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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.
“Algorithms are a useful artifact to begin discussing the larger issue of the effects of technology-enabled assists in our lives. Like fish in a tank, we can see them swimming around and keep an eye on them.
“Algorithms are the new arbiters of human decision-making in almost any area we can imagine, from watching a movie (Affectiva emotion recognition) to buying a house (Zillow.com) to self-driving cars (Google).
Hacking, cyberattacks and cryptographic code-breaking exploit algorithms.
Self-learning and self-programming algorithms are now emerging, so it is possible that in the future algorithms will write many if not most algorithms.
Some are calling this the Age of Algorithms and predicting that the future of algorithms is tied to machine learning and deep learning that will get better and better at an ever-faster pace. Analysts like Aneesh Aneesh of Stanford University foresee algorithms taking over public and private activities in a new era of “algocratic governance” that supplants “bureaucratic hierarchies.” Others, like Harvard’s Shoshana Zuboff, describe the emergence of “surveillance capitalism” that organizes economic behavior in an “information civilization.” To illuminate current attitudes about the potential impacts of algorithms in the next decade, Pew Research Center and Elon University’s Imagining the Internet Center conducted a large-scale canvassing of technology experts, scholars, corporate practitioners and government leaders.
All of our extended thinking systems (algorithms fuel the software and connectivity that create extended thinking systems) demand more thinking – not less – and a more global perspective than we have previously managed.Following that introductory section there is a much more in-depth look at respondents’ thoughts tied to each of the themes. There is fairly uniform agreement among these respondents that algorithms are generally invisible to the public and there will be an exponential rise in their influence in the next decade.A representative statement of this view came from Barry Chudakov, founder and principal at Sertain Research and Stream Fuzion Corp.These findings do not represent all the points of view that are possible to a question like this, but they do reveal a wide range of valuable observations based on current trends.In the next section we offer a brief outline of seven key themes found among the written elaborations.
We need to ask them to think about their thinking – to look out for pitfalls and inherent biases before those are baked in and harder to remove.