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Steve Bosserman

We need to feed a growing planet. Vegetables aren't the answer. - 0 views

www.washingtonpost.com/...6-8422-eac61c0ef74d_story.html

calories grains vegetables local foods nutrition

shared by Steve Bosserman on 16 Dec 16 - No Cached
  • Steve Bosserman on 16 Dec 16
     
    Vegetables from local food sources insufficient to meet the caloric and nutritional demands of a growing population
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
Bill Fulkerson

It's not all Pepes and trollfaces - memes can be a force for good - The Verge - 0 views

www.theverge.com/...d-behavioral-science-nazi-pepe

memes

shared by Bill Fulkerson on 30 Aug 18 - No Cached
  • Bill Fulkerson on 30 Aug 18
     
    "How the 'emotional contagion' of memes makes them the internet's moral conscience By Allie Volpe Aug 27, 2018, 11:30am EDT Illustration by Alex Castro & Keegan Larwin SHARE Newly single, Jason Donahoe was perusing Tinder for the first time since it started integrating users' Instagram feeds. Suddenly, he had an idea: follow the Instagram accounts of some of the women he'd been interested in but didn't match with on the dating service. A few days later, he considered taking it a step further and direct messaging one of the women on Instagram. After all, the new interface of the dating app seemed to encourage users to explore other areas of potential matches' online lives, so why not take the initiative to reach out? Before he had a chance, however, he came across the profile of another woman whose Tinder photo spread featured a meme with Parks and Recreation character Jean-Ralphio Saperstein (Ben Schwartz) leaning into the face of Ben Wyatt (Adam Scott) with the caption: hey I saw you on Tinder but we didn't match so I found your Instagram you're so beautiful you don't need to wear all that makeup ahah I bet you get a lot of creepy dm's but I'm not like all those other guys message me back beautiful btw what's your snap "I was like, 'Oh shit, wow,'" Donahoe says. Seeing his potential jerk move laid out so plainly as a neatly generalized joke, he saw it in a new light. "I knew a) to be aware of that, and b) to cut that shit out … It prompted self-reflection on my part." THE MOST SUCCESSFUL MEMES STRIKE A CULTURAL CHORD AND CAN GUIDE AND EVEN INFLUENCE BEHAVIOR Donahoe says memes have resonated with him particularly when they depict a "worse, extreme version" of himself. For Donahoe, the most successful memes are more than just jokes. They "strike a societal, cultural chord" and can be a potent cocktail for self-reflection as tools that can guide and even influence behavior. In the months leading up to the 2016 US
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 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.
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