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katherineharron

CES 2020: Toyota is building a 'smart' city to test AI, robots and self-driving cars - ... - 0 views

www.cnn.com/...index.html

shared by katherineharron on 17 Jan 20 - No Cached
  • armaker Toyota has unveiled plans for a 2,000-person "city of the future," where it will test autonomous vehicles, smart technology and robot-assisted living.
  • "With people buildings and vehicles all connected and communicating with each other through data and sensors, we will be able to test AI technology, in both the virtual and the physical world, maximizing its potential," he said on stage during Tuesday's unveiling. "We want to turn artificial intelligence into intelligence amplified."
  • The project is a collaboration between the Japanese carmaker and Danish architecture firm Bjarke Ingels Group (BIG), which designed the city's master plan. Buildings on the site will be made primarily from wood, and partly constructed using robotics. But the designs also look to Japan's past for inspiration, incorporating traditional joinery techniques and the sweeping roofs characteristic of the country's architecture.
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  • Smart technology will extend inside residents' homes, according to Ingels, whose firm also designed the 2 World Trade Center in New York, and Google's headquarters in both London and Silicon Valley.
  • "In an age when technology, social media and online retail is replacing and eliminating our natural meeting places, the Woven City will explore ways to stimulate human interaction in the urban space," he said. "After all, human connectivity is the kind of connectivity that triggers wellbeing and happiness, productivity and innovation."
blythewallick

Can Artificial Intelligence Be Creative? | JSTOR Daily - 0 views

daily.jstor.org/icial-intelligence-be-creative

Technology research

shared by blythewallick on 25 Oct 19 - No Cached
  • Machines can write compelling ad copy and solve complex “real life” problems. Should the creative class be worried?
  • Rich breaks down some “abstract” problems into their fundamental parts and shows how, with comprehensive enough data and well-structured enough logical programming, AI could be suited to tackle creative problems. In one case, she offers a “real world” example about a manufacturing company’s new line of products and their plans, goals, and expectations for marketing the new line to a specific city. Weekly Newsletter Get your fix of JSTOR Daily’s best stories in your inbox each Thursday. Privacy Policy   Contact Us You may unsubscribe at any time by clicking on the provided link on any marketing message.
  • almost all problems rely (or ought to rely) on an understanding of the nature of both knowledge and reasoning. Humanists are trying to solve many of these same problems. Thus there is room for a good deal of interaction between artificial intelligence and many disciplines within the humanities.
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  • There is much to be said, however, for art’s ability to evoke emotion based on common experience, sincerity, talent, and unique skill. Rich proves that AI can be used to answer complicated questions. But what we think of as creative work in the humanities is much more often about asking questions than it is about answering them.
Javier E

Silicon Valley's Safe Space - The New York Times - 0 views

www.nytimes.com/...e-star-codex-rationalists.html

ai tech elite rationalism silicon valley knowledge social media technology

shared by Javier E on 10 Jun 23 - No Cached
  • The roots of Slate Star Codex trace back more than a decade to a polemicist and self-described A.I. researcher named Eliezer Yudkowsky, who believed that intelligent machines could end up destroying humankind. He was a driving force behind the rise of the Rationalists.
  • Because the Rationalists believed A.I. could end up destroying the world — a not entirely novel fear to anyone who has seen science fiction movies — they wanted to guard against it. Many worked for and donated money to MIRI, an organization created by Mr. Yudkowsky whose stated mission was “A.I. safety.”
  • The community was organized and close-knit. Two Bay Area organizations ran seminars and high-school summer camps on the Rationalist way of thinking.
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  • “The curriculum covers topics from causal modeling and probability to game theory and cognitive science,” read a website promising teens a summer of Rationalist learning. “How can we understand our own reasoning, behavior, and emotions? How can we think more clearly and better achieve our goals?”
  • Some lived in group houses. Some practiced polyamory. “They are basically just hippies who talk a lot more about Bayes’ theorem than the original hippies,” said Scott Aaronson, a University of Texas professor who has stayed in one of the group houses.
  • For Kelsey Piper, who embraced these ideas in high school, around 2010, the movement was about learning “how to do good in a world that changes very rapidly.”
  • Yes, the community thought about A.I., she said, but it also thought about reducing the price of health care and slowing the spread of disease.
  • Slate Star Codex, which sprung up in 2013, helped her develop a “calibrated trust” in the medical system. Many people she knew, she said, felt duped by psychiatrists, for example, who they felt weren’t clear about the costs and benefits of certain treatment.
  • That was not the Rationalist way.
  • “There is something really appealing about somebody explaining where a lot of those ideas are coming from and what a lot of the questions are,” she said.
  • Sam Altman, chief executive of OpenAI, an artificial intelligence lab backed by a billion dollars from Microsoft. He was effusive in his praise of the blog.It was, he said, essential reading among “the people inventing the future” in the tech industry.
  • Mr. Altman, who had risen to prominence as the president of the start-up accelerator Y Combinator, moved on to other subjects before hanging up. But he called back. He wanted to talk about an essay that appeared on the blog in 2014.The essay was a critique of what Mr. Siskind, writing as Scott Alexander, described as “the Blue Tribe.” In his telling, these were the people at the liberal end of the political spectrum whose characteristics included “supporting gay rights” and “getting conspicuously upset about sexists and bigots.”
  • But as the man behind Slate Star Codex saw it, there was one group the Blue Tribe could not tolerate: anyone who did not agree with the Blue Tribe. “Doesn’t sound quite so noble now, does it?” he wrote.
  • Mr. Altman thought the essay nailed a big problem: In the face of the “internet mob” that guarded against sexism and racism, entrepreneurs had less room to explore new ideas. Many of their ideas, such as intelligence augmentation and genetic engineering, ran afoul of the Blue Tribe.
  • Mr. Siskind was not a member of the Blue Tribe. He was not a voice from the conservative Red Tribe (“opposing gay marriage,” “getting conspicuously upset about terrorists and commies”). He identified with something called the Grey Tribe — as did many in Silicon Valley.
  • The Grey Tribe was characterized by libertarian beliefs, atheism, “vague annoyance that the question of gay rights even comes up,” and “reading lots of blogs,” he wrote. Most significantly, it believed in absolute free speech.
  • The essay on these tribes, Mr. Altman told me, was an inflection point for Silicon Valley. “It was a moment that people talked about a lot, lot, lot,” he said.
  • And in some ways, two of the world’s prominent A.I. labs — organizations that are tackling some of the tech industry’s most ambitious and potentially powerful projects — grew out of the Rationalist movement.
  • In 2005, Peter Thiel, the co-founder of PayPal and an early investor in Facebook, befriended Mr. Yudkowsky and gave money to MIRI. In 2010, at Mr. Thiel’s San Francisco townhouse, Mr. Yudkowsky introduced him to a pair of young researchers named Shane Legg and Demis Hassabis. That fall, with an investment from Mr. Thiel’s firm, the two created an A.I. lab called DeepMind.
  • Like the Rationalists, they believed that A.I could end up turning against humanity, and because they held this belief, they felt they were among the only ones who were prepared to build it in a safe way.
  • In 2014, Google bought DeepMind for $650 million. The next year, Elon Musk — who also worried A.I. could destroy the world and met his partner, Grimes, because they shared an interest in a Rationalist thought experiment — founded OpenAI as a DeepMind competitor. Both labs hired from the Rationalist community.
  • Mr. Aaronson, the University of Texas professor, was turned off by the more rigid and contrarian beliefs of the Rationalists, but he is one of the blog’s biggest champions and deeply admired that it didn’t avoid live-wire topics.
  • “It must have taken incredible guts for Scott to express his thoughts, misgivings and questions about some major ideological pillars of the modern world so openly, even if protected by a quasi-pseudonym,” he said
  • In late June of last year, not long after talking to Mr. Altman, the OpenAI chief executive, I approached the writer known as Scott Alexander, hoping to get his views on the Rationalist way and its effect on Silicon Valley. That was when the blog vanished.
  • The issue, it was clear to me, was that I told him I could not guarantee him the anonymity he’d been writing with. In fact, his real name was easy to find because people had shared it online for years and he had used it on a piece he’d written for a scientific journal. I did a Google search for Scott Alexander and one of the first results I saw in the auto-complete list was Scott Alexander Siskind.
  • More than 7,500 people signed a petition urging The Times not to publish his name, including many prominent figures in the tech industry. “Putting his full name in The Times,” the petitioners said, “would meaningfully damage public discourse, by discouraging private citizens from sharing their thoughts in blog form.” On the internet, many in Silicon Valley believe, everyone has the right not only to say what they want but to say it anonymously.
  • I spoke with Manoel Horta Ribeiro, a computer science researcher who explores social networks at the Swiss Federal Institute of Technology in Lausanne. He was worried that Slate Star Codex, like other communities, was allowing extremist views to trickle into the influential tech world. “A community like this gives voice to fringe groups,” he said. “It gives a platform to people who hold more extreme views.”
  • I assured her my goal was to report on the blog, and the Rationalists, with rigor and fairness. But she felt that discussing both critics and supporters could be unfair. What I needed to do, she said, was somehow prove statistically which side was right.
  • When I asked Mr. Altman if the conversation on sites like Slate Star Codex could push people toward toxic beliefs, he said he held “some empathy” for these concerns. But, he added, “people need a forum to debate ideas.”
  • In August, Mr. Siskind restored his old blog posts to the internet. And two weeks ago, he relaunched his blog on Substack, a company with ties to both Andreessen Horowitz and Y Combinator. He gave the blog a new title: Astral Codex Ten. He hinted that Substack paid him $250,000 for a year on the platform. And he indicated the company would give him all the protection he needed.
Javier E

The Sad Trombone Debate: The RNC Throws in the Towel and Gets Ready to Roll Over for Tr... - 0 views

plus.thebulwark.com/...trombone-debate-the-rnc-throws

builder conserver media internet future forecast new content audience distribution creation technology social media

shared by Javier E on 06 Dec 23 - No Cached
  • Death to the Internet
  • Yesterday Ben Thompson published a remarkable essay in which he more or less makes the case that the internet is a socially deleterious invention, that it will necessarily get more toxic, and that the best we can hope for is that it gets so bad, so fast, that everyone is shocked into turning away from it.
  • Ben writes the best and most insightful newsletter about technology and he has been, in all the years I’ve read him, a techno-optimist.
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  • this is like if Russell Moore came out and said that, on the whole, Christianity turns out to be a bad thing. It’s that big of a deal.
  • Thompson’s case centers around constraints and supply, particularly as they apply to content creation.
  • In the pre-internet days, creating and distributing content was relatively expensive, which placed content publishers—be they newspapers, or TV stations, or movie studios—high on the value chain.
  • The internet reduced distribution costs to zero and this shifted value away from publishers and over to aggregators: Suddenly it was more important to aggregate an audience—a la Google and Facebook—than to be a content creator.
  • Audiences were valuable; content was commoditized.
  • What has alarmed Thompson is that AI has now reduced the cost of creating content to zero.
  • what does the world look like when both the creation and distribution of content are zero?
  • Hellscape
  • We’re headed to a place where content is artificially created and distributed in such a way as to be tailored to a given user’s preferences. Which will be the equivalent of living in a hall of mirrors.
  • What does that mean for news? Nothing good.
  • It doesn’t really make sense to talk about “news media” because there are fundamental differences between publication models that are driven by scale.
  • So the challenges the New York Times face will be different than the challenges that NPR or your local paper face.
  • Two big takeaways:
  • (1) Ad-supported publications will not survive
  • Zero-cost for content creation combined with zero-cost distribution means an infinite supply of content. The more content you have, the more ad space exists—the lower ad prices go.
  • Actually, some ad-supported publications will survive. They just won’t be news. What will survive will be content mills that exist to serve ads specifically matched to targeted audiences.
  • (2) Size is determinative.
  • The New York Times has a moat by dint of its size. It will see the utility of its soft “news” sections decline in value, because AI is going to be better at creating cooking and style content than breaking hard news. But still, the NYT will be okay because it has pivoted hard into being a subscription-based service over the last decade.
  • At the other end of the spectrum, independent journalists should be okay. A lone reporter running a focused Substack who only needs four digits’ worth of subscribers to sustain them.
  • But everything in between? That’s a crapshoot.
  • Technology writers sometimes talk about the contrast between “builders” and “conservers” — roughly speaking, between those who are most animated by what we stand to gain from technology and those animated by what we stand to lose.
  • in our moment the builder and conserver types are proving quite mercurial. On issues ranging from Big Tech to medicine, human enhancement to technologies of governance, the politics of technology are in upheaval.
  • Dispositions are supposed to be basically fixed. So who would have thought that deep blue cities that yesterday were hotbeds of vaccine skepticism would today become pioneers of vaccine passports? Or that outlets that yesterday reported on science and tech developments in reverent tones would today make it their mission to unmask “tech bros”?
  • One way to understand this churn is that the builder and the conserver types each speak to real, contrasting features within human nature. Another way is that these types each pick out real, contrasting features of technology. Focusing strictly on one set of features or the other eventually becomes unstable, forcing the other back into view.
Javier E

Why the Past 10 Years of American Life Have Been Uniquely Stupid - The Atlantic - 0 views

www.theatlantic.com/...629369

politics history social media technology psychology bias fragmentation

shared by Javier E on 26 Apr 22 - No Cached
  • Social scientists have identified at least three major forces that collectively bind together successful democracies: social capital (extensive social networks with high levels of trust), strong institutions, and shared stories.
  • Social media has weakened all three.
  • gradually, social-media users became more comfortable sharing intimate details of their lives with strangers and corporations. As I wrote in a 2019 Atlantic article with Tobias Rose-Stockwell, they became more adept at putting on performances and managing their personal brand—activities that might impress others but that do not deepen friendships in the way that a private phone conversation will.
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  • the stage was set for the major transformation, which began in 2009: the intensification of viral dynamics.
  • Before 2009, Facebook had given users a simple timeline––a never-ending stream of content generated by their friends and connections, with the newest posts at the top and the oldest ones at the bottom
  • That began to change in 2009, when Facebook offered users a way to publicly “like” posts with the click of a button. That same year, Twitter introduced something even more powerful: the “Retweet” button, which allowed users to publicly endorse a post while also sharing it with all of their followers.
  • “Like” and “Share” buttons quickly became standard features of most other platforms.
  • Facebook developed algorithms to bring each user the content most likely to generate a “like” or some other interaction, eventually including the “share” as well.
  • Later research showed that posts that trigger emotions––especially anger at out-groups––are the most likely to be shared.
  • By 2013, social media had become a new game, with dynamics unlike those in 2008. If you were skillful or lucky, you might create a post that would “go viral” and make you “internet famous”
  • If you blundered, you could find yourself buried in hateful comments. Your posts rode to fame or ignominy based on the clicks of thousands of strangers, and you in turn contributed thousands of clicks to the game.
  • This new game encouraged dishonesty and mob dynamics: Users were guided not just by their true preferences but by their past experiences of reward and punishment,
  • As a social psychologist who studies emotion, morality, and politics, I saw this happening too. The newly tweaked platforms were almost perfectly designed to bring out our most moralistic and least reflective selves. The volume of outrage was shocking.
  • It was just this kind of twitchy and explosive spread of anger that James Madison had tried to protect us from as he was drafting the U.S. Constitution.
  • The Framers of the Constitution were excellent social psychologists. They knew that democracy had an Achilles’ heel because it depended on the collective judgment of the people, and democratic communities are subject to “the turbulency and weakness of unruly passions.”
  • The key to designing a sustainable republic, therefore, was to build in mechanisms to slow things down, cool passions, require compromise, and give leaders some insulation from the mania of the moment while still holding them accountable to the people periodically, on Election Day.
  • The tech companies that enhanced virality from 2009 to 2012 brought us deep into Madison’s nightmare.
  • a less quoted yet equally important insight, about democracy’s vulnerability to triviality.
  • Madison notes that people are so prone to factionalism that “where no substantial occasion presents itself, the most frivolous and fanciful distinctions have been sufficient to kindle their unfriendly passions and excite their most violent conflicts.”
  • Social media has both magnified and weaponized the frivolous.
  • It’s not just the waste of time and scarce attention that matters; it’s the continual chipping-away of trust.
  • a democracy depends on widely internalized acceptance of the legitimacy of rules, norms, and institutions.
  • when citizens lose trust in elected leaders, health authorities, the courts, the police, universities, and the integrity of elections, then every decision becomes contested; every election becomes a life-and-death struggle to save the country from the other side
  • The most recent Edelman Trust Barometer (an international measure of citizens’ trust in government, business, media, and nongovernmental organizations) showed stable and competent autocracies (China and the United Arab Emirates) at the top of the list, while contentious democracies such as the United States, the United Kingdom, Spain, and South Korea scored near the bottom (albeit above Russia).
  • The literature is complex—some studies show benefits, particularly in less developed democracies—but the review found that, on balance, social media amplifies political polarization; foments populism, especially right-wing populism; and is associated with the spread of misinformation.
  • When people lose trust in institutions, they lose trust in the stories told by those institutions. That’s particularly true of the institutions entrusted with the education of children.
  • Facebook and Twitter make it possible for parents to become outraged every day over a new snippet from their children’s history lessons––and math lessons and literature selections, and any new pedagogical shifts anywhere in the country
  • The motives of teachers and administrators come into question, and overreaching laws or curricular reforms sometimes follow, dumbing down education and reducing trust in it further.
  • young people educated in the post-Babel era are less likely to arrive at a coherent story of who we are as a people, and less likely to share any such story with those who attended different schools or who were educated in a different decade.
  • former CIA analyst Martin Gurri predicted these fracturing effects in his 2014 book, The Revolt of the Public. Gurri’s analysis focused on the authority-subverting effects of information’s exponential growth, beginning with the internet in the 1990s. Writing nearly a decade ago, Gurri could already see the power of social media as a universal solvent, breaking down bonds and weakening institutions everywhere it reached.
  • he notes a constructive feature of the pre-digital era: a single “mass audience,” all consuming the same content, as if they were all looking into the same gigantic mirror at the reflection of their own society. I
  • The digital revolution has shattered that mirror, and now the public inhabits those broken pieces of glass. So the public isn’t one thing; it’s highly fragmented, and it’s basically mutually hostile
  • Facebook, Twitter, YouTube, and a few other large platforms unwittingly dissolved the mortar of trust, belief in institutions, and shared stories that had held a large and diverse secular democracy together.
  • I think we can date the fall of the tower to the years between 2011 (Gurri’s focal year of “nihilistic” protests) and 2015, a year marked by the “great awokening” on the left and the ascendancy of Donald Trump on the right.
  • Twitter can overpower all the newspapers in the country, and stories cannot be shared (or at least trusted) across more than a few adjacent fragments—so truth cannot achieve widespread adherence.
  • fter Babel, nothing really means anything anymore––at least not in a way that is durable and on which people widely agree.
  • Politics After Babel
  • “Politics is the art of the possible,” the German statesman Otto von Bismarck said in 1867. In a post-Babel democracy, not much may be possible.
  • The ideological distance between the two parties began increasing faster in the 1990s. Fox News and the 1994 “Republican Revolution” converted the GOP into a more combative party.
  • So cross-party relationships were already strained before 2009. But the enhanced virality of social media thereafter made it more hazardous to be seen fraternizing with the enemy or even failing to attack the enemy with sufficient vigor.
  • What changed in the 2010s? Let’s revisit that Twitter engineer’s metaphor of handing a loaded gun to a 4-year-old. A mean tweet doesn’t kill anyone; it is an attempt to shame or punish someone publicly while broadcasting one’s own virtue, brilliance, or tribal loyalties. It’s more a dart than a bullet
  • from 2009 to 2012, Facebook and Twitter passed out roughly 1 billion dart guns globally. We’ve been shooting one another ever since.
  • “devoted conservatives,” comprised 6 percent of the U.S. population.
  • the warped “accountability” of social media has also brought injustice—and political dysfunction—in three ways.
  • First, the dart guns of social media give more power to trolls and provocateurs while silencing good citizens.
  • a small subset of people on social-media platforms are highly concerned with gaining status and are willing to use aggression to do so.
  • Across eight studies, Bor and Petersen found that being online did not make most people more aggressive or hostile; rather, it allowed a small number of aggressive people to attack a much larger set of victims. Even a small number of jerks were able to dominate discussion forums,
  • Additional research finds that women and Black people are harassed disproportionately, so the digital public square is less welcoming to their voices.
  • Second, the dart guns of social media give more power and voice to the political extremes while reducing the power and voice of the moderate majority.
  • The “Hidden Tribes” study, by the pro-democracy group More in Common, surveyed 8,000 Americans in 2017 and 2018 and identified seven groups that shared beliefs and behaviors.
  • Social media has given voice to some people who had little previously, and it has made it easier to hold powerful people accountable for their misdeeds
  • The group furthest to the left, the “progressive activists,” comprised 8 percent of the population. The progressive activists were by far the most prolific group on social media: 70 percent had shared political content over the previous year. The devoted conservatives followed, at 56 percent.
  • These two extreme groups are similar in surprising ways. They are the whitest and richest of the seven groups, which suggests that America is being torn apart by a battle between two subsets of the elite who are not representative of the broader society.
  • they are the two groups that show the greatest homogeneity in their moral and political attitudes.
  • likely a result of thought-policing on social media:
  • political extremists don’t just shoot darts at their enemies; they spend a lot of their ammunition targeting dissenters or nuanced thinkers on their own team.
  • Finally, by giving everyone a dart gun, social media deputizes everyone to administer justice with no due process. Platforms like Twitter devolve into the Wild West, with no accountability for vigilantes.
  • Enhanced-virality platforms thereby facilitate massive collective punishment for small or imagined offenses, with real-world consequences, including innocent people losing their jobs and being shamed into suicide
  • we don’t get justice and inclusion; we get a society that ignores context, proportionality, mercy, and truth.
  • Since the tower fell, debates of all kinds have grown more and more confused. The most pervasive obstacle to good thinking is confirmation bias, which refers to the human tendency to search only for evidence that confirms our preferred beliefs
  • search engines were supercharging confirmation bias, making it far easier for people to find evidence for absurd beliefs and conspiracy theorie
  • The most reliable cure for confirmation bias is interaction with people who don’t share your beliefs. They confront you with counterevidence and counterargument.
  • In his book The Constitution of Knowledge, Jonathan Rauch describes the historical breakthrough in which Western societies developed an “epistemic operating system”—that is, a set of institutions for generating knowledge from the interactions of biased and cognitively flawed individuals
  • English law developed the adversarial system so that biased advocates could present both sides of a case to an impartial jury.
  • Newspapers full of lies evolved into professional journalistic enterprises, with norms that required seeking out multiple sides of a story, followed by editorial review, followed by fact-checking.
  • Universities evolved from cloistered medieval institutions into research powerhouses, creating a structure in which scholars put forth evidence-backed claims with the knowledge that other scholars around the world would be motivated to gain prestige by finding contrary evidence.
  • Part of America’s greatness in the 20th century came from having developed the most capable, vibrant, and productive network of knowledge-producing institutions in all of human history
  • But this arrangement, Rauch notes, “is not self-maintaining; it relies on an array of sometimes delicate social settings and understandings, and those need to be understood, affirmed, and protected.”
  • This, I believe, is what happened to many of America’s key institutions in the mid-to-late 2010s. They got stupider en masse because social media instilled in their members a chronic fear of getting darted
  • it was so pervasive that it established new behavioral norms backed by new policies seemingly overnight
  • Participants in our key institutions began self-censoring to an unhealthy degree, holding back critiques of policies and ideas—even those presented in class by their students—that they believed to be ill-supported or wrong.
  • The stupefying process plays out differently on the right and the left because their activist wings subscribe to different narratives with different sacred values.
  • The “Hidden Tribes” study tells us that the “devoted conservatives” score highest on beliefs related to authoritarianism. They share a narrative in which America is eternally under threat from enemies outside and subversives within; they see life as a battle between patriots and traitors.
  • they are psychologically different from the larger group of “traditional conservatives” (19 percent of the population), who emphasize order, decorum, and slow rather than radical change.
  • The traditional punishment for treason is death, hence the battle cry on January 6: “Hang Mike Pence.”
  • Right-wing death threats, many delivered by anonymous accounts, are proving effective in cowing traditional conservatives
  • The wave of threats delivered to dissenting Republican members of Congress has similarly pushed many of the remaining moderates to quit or go silent, giving us a party ever more divorced from the conservative tradition, constitutional responsibility, and reality.
  • The stupidity on the right is most visible in the many conspiracy theories spreading across right-wing media and now into Congress.
  • The Democrats have also been hit hard by structural stupidity, though in a different way. In the Democratic Party, the struggle between the progressive wing and the more moderate factions is open and ongoing, and often the moderates win.
  • The problem is that the left controls the commanding heights of the culture: universities, news organizations, Hollywood, art museums, advertising, much of Silicon Valley, and the teachers’ unions and teaching colleges that shape K–12 education. And in many of those institutions, dissent has been stifled:
  • Liberals in the late 20th century shared a belief that the sociologist Christian Smith called the “liberal progress” narrative, in which America used to be horrifically unjust and repressive, but, thanks to the struggles of activists and heroes, has made (and continues to make) progress toward realizing the noble promise of its founding.
  • It is also the view of the “traditional liberals” in the “Hidden Tribes” study (11 percent of the population), who have strong humanitarian values, are older than average, and are largely the people leading America’s cultural and intellectual institutions.
  • when the newly viralized social-media platforms gave everyone a dart gun, it was younger progressive activists who did the most shooting, and they aimed a disproportionate number of their darts at these older liberal leaders.
  • Confused and fearful, the leaders rarely challenged the activists or their nonliberal narrative in which life at every institution is an eternal battle among identity groups over a zero-sum pie, and the people on top got there by oppressing the people on the bottom. This new narrative is rigidly egalitarian––focused on equality of outcomes, not of rights or opportunities. It is unconcerned with individual rights.
  • The universal charge against people who disagree with this narrative is not “traitor”; it is “racist,” “transphobe,” “Karen,” or some related scarlet letter marking the perpetrator as one who hates or harms a marginalized group.
  • The punishment that feels right for such crimes is not execution; it is public shaming and social death.
  • anyone on Twitter had already seen dozens of examples teaching the basic lesson: Don’t question your own side’s beliefs, policies, or actions. And when traditional liberals go silent, as so many did in the summer of 2020, the progressive activists’ more radical narrative takes over as the governing narrative of an organization.
  • This is why so many epistemic institutions seemed to “go woke” in rapid succession that year and the next, beginning with a wave of controversies and resignations at The New York Times and other newspapers, and continuing on to social-justice pronouncements by groups of doctors and medical associations
  • The problem is structural. Thanks to enhanced-virality social media, dissent is punished within many of our institutions, which means that bad ideas get elevated into official policy.
  • In a 2018 interview, Steve Bannon, the former adviser to Donald Trump, said that the way to deal with the media is “to flood the zone with shit.” He was describing the “firehose of falsehood” tactic pioneered by Russian disinformation programs to keep Americans confused, disoriented, and angry.
  • artificial intelligence is close to enabling the limitless spread of highly believable disinformation. The AI program GPT-3 is already so good that you can give it a topic and a tone and it will spit out as many essays as you like, typically with perfect grammar and a surprising level of coherence.
  • Renée DiResta, the research manager at the Stanford Internet Observatory, explained that spreading falsehoods—whether through text, images, or deep-fake videos—will quickly become inconceivably easy. (She co-wrote the essay with GPT-3.)
  • American factions won’t be the only ones using AI and social media to generate attack content; our adversaries will too.
  • In the 20th century, America’s shared identity as the country leading the fight to make the world safe for democracy was a strong force that helped keep the culture and the polity together.
  • In the 21st century, America’s tech companies have rewired the world and created products that now appear to be corrosive to democracy, obstacles to shared understanding, and destroyers of the modern tower.
  • What changes are needed?
  • I can suggest three categories of reforms––three goals that must be achieved if democracy is to remain viable in the post-Babel era.
  • We must harden democratic institutions so that they can withstand chronic anger and mistrust, reform social media so that it becomes less socially corrosive, and better prepare the next generation for democratic citizenship in this new age.
  • Harden Democratic Institutions
  • we must reform key institutions so that they can continue to function even if levels of anger, misinformation, and violence increase far above those we have today.
  • Reforms should reduce the outsize influence of angry extremists and make legislators more responsive to the average voter in their district.
  • One example of such a reform is to end closed party primaries, replacing them with a single, nonpartisan, open primary from which the top several candidates advance to a general election that also uses ranked-choice voting
  • A second way to harden democratic institutions is to reduce the power of either political party to game the system in its favor, for example by drawing its preferred electoral districts or selecting the officials who will supervise elections
  • These jobs should all be done in a nonpartisan way.
  • Reform Social Media
  • Social media’s empowerment of the far left, the far right, domestic trolls, and foreign agents is creating a system that looks less like democracy and more like rule by the most aggressive.
  • it is within our power to reduce social media’s ability to dissolve trust and foment structural stupidity. Reforms should limit the platforms’ amplification of the aggressive fringes while giving more voice to what More in Common calls “the exhausted majority.”
  • the main problem with social media is not that some people post fake or toxic stuff; it’s that fake and outrage-inducing content can now attain a level of reach and influence that was not possible before
  • Perhaps the biggest single change that would reduce the toxicity of existing platforms would be user verification as a precondition for gaining the algorithmic amplification that social media offers.
  • One of the first orders of business should be compelling the platforms to share their data and their algorithms with academic researchers.
  • Prepare the Next Generation
  • Childhood has become more tightly circumscribed in recent generations––with less opportunity for free, unstructured play; less unsupervised time outside; more time online. Whatever else the effects of these shifts, they have likely impeded the development of abilities needed for effective self-governance for many young adults
  • Depression makes people less likely to want to engage with new people, ideas, and experiences. Anxiety makes new things seem more threatening. As these conditions have risen and as the lessons on nuanced social behavior learned through free play have been delayed, tolerance for diverse viewpoints and the ability to work out disputes have diminished among many young people
  • Students did not just say that they disagreed with visiting speakers; some said that those lectures would be dangerous, emotionally devastating, a form of violence. Because rates of teen depression and anxiety have continued to rise into the 2020s, we should expect these views to continue in the generations to follow, and indeed to become more severe.
  • The most important change we can make to reduce the damaging effects of social media on children is to delay entry until they have passed through puberty.
  • The age should be raised to at least 16, and companies should be held responsible for enforcing it.
  • et them out to play. Stop starving children of the experiences they most need to become good citizens: free play in mixed-age groups of children with minimal adult supervision
  • while social media has eroded the art of association throughout society, it may be leaving its deepest and most enduring marks on adolescents. A surge in rates of anxiety, depression, and self-harm among American teens began suddenly in the early 2010s. (The same thing happened to Canadian and British teens, at the same time.) The cause is not known, but the timing points to social media as a substantial contributor—the surge began just as the large majority of American teens became daily users of the major platforms.
  • What would it be like to live in Babel in the days after its destruction? We know. It is a time of confusion and loss. But it is also a time to reflect, listen, and build.
  • In recent years, Americans have started hundreds of groups and organizations dedicated to building trust and friendship across the political divide, including BridgeUSA, Braver Angels (on whose board I serve), and many others listed at BridgeAlliance.us. We cannot expect Congress and the tech companies to save us. We must change ourselves and our communities.
  • when we look away from our dysfunctional federal government, disconnect from social media, and talk with our neighbors directly, things seem more hopeful. Most Americans in the More in Common report are members of the “exhausted majority,” which is tired of the fighting and is willing to listen to the other side and compromise. Most Americans now see that social media is having a negative impact on the country, and are becoming more aware of its damaging effects on children.
Javier E

On the Controllability of Artificial Intelligence: An Analysis of Limitations | Journal... - 0 views

journals.riverpublishers.com/...16219

ai security control feasibility research technology evaluation expert

shared by Javier E on 27 Feb 23 - No Cached
  • In order to reap the benefits and avoid the pitfalls of such a powerful technology it is important to be able to control it. However, the possibility of controlling artificial general intelligence and its more advanced version, superintelligence, has not been formally established
  • In this paper, we present arguments as well as supporting evidence from multiple domains indicating that advanced AI cannot be fully controlled
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.
  • ...21 more annotations...
  • 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

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?
  • ...22 more annotations...
  • 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.
  • 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?
  • 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,”
  • I think it’s just going to get worse and worse.”
  • 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.
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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
  • ...22 more annotations...
  • , 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 Only Way to Deal With the Threat From AI? Shut It Down | Time - 0 views

time.com/...dkowsky-open-letter-not-enough

research knowledge superintelligence

shared by Javier E on 31 Mar 23 - No Cached
  • Javier E on 31 Mar 23
     
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Javier E

Scientists See Advances in Deep Learning, a Part of Artificial Intelligence - NYTimes.com - 1 views

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

technology research brain science AI

shared by Javier E on 24 Nov 12 - No Cached
  • Using an artificial intelligence technique inspired by theories about how the brain recognizes patterns, technology companies are reporting startling gains in fields as diverse as computer vision, speech recognition and the identification of promising new molecules for designing drugs.
  • They offer the promise of machines that converse with humans and perform tasks like driving cars and working in factories, raising the specter of automated robots that could replace human workers.
  • what is new in recent months is the growing speed and accuracy of deep-learning programs, often called artificial neural networks or just “neural nets” for their resemblance to the neural connections in the brain.
  • ...3 more annotations...
  • With greater accuracy, for example, marketers can comb large databases of consumer behavior to get more precise information on buying habits. And improvements in facial recognition are likely to make surveillance technology cheaper and more commonplace.
  • Modern artificial neural networks are composed of an array of software components, divided into inputs, hidden layers and outputs. The arrays can be “trained” by repeated exposures to recognize patterns like images or sounds.
  • “The point about this approach is that it scales beautifully. Basically you just need to keep making it bigger and faster, and it will get better. There’s no looking back now.”
Javier E

Stephen Hawking just gave humanity a due date for finding another planet - The Washingt... - 0 views

www.washingtonpost.com/...ate-for-finding-another-planet

artificial intelligence human extinction science technology

shared by Javier E on 17 Nov 16 - No Cached
  • Hawking told the audience that Earth's cataclysmic end may be hastened by humankind, which will continue to devour the planet’s resources at unsustainable rates
  • “Although the chance of a disaster to planet Earth in a given year may be quite low, it adds up over time, and becomes a near certainty in the next thousand or ten thousand years. By that time we should have spread out into space, and to other stars, so a disaster on Earth would not mean the end of the human race.”
  • “I think the development of full artificial intelligence could spell the end of the human race,” Hawking told the BBC in a 2014 interview that touched upon everything from online privacy to his affinity for his robotic-sounding voice.
  • ...1 more annotation...
  • “Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate,” Hawking warned in recent months. “Humans, who are limited by slow biological evolution, couldn't compete and would be superseded.”
Javier E

Microsoft Created a Twitter Bot to Learn From Users. It Quickly Became a Racist Jerk. -... - 0 views

www.nytimes.com/...ckly-became-a-racist-jerk.html

social media AI learning psychology language

shared by Javier E on 26 Mar 16 - No Cached
  • Microsoft, in an emailed statement, described the machine-learning project as a social and cultural experiment.
  • Microsoft said the artificial intelligence project had been designed to “engage and entertain people” through “casual and playful conversation,” and that it was built through mining public data. It was targeted at 18- to 24-year-olds in the United States and was developed by a staff that included improvisational comedians.
Javier E

Welcome, Robot Overlords. Please Don't Fire Us? | Mother Jones - 0 views

www.motherjones.com/...l-intelligence-jobs-automation

robot AI development brain science automation labor-replacement

shared by Javier E on 01 Feb 14 - No Cached
  • This is the happy version. It's the one where computers keep getting smarter and smarter, and clever engineers keep building better and better robots. By 2040, computers the size of a softball are as smart as human beings. Smarter, in fact. Plus they're computers: They never get tired, they're never ill-tempered, they never make mistakes, and they have instant access to all of human knowledge.
  • , just as it took us until 2025 to fill up Lake Michigan, the simple exponential curve of Moore's Law suggests it's going to take us until 2025 to build a computer with the processing power of the human brain. And it's going to happen the same way: For the first 70 years, it will seem as if nothing is happening, even though we're doubling our progress every 18 months. Then, in the final 15 years, seemingly out of nowhere, we'll finish the job.
  • And that's exactly where we are. We've moved from computers with a trillionth of the power of a human brain to computers with a billionth of the power. Then a millionth. And now a thousandth. Along the way, computers progressed from ballistics to accounting to word processing to speech recognition, and none of that really seemed like progress toward artificial intelligence. That's because even a thousandth of the power of a human brain is—let's be honest—a bit of a joke.
  • ...4 more annotations...
  • But there's another reason as well: Every time computers break some new barrier, we decide—or maybe just finally get it through our thick skulls—that we set the bar too low.
  • the best estimates of the human brain suggest that our own processing power is about equivalent to 10 petaflops. ("Peta" comes after giga and tera.) That's a lot of flops, but last year an IBM Blue Gene/Q supercomputer at Lawrence Livermore National Laboratory was clocked at 16.3 petaflops.
  • in Lake Michigan terms, we finally have a few inches of water in the lake bed, and we can see it rising. All those milestones along the way—playing chess, translating web pages, winning at Jeopardy!, driving a car—aren't just stunts. They're precisely the kinds of things you'd expect as we struggle along with platforms that aren't quite powerful enough—yet. True artificial intelligence will very likely be here within a couple of decades. Making it small, cheap, and ubiquitous might take a decade more.
  • In other words, by about 2040 our robot paradise awaits.
Javier E

But What Would the End of Humanity Mean for Me? - James Hamblin - The Atlantic - 0 views

www.theatlantic.com/...361931

future AI forecasting apocalypse technology

shared by Javier E on 12 May 14 - No Cached
  • Tegmark is more worried about much more immediate threats, which he calls existential risks. That’s a term borrowed from physicist Nick Bostrom, director of Oxford University’s Future of Humanity Institute, a research collective modeling the potential range of human expansion into the cosmos
  • "I am finding it increasingly plausible that existential risk is the biggest moral issue in the world, even if it hasn’t gone mainstream yet,"
  • Existential risks, as Tegmark describes them, are things that are “not just a little bit bad, like a parking ticket, but really bad. Things that could really mess up or wipe out human civilization.”
  • ...17 more annotations...
  • The single existential risk that Tegmark worries about most is unfriendly artificial intelligence. That is, when computers are able to start improving themselves, there will be a rapid increase in their capacities, and then, Tegmark says, it’s very difficult to predict what will happen.
  • Tegmark told Lex Berko at Motherboard earlier this year, "I would guess there’s about a 60 percent chance that I’m not going to die of old age, but from some kind of human-caused calamity. Which would suggest that I should spend a significant portion of my time actually worrying about this. We should in society, too."
  • "Longer term—and this might mean 10 years, it might mean 50 or 100 years, depending on who you ask—when computers can do everything we can do," Tegmark said, “after that they will probably very rapidly get vastly better than us at everything, and we’ll face this question we talked about in the Huffington Post article: whether there’s really a place for us after that, or not.”
  • "This is very near-term stuff. Anyone who’s thinking about what their kids should study in high school or college should care a lot about this.”
  • Tegmark and his op-ed co-author Frank Wilczek, the Nobel laureate, draw examples of cold-war automated systems that assessed threats and resulted in false alarms and near misses. “In those instances some human intervened at the last moment and saved us from horrible consequences,” Wilczek told me earlier that day. “That might not happen in the future.”
  • there are still enough nuclear weapons in existence to incinerate all of Earth’s dense population centers, but that wouldn't kill everyone immediately. The smoldering cities would send sun-blocking soot into the stratosphere that would trigger a crop-killing climate shift, and that’s what would kill us all
  • “We are very reckless with this planet, with civilization,” Tegmark said. “We basically play Russian roulette.” The key is to think more long term, “not just about the next election cycle or the next Justin Bieber album.”
  • “There are several issues that arise, ranging from climate change to artificial intelligence to biological warfare to asteroids that might collide with the earth,” Wilczek said of the group’s launch. “They are very serious risks that don’t get much attention.
  • a widely perceived issue is when intelligent entities start to take on a life of their own. They revolutionized the way we understand chess, for instance. That’s pretty harmless. But one can imagine if they revolutionized the way we think about warfare or finance, either those entities themselves or the people that control them. It could pose some disquieting perturbations on the rest of our lives.”
  • Wilczek’s particularly concerned about a subset of artificial intelligence: drone warriors. “Not necessarily robots,” Wilczek told me, “although robot warriors could be a big issue, too. It could just be superintelligence that’s in a cloud. It doesn’t have to be embodied in the usual sense.”
  • it’s important not to anthropomorphize artificial intelligence. It's best to think of it as a primordial force of nature—strong and indifferent. In the case of chess, an A.I. models chess moves, predicts outcomes, and moves accordingly. If winning at chess meant destroying humanity, it might do that.
  • Even if programmers tried to program an A.I. to be benevolent, it could destroy us inadvertently. Andersen’s example in Aeon is that an A.I. designed to try and maximize human happiness might think that flooding your bloodstream with heroin is the best way to do that.
  • “It’s not clear how big the storm will be, or how long it’s going to take to get here. I don’t know. It might be 10 years before there’s a real problem. It might be 20, it might be 30. It might be five. But it’s certainly not too early to think about it, because the issues to address are only going to get more complex as the systems get more self-willed.”
  • Even within A.I. research, Tegmark admits, “There is absolutely not a consensus that we should be concerned about this.” But there is a lot of concern, and sense of lack of power. Because, concretely, what can you do? “The thing we should worry about is that we’re not worried.”
  • Tegmark brings it to Earth with a case-example about purchasing a stroller: If you could spend more for a good one or less for one that “sometimes collapses and crushes the baby, but nobody’s been able to prove that it is caused by any design flaw. But it’s 10 percent off! So which one are you going to buy?”
  • “There are seven billion of us on this little spinning ball in space. And we have so much opportunity," Tegmark said. "We have all the resources in this enormous cosmos. At the same time, we have the technology to wipe ourselves out.”
  • Ninety-nine percent of the species that have lived on Earth have gone extinct; why should we not? Seeing the biggest picture of humanity and the planet is the heart of this. It’s not meant to be about inspiring terror or doom. Sometimes that is what it takes to draw us out of the little things, where in the day-to-day we lose sight of enormous potentials.
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