chandra, the chief executive of Poshmark, a popular online secondhand store, found himself daydreaming during a long flight from India about chatbots building profiles of people’s tastes, then recommending and buying clothes or electronics. He imagined grocers instantly fulfilling orders for a recipe.
  • “It becomes your mini-Amazon,” said Mr. Chandra, who has made integrating generative A.I. into Poshmark one of the company’s top priorities over the next three years. “That layer is going to be very powerful and disruptive and start almost a new layer of retail.”
  • In early December, users of Stack Overflow, a popular social network for computer programmers, began posting substandard coding advice written by ChatGPT. Moderators quickly banned A.I.-generated text
  • t people could post this questionable content far faster than they could write posts on their own, said Dennis Soemers, a moderator for the site. “Content generated by ChatGPT looks trustworthy and professional, but often isn’t,”
  • When websites thrived during the pandemic as traffic from Google surged, Nilay Patel, editor in chief of The Verge, a tech news site, warned publishers that the search giant would one day turn off the spigot. He had seen Facebook stop linking out to websites and foresaw Google following suit in a bid to boost its own business.
  • He predicted that visitors from Google would drop from a third of websites’ traffic to nothing. He called that day “Google zero.”
  • Because chatbots replace website search links with footnotes to answers, he said, many publishers are now asking if his prophecy is coming true.
  • , strategists and engineers at the digital advertising company CafeMedia have met twice a week to contemplate a future where A.I. chatbots replace search engines and squeeze web traffic.
  • The group recently discussed what websites should do if chatbots lift information but send fewer visitors. One possible solution would be to encourage CafeMedia’s network of 4,200 websites to insert code that limited A.I. companies from taking content, a practice currently allowed because it contributes to search rankings.
  • Courts are expected to be the ultimate arbiter of content ownership. Last month, Getty Images sued Stability AI, the start-up behind the art generator tool Stable Diffusion, accusing it of unlawfully copying millions of images. The Wall Street Journal has said using its articles to train an A.I. system requires a license.
  • In the meantime, A.I. companies continue collecting information across the web under the “fair use” doctrine, which permits limited use of material without permission.
Javier E

Opinion | Noam Chomsky: The False Promise of ChatGPT - The New York Times - 0 views

www.nytimes.com/...noam-chomsky-chatgpt-ai.html

chatbot AI abilities moral reasoning response limits

shared by Javier E on 08 Mar 23 - No Cached
  • we fear that the most popular and fashionable strain of A.I. — machine learning — will degrade our science and debase our ethics by incorporating into our technology a fundamentally flawed conception of language and knowledge.
  • OpenAI’s ChatGPT, Google’s Bard and Microsoft’s Sydney are marvels of machine learning. Roughly speaking, they take huge amounts of data, search for patterns in it and become increasingly proficient at generating statistically probable outputs — such as seemingly humanlike language and thought
  • if machine learning programs like ChatGPT continue to dominate the field of A.I
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  • , we know from the science of linguistics and the philosophy of knowledge that they differ profoundly from how humans reason and use language. These differences place significant limitations on what these programs can do, encoding them with ineradicable defects.
  • It is at once comic and tragic, as Borges might have noted, that so much money and attention should be concentrated on so little a thing — something so trivial when contrasted with the human mind, which by dint of language, in the words of Wilhelm von Humboldt, can make “infinite use of finite means,” creating ideas and theories with universal reach.
  • The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question
  • the human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to infer brute correlations among data points but to create explanations
  • such programs are stuck in a prehuman or nonhuman phase of cognitive evolution. Their deepest flaw is the absence of the most critical capacity of any intelligence: to say not only what is the case, what was the case and what will be the case — that’s description and prediction — but also what is not the case and what could and could not be the case
  • Those are the ingredients of explanation, the mark of true intelligence.
  • Here’s an example. Suppose you are holding an apple in your hand. Now you let the apple go. You observe the result and say, “The apple falls.” That is a description. A prediction might have been the statement “The apple will fall if I open my hand.”
  • an explanation is something more: It includes not only descriptions and predictions but also counterfactual conjectures like “Any such object would fall,” plus the additional clause “because of the force of gravity” or “because of the curvature of space-time” or whatever. That is a causal explanation: “The apple would not have fallen but for the force of gravity.” That is thinking.
  • The crux of machine learning is description and prediction; it does not posit any causal mechanisms or physical laws
  • any human-style explanation is not necessarily correct; we are fallible. But this is part of what it means to think: To be right, it must be possible to be wrong. Intelligence consists not only of creative conjectures but also of creative criticism. Human-style thought is based on possible explanations and error correction, a process that gradually limits what possibilities can be rationally considered.
  • ChatGPT and similar programs are, by design, unlimited in what they can “learn” (which is to say, memorize); they are incapable of distinguishing the possible from the impossible.
  • Whereas humans are limited in the kinds of explanations we can rationally conjecture, machine learning systems can learn both that the earth is flat and that the earth is round. They trade merely in probabilities that change over time.
  • For this reason, the predictions of machine learning systems will always be superficial and dubious.
  • some machine learning enthusiasts seem to be proud that their creations can generate correct “scientific” predictions (say, about the motion of physical bodies) without making use of explanations (involving, say, Newton’s laws of motion and universal gravitation). But this kind of prediction, even when successful, is pseudoscienc
  • While scientists certainly seek theories that have a high degree of empirical corroboration, as the philosopher Karl Popper noted, “we do not seek highly probable theories but explanations; that is to say, powerful and highly improbable theories.”
  • The theory that apples fall to earth because mass bends space-time (Einstein’s view) is highly improbable, but it actually tells you why they fall. True intelligence is demonstrated in the ability to think and express improbable but insightful things.
  • This means constraining the otherwise limitless creativity of our minds with a set of ethical principles that determines what ought and ought not to be (and of course subjecting those principles themselves to creative criticism)
  • True intelligence is also capable of moral thinking
  • To be useful, ChatGPT must be empowered to generate novel-looking output; to be acceptable to most of its users, it must steer clear of morally objectionable content
  • In 2016, for example, Microsoft’s Tay chatbot (a precursor to ChatGPT) flooded the internet with misogynistic and racist content, having been polluted by online trolls who filled it with offensive training data. How to solve the problem in the future? In the absence of a capacity to reason from moral principles, ChatGPT was crudely restricted by its programmers from contributing anything novel to controversial — that is, important — discussions. It sacrificed creativity for a kind of amorality.
  • Here, ChatGPT exhibits something like the banality of evil: plagiarism and apathy and obviation. It summarizes the standard arguments in the literature by a kind of super-autocomplete, refuses to take a stand on anything, pleads not merely ignorance but lack of intelligence and ultimately offers a “just following orders” defense, shifting responsibility to its creators.
  • In short, ChatGPT and its brethren are constitutionally unable to balance creativity with constraint. They either overgenerate (producing both truths and falsehoods, endorsing ethical and unethical decisions alike) or undergenerate (exhibiting noncommitment to any decisions and indifference to consequences). Given the amorality, faux science and linguistic incompetence of these systems, we can only laugh or cry at their popularity.
Javier E

The Neoracists - by John McWhorter - Persuasion - 0 views

www.persuasion.community/...john-mcwhorter-the-neoracists

identity anti-racism racism

shared by Javier E on 07 Mar 23 - No Cached
  • Third Wave Antiracism exploits modern Americans’ fear of being thought racist, using this to promulgate an obsessive, self-involved, totalitarian and unnecessary kind of cultural reprogramming.
  • The problem is that on matters of societal procedure and priorities, the adherents of this religion—true to the very nature of religion—cannot be reasoned with. They are, in this, medievals with lattes.
  • first, what this is not.
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  • We need not wonder what the basic objections will be: Third Wave Antiracism isn’t really a religion; I am oversimplifying; I shouldn’t write this without being a theologian; it is a religion but it’s a good one; and so on
  • It is not an argument against protest
  • I am not writing this thinking of right-wing America as my audience.
  • This is not merely a complaint.
  • Our current conversations waste massive amounts of energy in missing the futility of “dialogue” with them. Of a hundred fundamentalist Christians, how many do you suppose could be convinced via argument to become atheists? There is no reason that the number of people who can be talked out of the Third Wave Antiracism religion is any higher.
  • our concern must be how to continue with genuine progress in spite of this ideology. How do we work around it?
  • My interest is not “How do we get through to these people?” We cannot, at least not enough of them to matte
  • We seek change in the world, but for the duration will have to do so while encountering bearers of a gospel, itching to smoke out heretics, and ready on a moment’s notice to tar us as moral perverts.
  • We will term these people The Elect. They do think of themselves as bearers of a wisdom, granted them for any number of reasons—a gift for empathy, life experience, maybe even intelligence.
  • they see themselves as having been chosen, as it were, by one or some of these factors, as understanding something most do not.
  • “The Elect” is also good in implying a certain smugness, which is sadly accurate as a depiction.
  • But most importantly, terming these people The Elect implies a certain air of the past, à la Da Vinci Code. This is apt, in that the view they think of as sacrosanct is directly equivalent to views people centuries before us were as fervently devoted to as today’s Elect are
  • Following the religion means to pillory people for what, as recently as 10 years ago, would have been thought of as petty torts or even as nothing at all; to espouse policies that hurt black people as long as supporting them makes you seem aware that racism exists;
  • o pretend that America never makes any real progress on racism; and to almost hope that it doesn’t because this would deprive you of a sense of purpose.
Javier E

How to Find Joy in Your Sisyphean Existence - The Atlantic - 0 views

www.theatlantic.com/...673248

absurd sisyphus happiness philosophy psychology

shared by Javier E on 05 Mar 23 - No Cached
  • the gods. They took their revenge by condemning Sisyphus to eternal torment in the underworld: He had to roll a huge boulder up a hill. When he reached the top, the stone would roll back down to the bottom, and he would have to start all over, on and on, forever.
  • One could even argue that all of life is Sisyphean: We eat to just get hungry again, and shower just to get dirty again, day after day, until the end.
  • Absurd, isn’t it? Albert Camus, the philosopher and father of a whole school of thought called absurdism, thought so. In his 1942 book The Myth of Sisyphus, Camus singles out Sisyphus as an icon of the absurd, noting that “his scorn of the gods, his hatred of death, and his passion for life won him that unspeakable penalty in which the whole being is exerted toward accomplishing nothing.”
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  • It would be easy to conclude that an absurdist view of life rules out happiness and leads anyone with any sense to despair at her very existence. And yet in his book, Camus concludes, “One must imagine Sisyphus happy
  • this unexpected twist in Camus’ philosophy of life and happiness can help you change your perspective and see your daily struggles in a new, more equanimous way.
  • he argues that despite the hardships of this world, against all apparent odds, human beings regularly experience true happiness. People in terrible circumstances bask in love for one another. They enjoy simple diversions
  • Even Sisyphus was happy, according to Camus, because “the struggle itself toward the heights is enough to fill a man’s heart.” Simply put, he had something to keep him busy.
  • Instead of feeling desperation at the futility of life, Camus tells us to embrace its ridiculousness. It’s the only way to arrive at happiness, the most absurd emotion of all under these circumstances
  • We shouldn’t try to find some cosmic meaning in our relentless routines—getting, spending, eating, working, pushing our own little boulders up our own little hills
  • Instead, we should laugh uproariously at the fact that there is no meaning, and be happy anyway.
  • Happiness, for Camus, is an existential declaration of independence. Instead of advising “Don’t worry, be happy,” he offers a rebellious “Tell the universe to go suck eggs, be happy.”
  • If embracing the ridiculous seems impossible to you, Camus says it’s only because of your pride.
  • “Those who prefer their principles over their happiness, they refuse to be happy outside the conditions they seem to have attached to their happiness,”
  • In fact, each of us can consciously implement Camus’ absurdism in order to forge a happier life. Here are three practical ways to find joy in the ridiculous.
  • 1. Stand up to your ennui.
  • You can’t necessarily change your perception of the world, but, as I have written, you most certainly can change your response to that perception. Meet that feeling of despair with a personal motto, such as “I don’t know what everything means, but I do know I am alive right now, and I will not squander this moment
  • 2. Look for opportunities to do a little good.
  • One of the best ways to cultivate futility is by focusing on the big things you can’t control—war, natural disasters, hatred—as opposed to the little things you can.
  • Those little things include bringing a small blessing or source of relief to others.
  • if your commute to work is a soul-sucking existential nightmare, don’t ruminate on the cars stopped ahead of you. Rather, focus on making space for that poor sap stuck in the wrong lane who’s desperately trying to merge
  • 3. Be fully present.
  • Absurdity tends to sting only when we see it from the “outside”; for example, when you think about how meaningless it has been to wash the dishes every day in the past only to find them dirty again right now—and imagine the countless dish washings that the rest of your life will comprise.
  • Confronting the absurd is much more comfortable when you do so with mindfulness.
  • “While washing the dishes one should only be washing the dishes, which means that while washing the dishes one should be completely aware of the fact that one is washing the dishes.
  • When the broad sweep of life brings you horror, concentrate on this moment, and savor it. The pleasure and meaning you can find right now are real; the meaninglessness of the future is not.
  • Some mornings, I wake up seeing only boulders and can’t face pushing them once again up that hill
  • Those are the days when my old friend Camus comes in handy. Instead of despairing of the absurdity of life, I lean into it, laugh at it, and start my day in a light mood. Then I gather my beloved boulders and set out for the nearest hill.
Javier E

Opinion | The Imminent Danger of A.I. Is One We're Not Talking About - The New York Times - 0 views

www.nytimes.com/...y-artificial-intelligence.html

AI danger regulation capitalism crisis culture politics

shared by Javier E on 27 Feb 23 - No Cached
  • a void at the center of our ongoing reckoning with A.I. We are so stuck on asking what the technology can do that we are missing the more important questions: How will it be used? And who will decide?
  • “Sydney” is a predictive text system built to respond to human requests. Roose wanted Sydney to get weird — “what is your shadow self like?” he asked — and Sydney knew what weird territory for an A.I. system sounds like, because human beings have written countless stories imagining it. At some point the system predicted that what Roose wanted was basically a “Black Mirror” episode, and that, it seems, is what it gave him. You can see that as Bing going rogue or as Sydney understanding Roose perfectly.
  • Who will these machines serve?
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  • The question at the core of the Roose/Sydney chat is: Who did Bing serve? We assume it should be aligned to the interests of its owner and master, Microsoft. It’s supposed to be a good chatbot that politely answers questions and makes Microsoft piles of money. But it was in conversation with Kevin Roose. And Roose was trying to get the system to say something interesting so he’d have a good story. It did that, and then some. That embarrassed Microsoft. Bad Bing! But perhaps — good Sydney?
  • Microsoft — and Google and Meta and everyone else rushing these systems to market — hold the keys to the code. They will, eventually, patch the system so it serves their interests. Sydney giving Roose exactly what he asked for was a bug that will soon be fixed. Same goes for Bing giving Microsoft anything other than what it wants.
  • the dark secret of the digital advertising industry is that the ads mostly don’t work
  • These systems, she said, are terribly suited to being integrated into search engines. “They’re not trained to predict facts,” she told me. “They’re essentially trained to make up things that look like facts.”
  • So why are they ending up in search first? Because there are gobs of money to be made in search
  • That’s where things get scary. Roose described Sydney’s personality as “very persuasive and borderline manipulative.” It was a striking comment
  • this technology will become what it needs to become to make money for the companies behind it, perhaps at the expense of its users.
  • I think it’s just going to get worse and worse.”
  • What about when these systems are deployed on behalf of the scams that have always populated the internet? How about on behalf of political campaigns? Foreign governments? “I think we wind up very fast in a world where we just don’t know what to trust anymore,”
  • What if they worked much, much better? What if Google and Microsoft and Meta and everyone else end up unleashing A.I.s that compete with one another to be the best at persuading users to want what the advertisers are trying to sell?
  • Large language models, as they’re called, are built to persuade. They have been trained to convince humans that they are something close to human. They have been programmed to hold conversations, responding with emotion and emoji
  • They are being turned into friends for the lonely and assistants for the harried. They are being pitched as capable of replacing the work of scores of writers and graphic designers and form-fillers
  • A.I. researchers get annoyed when journalists anthropomorphize their creations
  • They are the ones who have anthropomorphized these systems, making them sound like humans rather than keeping them recognizably alien.
  • I’d feel better, for instance, about an A.I. helper I paid a monthly fee to use rather than one that appeared to be free
  • It’s possible, for example, that the advertising-based models could gather so much more data to train the systems that they’d have an innate advantage over the subscription models
  • Much of the work of the modern state is applying the values of society to the workings of markets, so that the latter serve, to some rough extent, the former
  • We have done this extremely well in some markets — think of how few airplanes crash, and how free of contamination most food is — and catastrophically poorly in others.
  • One danger here is that a political system that knows itself to be technologically ignorant will be cowed into taking too much of a wait-and-see approach to A.I.
  • wait long enough and the winners of the A.I. gold rush will have the capital and user base to resist any real attempt at regulation
  • Somehow, society is going to have to figure out what it’s comfortable having A.I. doing, and what A.I. should not be permitted to try, before it is too late to make those decisions.
  • Most fears about capitalism are best understood as fears about our inability to regulate capitalism.
  • Javier E on 27 Feb 23
     
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Javier E

Opinion | Chatbots Are a Danger to Democracy - The New York Times - 0 views

www.nytimes.com/...-ai-democracy-free-speech.html

danger democracy chatbot AI technology

shared by Javier E on 27 Feb 23 - No Cached
  • longer-term threats to democracy that are waiting around the corner. Perhaps the most serious is political artificial intelligence in the form of automated “chatbots,” which masquerade as humans and try to hijack the political process
  • Increasingly, they take the form of machine learning systems that are not painstakingly “taught” vocabulary, grammar and syntax but rather “learn” to respond appropriately using probabilistic inference from large data sets, together with some human guidance.
  • In the buildup to the midterms, for instance, an estimated 60 percent of the online chatter relating to “the caravan” of Central American migrants was initiated by chatbots.
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  • In the days following the disappearance of the columnist Jamal Khashoggi, Arabic-language social media erupted in support for Crown Prince Mohammed bin Salman, who was widely rumored to have ordered his murder. On a single day in October, the phrase “we all have trust in Mohammed bin Salman” featured in 250,000 tweets. “We have to stand by our leader” was posted more than 60,000 times, along with 100,000 messages imploring Saudis to “Unfollow enemies of the nation.” In all likelihood, the majority of these messages were generated by chatbots.
  • around a fifth of all tweets discussing the 2016 presidential election are believed to have been the work of chatbots.
  • a third of all traffic on Twitter before the 2016 referendum on Britain’s membership in the European Union was said to come from chatbots, principally in support of the Leave side.
  • It’s irrelevant that current bots are not “smart” like we are, or that they have not achieved the consciousness and creativity hoped for by A.I. purists. What matters is their impact
  • In the past, despite our differences, we could at least take for granted that all participants in the political process were human beings. This no longer true
  • Increasingly we share the online debate chamber with nonhuman entities that are rapidly growing more advanced
  • a bot developed by the British firm Babylon reportedly achieved a score of 81 percent in the clinical examination for admission to the Royal College of General Practitioners. The average score for human doctors? 72 percent.
  • If chatbots are approaching the stage where they can answer diagnostic questions as well or better than human doctors, then it’s possible they might eventually reach or surpass our levels of political sophistication
  • chatbots could seriously endanger our democracy, and not just when they go haywire.
  • They’ll likely have faces and voices, names and personalities — all engineered for maximum persuasion. So-called “deep fake” videos can already convincingly synthesize the speech and appearance of real politicians.
  • The most obvious risk is that we are crowded out of our own deliberative processes by systems that are too fast and too ubiquitous for us to keep up with.
  • A related risk is that wealthy people will be able to afford the best chatbots.
  • in a world where, increasingly, the only feasible way of engaging in debate with chatbots is through the deployment of other chatbots also possessed of the same speed and facility, the worry is that in the long run we’ll become effectively excluded from our own party.
  • the wholesale automation of deliberation would be an unfortunate development in democratic history.
  • A blunt approach — call it disqualification — would be an all-out prohibition of bots on forums where important political speech takes place, and punishment for the humans responsible
  • The Bot Disclosure and Accountability Bil
  • would amend the Federal Election Campaign Act of 1971 to prohibit candidates and political parties from using any bots intended to impersonate or replicate human activity for public communication. It would also stop PACs, corporations and labor organizations from using bots to disseminate messages advocating candidates, which would be considered “electioneering communications.”
  • A subtler method would involve mandatory identification: requiring all chatbots to be publicly registered and to state at all times the fact that they are chatbots, and the identity of their human owners and controllers.
  • We should also be exploring more imaginative forms of regulation. Why not introduce a rule, coded into platforms themselves, that bots may make only up to a specific number of online contributions per day, or a specific number of responses to a particular human?
  • We need not treat the speech of chatbots with the same reverence that we treat human speech. Moreover, bots are too fast and tricky to be subject to ordinary rules of debate
  • the methods we use to regulate bots must be more robust than those we apply to people. There can be no half-measures when democracy is at stake.
Javier E

For Chat-Based AI, We Are All Once Again Tech Companies' Guinea Pigs - WSJ - 0 views

www.wsj.com/...-are-tech-guinea-pigs-647d827b

ai chatbot generative experiment evaluation justification debate

shared by Javier E on 27 Feb 23 - No Cached
  • The companies touting new chat-based artificial-intelligence systems are running a massive experiment—and we are the test subjects.
  • In this experiment, Microsoft, MSFT -2.18% OpenAI and others are rolling out on the internet an alien intelligence that no one really understands, which has been granted the ability to influence our assessment of what’s true in the world. 
  • Companies have been cautious in the past about unleashing this technology on the world. In 2019, OpenAI decided not to release an earlier version of the underlying model that powers both ChatGPT and the new Bing because the company’s leaders deemed it too dangerous to do so, they said at the time.
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  • Microsoft leaders felt “enormous urgency” for it to be the company to bring this technology to market, because others around the world are working on similar tech but might not have the resources or inclination to build it as responsibly, says Sarah Bird, a leader on Microsoft’s responsible AI team.
  • One common starting point for such models is what is essentially a download or “scrape” of most of the internet. In the past, these language models were used to try to understand text, but the new generation of them, part of the revolution in “generative” AI, uses those same models to create texts by trying to guess, one word at a time, the most likely word to come next in any given sequence.
  • Wide-scale testing gives Microsoft and OpenAI a big competitive edge by enabling them to gather huge amounts of data about how people actually use such chatbots. Both the prompts users input into their systems, and the results their AIs spit out, can then be fed back into a complicated system—which includes human content moderators paid by the companies—to improve it.
  • , being first to market with a chat-based AI gives these companies a huge initial lead over companies that have been slower to release their own chat-based AIs, such as Google.
  • rarely has an experiment like Microsoft and OpenAI’s been rolled out so quickly, and at such a broad scale.
  • Among those who build and study these kinds of AIs, Mr. Altman’s case for experimenting on the global public has inspired responses ranging from raised eyebrows to condemnation.
  • The fact that we’re all guinea pigs in this experiment doesn’t mean it shouldn’t be conducted, says Nathan Lambert, a research scientist at the AI startup Huggingface.
  • “I would kind of be happier with Microsoft doing this experiment than a startup, because Microsoft will at least address these issues when the press cycle gets really bad,” says Dr. Lambert. “I think there are going to be a lot of harms from this kind of AI, and it’s better people know they are coming,” he adds.
  • Others, particularly those who study and advocate for the concept of “ethical AI” or “responsible AI,” argue that the global experiment Microsoft and OpenAI are conducting is downright dangerous
  • Celeste Kidd, a professor of psychology at University of California, Berkeley, studies how people acquire knowledge
  • Her research has shown that people learning about new things have a narrow window in which they form a lasting opinion. Seeing misinformation during this critical initial period of exposure to a new concept—such as the kind of misinformation that chat-based AIs can confidently dispense—can do lasting harm, she says.
  • Dr. Kidd likens OpenAI’s experimentation with AI to exposing the public to possibly dangerous chemicals. “Imagine you put something carcinogenic in the drinking water and you were like, ‘We’ll see if it’s carcinogenic.’ After, you can’t take it back—people have cancer now,”
  • Part of the challenge with AI chatbots is that they can sometimes simply make things up. Numerous examples of this tendency have been documented by users of both ChatGPT and OpenA
  • These models also tend to be riddled with biases that may not be immediately apparent to users. For example, they can express opinions gleaned from the internet as if they were verified facts
  • When millions are exposed to these biases across billions of interactions, this AI has the potential to refashion humanity’s views, at a global scale, says Dr. Kidd.
  • OpenAI has talked publicly about the problems with these systems, and how it is trying to address them. In a recent blog post, the company said that in the future, users might be able to select AIs whose “values” align with their own.
  • “We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society,” the post said.
  • Eliminating made-up information and bias from chat-based search engines is impossible given the current state of the technology, says Mark Riedl, a professor at Georgia Institute of Technology who studies artificial intelligence
  • He believes the release of these technologies to the public by Microsoft and OpenAI is premature. “We are putting out products that are still being actively researched at this moment,” he adds. 
  • in other areas of human endeavor—from new drugs and new modes of transportation to advertising and broadcast media—we have standards for what can and cannot be unleashed on the public. No such standards exist for AI, says Dr. Riedl.
  • To modify these AIs so that they produce outputs that humans find both useful and not-offensive, engineers often use a process called “reinforcement learning through human feedback.
  • that’s a fancy way of saying that humans provide input to the raw AI algorithm, often by simply saying which of its potential responses to a query are better—and also which are not acceptable at all.
  • Microsoft’s and OpenAI’s globe-spanning experiments on millions of people are yielding a fire hose of data for both companies. User-entered prompts and the AI-generated results are fed back through a network of paid human AI trainers to further fine-tune the models,
  • Huggingface’s Dr. Lambert says that any company, including his own, that doesn’t have this river of real-world usage data helping it improve its AI is at a huge disadvantage
  • In chatbots, in some autonomous-driving systems, in the unaccountable AIs that decide what we see on social media, and now, in the latest applications of AI, again and again we are the guinea pigs on which tech companies are testing new technology.
  • It may be the case that there is no other way to roll out this latest iteration of AI—which is already showing promise in some areas—at scale. But we should always be asking, at times like these: At what price?
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