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12-Dec-2017 18:35

[See “About this canvassing of experts” for further details about the limits of this sample.] Participants were asked to explain their answers, and most wrote detailed elaborations that provide insights about hopeful and concerning trends.Respondents were allowed to respond anonymously; these constitute a slight majority of the written elaborations.However, sometimes the application of algorithms created with good intentions leads to unintended consequences.

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The question now is, how to better understand and manage what we have done? And most importantly for those who don’t create algorithms for a living – how do we educate ourselves about the way they work, where they are in operation, what assumptions and biases are inherent in them, and how to keep them transparent?The 37% Rule, optimal stopping and other algorithmic conclusions are evidence-based guides that enable us to use wisdom and mathematically verified steps to make better decisions. In a technological recapitulation of what spiritual teachers have been saying for centuries, our things are demonstrating that everything is – or can be – connected to everything else. Our systems do not have, and we need to build in, what David Gelernter called ‘topsight,’ the ability to not only create technological solutions but also see and explore their consequences before we build business models, companies and markets on their strengths, and especially on their limitations.” Chudakov added that this is especially necessary because in the next decade and beyond, “By expanding collection and analysis of data and the resulting application of this information, a layer of intelligence or thinking manipulation is added to processes and objects that previously did not have that layer.Algorithms with the persistence and ubiquity of insects will automate processes that used to require human manipulation and thinking. A grocery can suggest a healthy combination of meats and vegetables for dinner. “The main negative changes come down to a simple but now quite difficult question: How can we see, and fully understand the implications of, the algorithms programmed into everyday actions and decisions? So prediction possibilities follow us around like a pet.That, by itself, is a tall order that requires impartial experts backtracking through the technology development process to find the models and formulae that originated the algorithms.

Then, keeping all that learning at hand, the experts need to soberly assess the benefits and deficits or risks the algorithms create. Who has the time, the budget and resources to investigate and recommend useful courses of action?

Deloitte Global predicted more than 80 of the world’s 100 largest enterprise software companies will have cognitive technologies – mediated by algorithms – integrated into their products by the end of 2016.




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