Why do American CEOs get paid so much? | James K Galbraith | Opinion | The Guardian - 0 views
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"new report from the Economic Policy Institute calls attention to the hardy perennial of how much America's corporate titans make: bosses of the top 350 firms made an average of $18.9m in 2017. That's a ratio of 312-1 over the median worker in their industries. Big bucks to be sure. And a big change since 1965, when the ratio was just 20-1. But what does it mean? And if there's a problem, what is it, exactly? What it means, as the EPI economists carefully document, is that the top US corporate chiefs are paid overwhelmingly with stock options, and their income fluctuates with the market. About 80% of the pay packet is in stocks, and the rise of 17% in 2017 after two flat years surely suggests that the top CEOs (not unreasonably) sensed the market peaked last year. So they cashed in. On the other 20% of the pay packets, no gains occurred"
How to Make Property Work Better for Society - 0 views
The Making of Great Hypothesis - Towards Data Science - 0 views
Making sense of systems complexity: practical systems thinking - workshop - 0 views
About - Catalog - 0 views
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"We are developing next generation technology to store digital information in DNA molecules. Our vision is to fit the information content of entire data centers in the palm of your hand. We have proven our approach to encoding data in DNA and are in the process of scaling up our platform. CATALOG technology will make it economically attractive to use DNA as a medium for long-term archival of data."
To Make Sense of the Present, Brains May Predict the Future | Quanta Magazine - 0 views
The Decision Matrix: How to Prioritize What Matters - 0 views
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"Consequential and irreversible decisions are the ones that you really need to focus on. All of the time I saved from using this matrix didn't allow me to sip drinks on the beach. Rather, I invested it in the most important decisions, the ones I couldn't justify delegating. I also had another rule that proved helpful: unless the decision needed to be made on the spot, as some operational decisions do, I would take a 30-minute walk first. The key to successfully employing this in practice was to make sure everyone was on same page with the terms of consequential and reversible. At first, people checked with me but later, as the terms became clear, they just started deciding."
Do Participation Trophies Actually Make Kids Worse Off? - 0 views
Decision Making under Deep Uncertainty - 0 views
Another Way Climate Change Might Make Hurricanes Worse - 0 views
Rory Sutherland on The Psychology of Advertising, Complex Evolved Systems, Reading, Dec... - 0 views
Researchers say they've figured out what makes people reject science, and it's not igno... - 0 views
Which Industries Are Investing in Artificial Intelligence? - 0 views
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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.
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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.
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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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Are we living in a post-truth era? Yes, but that's because we're a post-truth species. - 0 views
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A cursory look at history reveals that propaganda and disinformation are nothing new. In fact, humans have always lived in the age of post-truth. Homo sapiens is a post-truth species, who conquered this planet thanks above all to the unique human ability to create and spread fictions. We are the only mammals that can cooperate with numerous strangers because only we can invent fictional stories, spread them around, and convince millions of others to believe in them. As long as everybody believes in the same fictions, we all obey the same laws and can thereby cooperate effectively.
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The truth is, truth has never been high on the agenda of Homo sapiens. If you stick to unalloyed reality, few people will follow you. False stories have an intrinsic advantage over the truth when it comes to uniting people. If you want to gauge group loyalty, requiring people to believe an absurdity is a far better test than asking them to believe the truth. If the chief says the sun rises in the west and sets in the east, only true loyalists will clap their hands. Similarly, if all your neighbors believe the same outrageous tale, you can count on them to stand together in times of crisis. If they are willing to believe only accredited facts, what does that prove?
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Yet the difference between holy books and money is far smaller than it might seem. When most people see a dollar bill, they forget that it is just a human convention. As they see the green piece of paper with the picture of the dead white man, they see it as something valuable in and of itself. They hardly ever remind themselves, “Actually, this is a worthless piece of paper, but because other people view it as valuable, I can make use of it.” If you observed a human brain in an fMRI scanner, you would see that as someone is presented with a suitcase full of hundred-dollar bills, the parts of the brain that start buzzing with excitement are not the skeptical parts but the greedy parts. Conversely, in the vast majority of cases people begin to sanctify the Bible or the Vedas only after long and repeated exposure to others who view it as sacred. We learn to respect holy books in exactly the same way we learn to respect paper currency.
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