What is big data and how does it affect our lives? What are the dark and negative aspects of metropolitan data? How can you get rid of bigotry? These are the questions that the book intends to answer.
In general, with the advancement of technology and the creation of new technological tools, the question first arises whether this technology will be to our advantage or to our detriment? Better yet, does the benefits of this new technology outweigh its disadvantages? The metropolitan is no exception. In recent years, with the beginning of the Fourth Industrial Revolution , many technologies have entered and will enter our world; Technologies such as artificial intelligence , the Internet of Things, metadata, cloud computing , and more. Along with the entry of these technologies into our world, there have been discussions about the social and moral limits of these technologies and how far these technologies can enter our world.
For example, his acclaimed film (Her) deals with how electronic devices such as the Internet, artificial intelligence, etc. have turned humans away from each other and turned them into separate atomic atoms. The West World series also explores how powerful the combination of artificial intelligence and macro data provides the owners of this technology to control our world so that they can discover the essence of our existence.
The Big Data Book is not an apocalyptic story that sees technology as a whole set of pros and cons and ignores its benefits; Rather, it seeks to make people understand that while they can take advantage of macroeconomic benefits to live a more comfortable life, they can prevent the negative effects of this technology on their biosocial consciousness by being aware of the harms of macroeconomics.
The present book consists of seven chapters, each of which deals with one aspect of this technology:
We know what you think
Knowing people's interests and preferences can help businesses deliver very successful services to the community. One successful example is Netflix's acclaimed series House of Cards . The series' producers contacted several networks in 2011 to get a budget for a trial program. At the time, a political series had long failed to succeed. With such a background, television networks refused to invest in the series; But Netflix, with its massive data on its customers, knew that such a series would be popular. So instead of producing experimental programs, he already paid $ 100 million to produce the first two series, for a total of 26 episodes.
Of course, this wasn't the only Netflix use of the data; Even during the production of the series, they used the big data to direct it; But the use of big data doesn't guarantee success, just as Netflix has a lot of failed series and movies in its track record.
In this chapter, the author gives the history of Saraghgh and goes to the metropolis. It can be said that the ancestors of today's big data are the same censuses that the government used to do. You may be surprised to learn that there was a fear of bigotry at the time. The main fear was that the information of the citizens might reach the enemies and they might use this information against the country.
Also, the author deals with the limitations and deceptions that may be present in the sleeve. For example, the author claims that no matter how powerful the macro-tools we have, it is not possible to accurately predict the weather for more than two days. In addition, the risks of misleading conclusions must be considered. For example, if the increase in temperature in the early summer leads to a threefold increase in meat sales, it cannot be concluded that this increase in temperature has caused that amount of sales; This is because a similar increase in temperature may not have such an effect in late summer or any other time. The author emphasizes that we must always be careful about our conclusions about macro data, and for this situation he has invented the term GIGO .
Garbage stands for garbage in, garbage out, and means: If you import garbage, garbage will come out. No matter how good your system is, if the data you give it is rubbish, you will get nothing but occupation. Of course, if you run the system without a mechanism that can detect junk, the system may give you results that are correct. Of course, this is not the true result of a reflection of the real world; Rather, the system operates in the world it has created and accidentally gives you the right answer.
Buy enough to survive
One of the areas that the metropolitan area has changed is the retail sector. Here is an interesting story from the experience of buying a camera: