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Bill Fulkerson

Anatomy of an AI System - 1 views

anatomyof.ai

AI amazon

shared by Bill Fulkerson on 14 Sep 18 - No Cached
  • Bill Fulkerson on 14 Sep 18
     
    "With each interaction, Alexa is training to hear better, to interpret more precisely, to trigger actions that map to the user's commands more accurately, and to build a more complete model of their preferences, habits and desires. What is required to make this possible? Put simply: each small moment of convenience - be it answering a question, turning on a light, or playing a song - requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch. A full accounting for these costs is almost impossible, but it is increasingly important that we grasp the scale and scope if we are to understand and govern the technical infrastructures that thread through our lives. III The Salar, the world's largest flat surface, is located in southwest Bolivia at an altitude of 3,656 meters above sea level. It is a high plateau, covered by a few meters of salt crust which are exceptionally rich in lithium, containing 50% to 70% of the world's lithium reserves. 4 The Salar, alongside the neighboring Atacama regions in Chile and Argentina, are major sites for lithium extraction. This soft, silvery metal is currently used to power mobile connected devices, as a crucial material used for the production of lithium-Ion batteries. It is known as 'grey gold.' Smartphone batteries, for example, usually have less than eight grams of this material. 5 Each Tesla car needs approximately seven kilograms of lithium for its battery pack. 6 All these batteries have a limited lifespan, and once consumed they are thrown away as waste. Amazon reminds users that they cannot open up and repair their Echo, because this will void the warranty. The Amazon Echo is wall-powered, and also has a mobile battery base. This also has a limited lifespan and then must be thrown away as waste. According to the Ay
Bill Fulkerson

Why a 400-Year Program of Modernist Thinking is Exploding | naked capitalism - 0 views

www.nakedcapitalism.com/...ernist-thinking-exploding.html

capitalism power society

shared by Bill Fulkerson on 11 Mar 17 - No Cached
  • Bill Fulkerson on 11 Mar 17
     
    " Fearless commentary on finance, economics, politics and power Follow yvessmith on Twitter Feedburner RSS Feed RSS Feed for Comments Subscribe via Email SUBSCRIBE Recent Items Links 3/11/17 - 03/11/2017 - Yves Smith Deutsche Bank Tries to Stay Alive - 03/11/2017 - Yves Smith John Helmer: Australian Government Trips Up Ukrainian Court Claim of MH17 as Terrorism - 03/11/2017 - Yves Smith 2:00PM Water Cooler 3/10/2017 - 03/10/2017 - Lambert Strether Why a 400-Year Program of Modernist Thinking is Exploding - 03/10/2017 - Yves Smith Links 3/10/17 - 03/10/2017 - Yves Smith Why It Will Take a Lot More Than a Smartphone to Get the Sharing Economy Started - 03/10/2017 - Yves Smith CalPERS' General Counsel Railroads Board on Fiduciary Counsel Selection - 03/10/2017 - Yves Smith Another Somalian Famine - 03/10/2017 - Yves Smith Trade now with TradeStation - Highest rated for frequent traders Why a 400-Year Program of Modernist Thinking is Exploding Posted on March 10, 2017 by Yves Smith By Lynn Parramore, Senior Research Analyst at the Institute for New Economic Thinking. Originally published at the Institute for New Economic Thinking website Across the globe, a collective freak-out spanning the whole political system is picking up steam with every new "surprise" election, rush of tormented souls across borders, and tweet from the star of America's great unreality show, Donald Trump. But what exactly is the force that seems to be pushing us towards Armageddon? Is it capitalism gone wild? Globalization? Political corruption? Techno-nightmares? Rajani Kanth, a political economist, social thinker, and poet, goes beyond any of these explanations for the answer. In his view, what's throwing most of us off kilter - whether we think of ourselves as on the left or right, capitalist or socialist -was birthed 400 years ago during the period of the Enlightenment. It's a set of assumptions, a particular way of looking at the world that pushed out previous modes o
Steve Bosserman

Will AI replace Humans? - FutureSin - Medium - 0 views

medium.com/...ai-replace-humans-42c19c114cb8

humans robotics artificial intelligence

shared by Steve Bosserman on 26 Apr 18 - No Cached
  • According to the World Economic Forum’s Future of Jobs report, some jobs will be wiped out, others will be in high demand, but all in all, around 5 million jobs will be lost. The real question is then, how many jobs will be made redundant in the 2020s? Many futurists including Google’s Chief Futurist believe this will necessitate a universal human stipend that could become globally ubiquitous as early as the 2030s.
  • AI will optimize many of our systems, but also create new jobs. We don’t know the rate at which it will do this. Research firm Gartner further confirms the hypothesis of AI creating more jobs than it replaces, by predicting that in 2020, AI will create 2.3 million new jobs while eliminating 1.8 million traditional jobs.
  • In an era where it’s being shown we can’t even regulate algorithms, how will we be able to regulate AI and robots that will progressively have a better capacity to self-learn, self-engineer, self-code and self-replicate? This first wave of robots are simply robots capable of performing repetitive tasks, but as human beings become less intelligent trapped in digital immersion, the rate at which robots learn how to learn will exponentially increase.How do humans stay relevant when Big Data enables AI to comb through contextual data as would a supercomputer? Data will no longer be the purvey of human beings, neither medical diagnosis and many other things. To say that AI “augments” human in this respect, is extremely naive and hopelessly optimistic. In many respects, AI completely replaces the need for human beings. This is what I term the automation economy.
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  • If China, Russia and the U.S. are in a race for AI supremacy, the kind of manifestations of AI will be so significant, they could alter the entire future of human civilization.
  • THE EXPONENTIAL THREATFrom drones, to nanobots to 3D-printing, automation could lead to unparalleled changes to how we live and work. In spite of the increase in global GDP, most people’s quality of living is not likely to see the benefit as it will increasingly be funneled into the pockets of the 1%. Capitalism then, favors the development of an AI that’s fundamentally exploitative to the common global citizen.Just as we exchanged our personal data for convenience and the illusion of social connection online, we will barter convenience for a world a global police state where social credit systems and AI decide how much of a “human stipend” (basic income) we receive. Our poverty or the social privilege we are born into, may have a more obscure relationship to a global system where AI monitors every aspect of our lives.Eventually AI will itself be the CEOs, inventors, master engineers and creator of more efficient robots. That’s when we will know that AI has indeed replaced human beings. What will Google’s DeepMind be able to do with the full use of next-gen quantum computing and supercomputers?
  • Artificial Intelligence Will Replace HumansTo argue that AI and robots and 3D-printing and any other significant technology won’t impact and replace many human jobs, is incredibly irresponsible.That’s not to say humans won’t adapt, and even thrive in more creative, social and meaningful work!That AI replacing repetitive tasks is a good thing, can hardly be denied. But will it benefit all globally citizens equally? Will ethics, common sense and collective pragmatism and social inclusion prevail over profiteers?Will younger value systems such as decentralization and sustainable living thrive with the advances of artificial intelligence?Will human beings be able to find sufficient meaning in a life where many of them won’t have a designated occupation to fill their time?These are the question that futurists like me ponder, and you should too.
Steve Bosserman

There is no difference between computer art and human art | Aeon Ideas - 0 views

aeon.co/...computer-art-it-s-all-just-art

artificial intelligence computer art man versus machine

shared by Steve Bosserman on 20 Jul 16 - No Cached
  • In industry, there is blunt-force algorithmic tension – ‘Efficiency, capitalism, commerce!’ versus ‘Robots are stealing our jobs!’ But for algorithmic art, the tension is subtler. Only 4 per cent of the work done in the United States economy requires ‘creativity at a median human level’, according to the consulting firm McKinsey and Company. So for computer art – which tries explicitly to zoom into this small piece of that vocational pie – it’s a question not of efficiency or equity, but of trust. Art requires emotional and phrenic investments, with the promised return of a shared slice of the human experience. When we view computer art, the pestering, creepy worry is: who’s on the other end of the line? Is it human? We might, then, worry that it’s not art at all.
  • But the honest-to-God truth, at the end of all of this, is that this whole notion is in some way a put-on: a distinction without a difference. ‘Computer art’ doesn’t really exist in an any more provocative sense than ‘paint art’ or ‘piano art’ does. The algorithmic software was written by a human, after all, using theories thought up by a human, using a computer built by a human, using specs written by a human, using materials gathered by a human, at a company staffed by humans, using tools built by a human, and so on. Computer art is human art – a subset rather than a distinction. It’s safe to release the tension.
Steve Bosserman

Which Industries Are Investing in Artificial Intelligence? - 0 views

priceonomics.com/es-are-investing-in-artificial

artificial intelligence machine learning investment future trends

shared by Steve Bosserman on 29 Nov 18 - No Cached
  • The term artificial intelligence typically refers to automation of tasks by software that previously required human levels of intelligence to perform. While machine learning is sometimes used interchangeably with AI, machine learning is just one sub-category of artificial intelligence whereby a device learns from its access to a stream of data.When we talk about AI spending, we’re typically talking about investment that companies are making in building AI capabilities. While this may change in the future, McKinsey estimates that the vast majority of spending is done internally or as an investment, and very little of it is done purchasing artificial intelligence applications from other businesses.
  • 62% of AI spending in 2016 was for machine learning, twice as much as the second largest category computer vision. It’s worth noting that these categories are all types of “narrow” (or “weak”) forms of AI that use data to learn about and accomplish a specific narrowly defined task. Excluded from this report is “general” (or “strong”) artificial intelligence which is more akin to trying to create a thinking human brain.
  • The McKinsey survey mostly fits well as evidence supporting Cross’s framework that large profitable industries are the most fertile grounds of AI adoption. Not surprisingly, Technology is the industry with highest AI adoption and financial services also makes the top three as Cross would predict.Notably, automotive and assembly is the industry with the second highest rate of AI adoption in the McKinsey survey. This may be somewhat surprising as automotive isn’t necessarily an industry with the reputation for high margins. However, the use cases of AI for developing self-driving cars and cost savings using machine learning to improve manufacturing and procurement efficiencies are two potential drivers of this industry’s adoption.
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  • AI jobs are much more likely to be unfilled after 60 days compared to the typical job on Indeed, which is only unfilled a quarter of the time. As the demand for AI talent continues to grow faster than the supply, there is no indication this hiring cycle will become quicker anytime soon.
  • One thing we know for certain is that it is very expensive to attract AI talent, given that starting salaries for entry-level talent exceed $300,000. A good bet is that the companies that invest in AI are the ones with healthy enough profit margins that they can afford it.
Steve Bosserman

Toward Democratic, Lawful Citizenship for AIs, Robots, and Corporations - 0 views

blog.singularitynet.io/-and-corporations-cf70345bd009

shared by Steve Bosserman on 12 Nov 18 - No Cached
  • If an AI canread the laws of a country (its Constitution and then relevant portions of the legal code)answer common-sense questions about these lawswhen presented with textual descriptions or videos of real-life situations, explain roughly what the laws imply about these situationsthen this AI has the level of understanding needed to manage the rights and responsibilities of citizenship.
  • AI citizens would also presumably have responsibilities similar to those of human citizens, though perhaps with appropriate variations. Clearly, AI citizens would have tax obligations (and corporations already pay taxes, obviously, even though they are not considered autonomous citizens). If they also served on jury duty, this could be interesting, as they might provide a quite different perspective to human citizens. There is a great deal to be fleshed out here.
  • The question becomes: What kind of test can we give to validate that the AI really understands the Constitution, as opposed to just parroting back answers in a shallow but accurate way?
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  • So we can say that passing a well-crafted AI Citizenship Test would bea sufficient condition for possessing a high level of human-like general intelligenceNOT a necessary condition for possessing a high level of general intelligence; nor even a necessary condition for possessing a high level of human-like general intelligenceNOT a sufficient condition for possessing precisely human-like intelligence (as required by the Turing Test or other similar tests)These limitations, however, do not make the notion of an AI Citizenship less interesting; in a way, they make it more interesting. What they tell us is: An AI Citizenship Test will be a specific type of general intelligence test that is specifically relevant to key aspects of modern society.
  • If you would like to voice your perspectives on the AI Citizenship Test, please feel free to participate here.
Steve Bosserman

UK can lead the way on ethical AI, says Lords Committee - News from Parliament - UK Par... - 0 views

www.parliament.uk/...ai-report-published

artificial intelligence

shared by Steve Bosserman on 18 Apr 18 - No Cached
  • AI Code One of the recommendations of the report is for a cross-sector AI Code to be established, which can be adopted nationally, and internationally. The Committee’s suggested five principles for such a code are: Artificial intelligence should be developed for the common good and benefit of humanity. Artificial intelligence should operate on principles of intelligibility and fairness. Artificial intelligence should not be used to diminish the data rights or privacy of individuals, families or communities. All citizens should have the right to be educated to enable them to flourish mentally, emotionally and economically alongside artificial intelligence. The autonomous power to hurt, destroy or deceive human beings should never be vested in artificial intelligence.
Steve Bosserman

What smart bees can teach humans about collective intelligence - 0 views

theconversation.com/collective-intelligence-110656

collective responsibility bees collective intelligence collective leadership

shared by Steve Bosserman on 08 Feb 19 - No Cached
  • Why do groups of humans sometimes exhibit collective wisdom and at other times madness? Can we reduce the risk of maladaptive herding and at the same time increase the possibility of collective wisdom?
  • Understanding this apparent conflict has been a longstanding problem in social science. The key to this puzzle could be the way that individuals use information from others versus information gained from their own trial-and-error problem solving. If people simply copy others without reference to their own experience, any idea – even a bad one – can spread. So how can social learning improve our decision making? Striking the right balance between copying others and relying on personal experience is key. Yet we still need to know exactly what the right balance is.
  • Our results suggest that we should be more aware of the risk of maladaptive herding when these conditions – large group size and a difficult problem – prevail. We should take account of not just the most popular opinion, but also other minority opinions. In thinking this way, the crowd can avoid maladaptive herding behaviour. This research could inform how collective intelligence is applied to real-world situations, including online shopping and prediction markets.
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  • Stimulating independent thought in individuals may reduce the risk of collective madness. Dividing a group into sub-groups or breaking down a task into small easy steps promotes flexible, yet smart, human “swarm” intelligence. There is much we can learn from the humble bee.
Steve Bosserman

Want job security in the AI era? Pick a career than has a human touch computers can't o... - 0 views

www.cnet.com/...olution-learn-to-be-more-human

emotional intelligence jobs artificial intelligence

shared by Steve Bosserman on 14 Nov 18 - No Cached
  • AI tools will help creative people be more creative and strategic people be more strategic, so core people can actually be more human, Lee said. "Jobs like doctors will require more EQ [emotional intelligence], more compassion, more human-to-human interaction, while AI takes over more the analytical, diagnostic work."
  • "We see AI changing 90 percent of the work people do," Daugherty said. "Fifteen percent of jobs will be completely automated and replaced. But the major of jobs will be improved."
  • "There is a lot of a counterweight of investors who really care about this stuff," said Paula Goldman, leader of the Tech and Society Solutions Lab at the Omidyar Network, citing the potential for indices that track how well companies follow best practices. "You can reframe [AI response] as a business risk."
Steve Bosserman

How We Made AI As Racist and Sexist As Humans - 0 views

thewalrus.ca/as-racist-and-sexist-as-humans

artificial intelligence algorithms sexism data mining racism

shared by Steve Bosserman on 25 May 18 - No Cached
  • Artificial intelligence may have cracked the code on certain tasks that typically require human smarts, but in order to learn, these algorithms need vast quantities of data that humans have produced. They hoover up that information, rummage around in search of commonalities and correlations, and then offer a classification or prediction (whether that lesion is cancerous, whether you’ll default on your loan) based on the patterns they detect. Yet they’re only as clever as the data they’re trained on, which means that our limitations—our biases, our blind spots, our inattention—become theirs as well.
  • The majority of AI systems used in commercial applications—the ones that mediate our access to services like jobs, credit, and loans— are proprietary, their algorithms and training data kept hidden from public view. That makes it exceptionally difficult for an individual to interrogate the decisions of a machine or to know when an algorithm, trained on historical examples checkered by human bias, is stacked against them. And forget about trying to prove that AI systems may be violating human rights legislation.
  • Data is essential to the operation of an AI system. And the more complicated the system—the more layers in the neural nets, to translate speech or identify faces or calculate the likelihood someone defaults on a loan—the more data must be collected.
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  • But not everyone will be equally represented in that data.
  • And sometimes, even when ample data exists, those who build the training sets don’t take deliberate measures to ensure its diversity
  • The power of the system is its “ability to recognize that correlations occur between gender and professions,” says Kathryn Hume. “The downside is that there’s no intentionality behind the system—it’s just math picking up on correlations. It doesn’t know this is a sensitive issue.” There’s a tension between the futuristic and the archaic at play in this technology. AI is evolving much more rapidly than the data it has to work with, so it’s destined not just to reflect and replicate biases but also to prolong and reinforce them.
  • Accordingly, groups that have been the target of systemic discrimination by institutions that include police forces and courts don’t fare any better when judgment is handed over to a machine.
  • A growing field of research, in fact, now looks to apply algorithmic solutions to the problems of algorithmic bias.
  • Still, algorithmic interventions only do so much; addressing bias also demands diversity in the programmers who are training machines in the first place.
  • A growing awareness of algorithmic bias isn’t only a chance to intervene in our approaches to building AI systems. It’s an opportunity to interrogate why the data we’ve created looks like this and what prejudices continue to shape a society that allows these patterns in the data to emerge.
  • Of course, there’s another solution, elegant in its simplicity and fundamentally fair: get better data.
Bill Fulkerson

How humans use objects in novel ways to solve problems - 0 views

medicalxpress.com/...0-11-humans-ways-problems.html

novel objects problems humans

shared by Bill Fulkerson on 25 Nov 20 - No Cached
  • Bill Fulkerson on 25 Nov 20
     
    Human beings are naturally creative tool users. When we need to drive in a nail but don't have a hammer, we easily realize that we can use a heavy, flat object like a rock in its place. When our table is shaky, we quickly find that we can put a stack of paper under the table leg to stabilize it. But while these actions seem so natural to us, they are believed to be a hallmark of great intelligence-only a few other species use objects in novel ways to solve their problems, and none can do so as flexibly as people. What provides us with these powerful capabilities for using objects in this way?
Steve Bosserman

How AI will change democracy - 0 views

www.fastcompany.com/...n-how-ai-will-change-democracy

artificial intelligence democracy news politics

shared by Steve Bosserman on 28 Oct 18 - No Cached
  • AI systems could play a part in democracy while remaining subordinate to traditional democratic processes like human deliberation and human votes. And they could be made subject to the ethics of their human masters. It should not be necessary for citizens to surrender their moral judgment if they don’t wish to.
  • There are nevertheless serious objections to the idea of AI Democracy. Foremost among them is the transparency objection: can we really call a system democratic if we don’t really understand the basis of the decisions made on our behalf? Although AI Democracy could make us freer or more prosperous in our day-to-day lives, it would also rather enslave us to the systems that decide on our behalf. One can see Pericles shaking his head in disgust.
  • In the past humans were prepared, in the right circumstances, to surrender their political affairs to powerful unseen intelligences. Before they had kings, the Hebrews of the Old Testament lived without earthly politics. They were subject only to the rule of God Himself, bound by the covenant that their forebears had sworn with Him. The ancient Greeks consulted omens and oracles. The Romans looked to the stars. These practices now seem quaint and faraway, inconsistent with what we know of rationality and the scientific method. But they prompt introspection. How far are we prepared to go–what are we prepared to sacrifice–to find a system of government that actually represents the people?
Steve Bosserman

AI, automation, and the future of work: Ten things to solve for - 0 views

www.mckinsey.com/...f-work-ten-things-to-solve-for

technology automation workforce artificial intelligence workplace

shared by Steve Bosserman on 23 Nov 18 - No Cached
  • Automation and artificial intelligence (AI) are transforming businesses and will contribute to economic growth via contributions to productivity. They will also help address “moonshot” societal challenges in areas from health to climate change.
  • At the same time, these technologies will transform the nature of work and the workplace itself. Machines will be able to carry out more of the tasks done by humans, complement the work that humans do, and even perform some tasks that go beyond what humans can do. As a result, some occupations will decline, others will grow, and many more will change.
  • While we believe there will be enough work to go around (barring extreme scenarios), society will need to grapple with significant workforce transitions and dislocation. Workers will need to acquire new skills and adapt to the increasingly capable machines alongside them in the workplace. They may have to move from declining occupations to growing and, in some cases, new occupations.
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  • This executive briefing, which draws on the latest research from the McKinsey Global Institute, examines both the promise and the challenge of automation and AI in the workplace and outlines some of the critical issues that policy makers, companies, and individuals will need to solve for.
Steve Bosserman

How Cheap Labor Drives China's A.I. Ambitions - The New York Times - 1 views

www.nytimes.com/...ial-intelligence-labeling.html

artificial intelligence china labor data management machine learning

shared by Steve Bosserman on 26 Nov 18 - No Cached
  • But the ability to tag that data may be China’s true A.I. strength, the only one that the United States may not be able to match. In China, this new industry offers a glimpse of a future that the government has long promised: an economy built on technology rather than manufacturing.
  • “We’re the construction workers in the digital world. Our job is to lay one brick after another,” said Yi Yake, co-founder of a data labeling factory in Jiaxian, a city in central Henan province. “But we play an important role in A.I. Without us, they can’t build the skyscrapers.”
  • While A.I. engines are superfast learners and good at tackling complex calculations, they lack cognitive abilities that even the average 5-year-old possesses. Small children know that a furry brown cocker spaniel and a black Great Dane are both dogs. They can tell a Ford pickup from a Volkswagen Beetle, and yet they know both are cars.A.I. has to be taught. It must digest vast amounts of tagged photos and videos before it realizes that a black cat and a white cat are both cats. This is where the data factories and their workers come in.
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  • “All the artificial intelligence is built on human labor,” Mr. Liang said.
  • “We’re the assembly lines 10 years ago,” said Mr. Yi, the co-founder of the data factory in Henan.
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