Free PDF , by Scott Hartley
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, by Scott Hartley
Free PDF , by Scott Hartley
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Product details
File Size: 2345 KB
Print Length: 309 pages
Publisher: Houghton Mifflin Harcourt; Reprint edition (April 25, 2017)
Publication Date: April 25, 2017
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B01I4FPMGO
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#288,312 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
Hartley is a venture capitalist who in the past has worked for Google and Facebook, been a Presidential Innovation Fellow at the White House and worked at Harvard’s Berkman Klein Center for Internet and Society. His goal in this interesting and generally well researched book is not to show that being educated a fuzzy (majoring in college the humanities or social sciences) is better than being educated a techie (the STEM disciplines of science, technology, engineering and math). Rather, for technology to work optimally, the two approaches, techie and fuzzy, need to be blended. That also means that in the foreseeable future, there are, and will be, jobs for fuzzies as well as techies, and not just as barristas at Starbuck’s or behind the counter at McDonald’s. There are illuminating passages that illustrate just where and how fuzzies can fit into an increasingly technologized business environment. Thus, Harvard psychologist Joshua Greene, in an article on driverless cars and the challenges they pose to design, writes that machine decision-making “is more philosophical than technical. Before we can put our values into machines, we have to figure out how to make our values clear and consistent.†Shyam Sankar, director of Palantir Technologies, a $20 billion firm that designs analytics platforms for security and police work, states that human intelligence is essential to stay ahead of the curve: “Terrorists are always adapting… Computers don’t detect novel patterns and new behaviors. Humans do.†What do fuzzies bring to this world? Hartley emphasizes flexibility, breadth versus depth and the ability to bridge disciplines (especially important today), ethical orientation. He stresses too that many of the ‘soft’ disciplines do in practice train students in intellectually sophisticated mathematical and statistical analysis, or, conversely, in rigorous ‘philosophical’ thinking. Lastly, machines are built to serve humans, and human needs, and humankind has problems of its own which technology can help to solve (or at least abate). Here too, people need to collaborate across disciplines to address complicated, human-centric design and sales problems. Hartley roams wide in topics discussed and examples cited. If occasionally, he veers over into boosterism, he deserves to be cut slack because, over all, this is a worthwhile and eminently readable book on a topic that should be of interest to all of us.
Scott Hartley's soft and informative touch on a topic that affects us all is great. He constantly references organizations, people, and events that bring evidence to his claims. I appreciate that his insight is backed by a world perspective. As a fuzzy that is constantly questioning if I am living in the wrong century, Scott gives me a sense of ease knowing that a balance must be maintained for society to thrive."As "software eats the world," technology requires input and expertise from every corner of society. We need more techies in traditionally fuzzy institutions such as our government, and we need more fuzzies building tech companies. Our technology ought to augment rather than replace, and ought to provide us with great hope rather than great fear."
As a techie who has obsessed, worried, and generally just been quite skeptical over the chance non-techies have in surviving the potential automation explosion that could soon come, I found myself relieved to FINALLY find such a convincing argument that the future may be bright after all for both "fuzzies" and techies alike. Prior to reading this, I had come across the Oxford study (that is also discussed in the book) which estimated some 47% of jobs would be automated in the next one to two decades. This study initially rang true to my intuition, as I had been involved in programming several products which were responsible for automating away many manual, repetitive jobs. Having done these jobs, I really couldn't see any end in sight to the potential automation wave that could really create a dire future for any non-techies.But, Hartley presents many studies in the book which contradict these findings - the most prominent of which I found to be the Mckinsey study -which states the number is probably closer to about 5%. More importantly, though, throughout the book he gives several explanatory models explaining WHY many jobs will survive automation, as well as why many "fuzzy" jobs will need to be created and even why these fuzzy jobs will be complex, high skilled and high value jobs. These models further *qualitatively* distinguish what jobs are ripe for automation, and what jobs (or potential jobs) are best served by "fuzzy" skills. The core concept that governs these models is complexity. By looking at a given job, these models highlight both the *magnitude* of complexity, as well as the *type* of complexity. For example, Hartley uses the Cynefin framework to distinguish between tasks that are simple, complicated, complex, chaotic, or disordered. Each of these categories are governed by the structure of the cause and effect relationships which dictate the required action of the person (or job/role) in effectively carrying out a required task. I found models like this to give me an incredibly simple and useful way for organizing and making sense of this topic, where previously I could feel myself floundering to pull together the essential governing laws of the debate.Besides this, the book is filled with a really nice blend of hard data and entertaining stories, that allows for a convincing argument in an entertaining way. I had one or two disagreements, where I thought the role of a "fuzzie" was slightly over-exaggerated - or at the very least was likely to be more valuable supplementally rather than critically. But, on the whole, I found myself mostly nodding in agreement with my own experience, where I have personally found many of the tech claims - especially those involving machine learning, AI, neural nets, etc - to be highly over-exaggerated, as well as the many times in my own work-life experience I have seen just how invaluable fuzzies can be in the right domains. The one benefit I did not expect to get from this book was just how much it could help me to not only appreciate more what "fuzzies" do in the current workplace, but also how to help and support their future in the workplace as we create more meaningful, cooperative, and fun environments where more people feel valued and important in these collective, creative engagements (that we so boringly call jobs) as we humans march forward into the totally unknown and exciting future that lays ahead of us
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