On a recent visit to a nearby hospital, I realized that Dr. Google nowadays appears to understand more than our family medicine specialist. While in the consultation unit I explained my condition to a somewhat tousled and exhausted nurse. He listened keenly and then requested for a minute as he keyed in certain phrases into Google. “Precisely then,” the nurse continued cheerfully,” you are suffering from…” and continue to evaluate my sickness and recommend the right medicine to deal with my situation. I was left wondering.
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What was the nurse undertaking searching it up from Google? I anticipated that the nurse would possess sufficient know-how to understand what I was suffering from. And what would happen in case the internet is nonfunctional? Would the nurse just assume?
This reminded me of this situation and my response to issues arising while analyzing Super Crunchers. The author’s recent work tackles this very query-what are the correct applications of information and how can lessons are drawn from the book be utilized together with the perception and know-how of this doctor? Ian Ayres, a professor and lecturer of law, has published an informative and greatly relevant material that rests simply along with such topics as “The Tipping Point” and “Blink”.
Ayres’s core objective is for people to remain focused at certain important periods in history-perceptive decision making processes are currently being replaced with information crunching and may in the future be surpassed by it. Ian holds that he that refuses to appreciate the power of greatly supported information examination will forfeit his/her economical advantage and may in future fall behind he that adopts the likelihoods of this new sector (Ayres 23).
Ian claims that a few elements have made the gathering, evaluation, and application of information necessary instruments for the state, organization, and clients. As the data storage costs decrease it turns out to be possible for an organization to gather and stock up large volumes of information. Additionally, a rising volume of business deals are “digital” therefore the gathering of information has become less expensive and faster (Ayres 23). The two elements coupled with the rising use of laptops imply that information-founded decision-making is among the rapidly expanding and most significant establishments in the contemporary world.
All through the book, Ian utilizes the phrase “super crunching” as an implication for the informal but more popularly utilized phrase “data mining”. For the last two decades, information mining has originated from the associated sectors of descriptive statistics, nonnatural acumen, electronic information processing (EIP), and learning organizations. Information mining differentiates itself from such fields since it deals with a large data store that is valued in terabytes (1012 bytes). Information mining involves digging out forecasts, trends, and extra beneficial data from huge data banks in a manner that normal people (with basic education) can understand (Ayres 59). Because information is continuously being increased to remote data banks, information searching is also dependent on authentic retrieval of useful data and forecasts.
The author begins his book of super crunching through quoting from online sites like Amazon.com which comprises often read papers, current lyrics, or commonly utilized bookmarks. Ayres utilizes these websites to explain how technologies are replacing professionals.
Previously people achieved networks through friends and relatives. Of late people pursue the direction of an online site. He pursues the same trend by showing how an internet-focused match-referral service and a hiring company uses authentic information gathering and potential regression frameworks in predicting how effective potential matches will be (Ayres 68). In the past, people followed the choice of colleagues, close friends, and relatives when proposing these alliances. Nowadays people are directed, willingly or unwillingly, by the outcomes of an imaginary regression model.
The author illustrates that while an organization exploits the potential of crunching to increase profitability, users can also tap these emerging technologies to achieve healthier deals. Ayres provides the example of farecasts.com and other similar sites that not only report and compare present travel costs of flight fares but also predict whether or not these travel costs will increase or decrease in the next two days (Ayres 72).
Among the most captivating elements of the book is the application of random attempts to purposely determine whether or not the identified alterations would ideally yield the anticipated outcomes. The author explains how Capitals, one of the biggest providers of credit cards in the United States, utilized a random method to weigh possible phrasing of advertising rallies. The benefit of applying this method is that due to random metrics, the teams treated with the substitute phrasings are similar in all but a single element-variation in wordings. Also, the author explains how he utilized Google is testing two different topics, rendering super crunching something of children of the data mining situation (Ayres 123).
Tales like these whereby an organization uses its extensive monetary assets and technical experience in wringing money out of unsuspicious clients may appear distasteful to certain consumers. However, I found the model of random attempts explained in his book signing. The author explains the utilization of random methods in testing the effectiveness of suggested adjustments while implementing government policies (Ayres 132). Ayres clarifies the application of the random method through the Progression System used in Mexico’s health sector.
The concept of trying strategies before their introduction on a nation-wide and/or central standard is a nice one and until now it is weirdly not available in Australian practices (Ayres 178). All through the book, the author takes the reader on a journey through various topic sections comprising: probability, approximating baseball team members, the evidence-driven medical crisis, point-shaving during a basketball match, and perceptive learning. The above core issues support the utilization of information and technology to enhance decision-making in contemporary businesses.
Ideally, this is a compelling, educative, and excellently compiled piece. The book assumes the unspecialized background of math or regression analysis. For someone searching for a comprehensive explanation regarding information mining tactics, this book will not be of help. However, for amazing research on new developments in data mining, it is an important resource. The contents of the book are roughly absolutely focused on the United States and seldom quote studies or new programs happening elsewhere.
The book is subtitled “how everything could be forecasted”. This is going overboard. There has been a development in the United States to identify the kind and magnitude of the next terror attempt. In theory, this may be applicable but politically and morally the hypothesis tested to be offensive and was discontinued.
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In conclusion, now after reading this book will I be better when I am diagnosed or dropped from an opportunity I understand I could take because an algorithm program indicates I am more than qualified? Not really. But I would be knowledgeable regarding how such things happen and most likely be alert if I would require circumventing the constantly increasing technology.
Ayres, Ian. Super Crunchers: Why Thinking-by-Numbers Is the New Way to be Smart. New York: Bantam, 2007.