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Steve Bosserman

What if the Government Gave Everyone a Paycheck? - The New York Times - 0 views

  • A world inhabited only by robots, their billionaire owners and a large and increasingly restive population is the plotline for countless dystopian fantasies, but it’s a reality that appears to be drawing closer. If we continue on the path we’re on, we will need to make fundamental choices about how to support human livelihoods and ensure equal participation in our economy and society. Most basically, we will have to confront the realities of vastly unequal economic and political power. Even if we manage to enact a U.B.I., it will not be nearly enough.
Steve Bosserman

Why I am afraid of global cooling - Nexus Newsfeed - 0 views

  • I think we already have enough of the quantifiable (although it is poorly distributed, a separate though deeply related issue). What we need more of are the things that are hard to quantify. The rising tide of suicide and depression in the developed world is not caused by shrinking residential floor space or lack of access to 4G cell service. It probably has something to do with the disintegration of community, the withering of connection, loss of purpose and meaning, chronic pain and unresolved trauma, unprocessed grief, ambient anxiety, and the other accoutrements of Separation. This point seems obvious here at my brother’s farm where I write this, because my life is rich here; rich in relationship to the natural world through my hands, my senses, my labor, and yes, my bare feet, and rich in relationship to the human world as well through shared labor, common purpose, and mutual reliance. And the point seems equally unobvious when I’m separated from all these things. In the busy world of cars and clocks and screens, faster and more of them seems like progress.
Steve Bosserman

Facial recognition software recognized a Chinese fugitive in a crowd of 60,000 people - 1 views

  • Unfortunately, AI can’t recognize all types of people equally. An MIT study called Gender Shades showed how some AI can fail to distinguish, or even recognize, brown faces.
Steve Bosserman

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

  • 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

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

  • 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.
Steve Bosserman

The Time Based Economy - Amar SINGH Kaleka - Medium - 0 views

  • If it works, then why in the world are we not basing our whole economy on the finite construct of “time”? It would nearly be infallible, versus the legacy commodities model, which is full of holes and reject-able logic.A “time based economy” can be used with any nation state, group, or community based economics model. To make it simple, the value at the transaction would be time dollars in the form of a digital debit.
  • In the time based economy, each person enrolled, anywhere in the world would have an online account which is controlled by the debit card (not a citizenship card).
  • The time based economy primarily functions through the education, civics, and knowledge sector.
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  • This new education model would then become the basis of the global economy, like the base of a pyramid. During these years, and throughout their education, each child would pay for their own education through “time dollars”.
  • It would become the first global economy which standardizes and binds the economic trade of all market forces, known and unknown, to the only universal equality on this planet: time.
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