The big data age can't be like "brother"

(source from FT, Tiger-smelling compilation)

After Edward Snowden exposed the NSA, sales of George Orwell's book "1984" increased. In the present case, even though people do not like Big Brother spying on themselves, they are prepared to accept the cost of being offended by privacy in exchange for security.

What about "Big data"? Fast-growing personal data is in the hands of companies that use new data analysis and artificial intelligence technologies to improve their products and services and to anticipate customer needs. Larry Page, Google's chief executive, described his ideal technology as "a truly intelligent assistant who can help people do things, and we don't have to worry about it."

Imagine living in a virtual Downton Manor (Downton Abbey), there is a computer to help you plan a day, give the best route advice on travel, movies you might want to watch and the most appropriate flights--and even tickets for you--it's tempting. We are all in a hurry and want a simple and easy life. As long as you are not bombarded with information or forced to lose your choice, a personal assistant service is good.

But the NSA surveillance was a surprise to everyone, and although the surveillance program has been around for 60 years, I wonder if many people can understand how much data they are making every day, or whether they know what technology is going on today-a handful of big data companies are already digging for data. Technology has grown so fast that what was thought to be impossible two years ago is now commonplace.

"The future is both exciting and frightening," he said. Companies with huge amounts of data even know who you are. They can predict what you might do below, "said Lee. He is the former CEO of Google China and is currently investing in Beijing.

In a column last week I compared Google to ge in 19th century-an innovative industrial company with the power to develop new technologies. The downside is that Google, Amazon, Microsoft and other tech giants are accumulating their own strength, and need to be carefully controlled.

The NSA and big data companies use their databases and computing power in different places-one for discovering spies and terrorists, and one for matching services to users. They have similarities to the use of large-scale databases, such as pattern recognition and network analysis.

Further, this involves AI techniques, such as analyzing the search for user input keywords, translating speeches into another language in real time (as Microsoft demonstrated in China last year), and learning to distinguish a cat's photos by reading thousands of images.

The ability of computers to learn about human convergence is called "deep learning" (deep learning), and it is noteworthy that Google has hired several frontier scholars in the field, including scientists, writers Rey Kuzwer (Ray Kurzweil). The NSA has "Advanced machine learning Technology" in the transfer of technology to US private companies.

This software can predict many things from information fragments, as long as the debris is sufficient, as if the NSA gets phone calls from carrier Verizon to dial metadata and analyze it. President Obama assured U.S. citizens that "no one is eavesdropping on your phone," but just dialing a record is enough.

A study by Harvard University Professor Latanya Swinnie (LaTanya Sweeney) shows that 87% of people can be identified by age, sex, and postcode, as long as they are cross-referenced (cross-checked) in the public database. This is precisely the data that social networks and internet companies typically collect.

The astonishing power of big data companies comes from the fact that they can integrate their personal data, which covers what goods they buy, where they are located (collected by GPs from mobile phones). This generates a set of "speculative data" (inferred) about the customer's intent.

For example, if I used an Android phone to search for "the Taj Mahal" in India, Google would give priority to the results of the temple in Uttar Pradesh (Uttar Pradesh). If I'm in Brick Street east of London, Brick Lane, I will return to the local Bengal Flavor restaurant results. It is not difficult to implement a restaurant reservation service based on my evaluation record.

On the one hand, if you do this (as long as it's a good restaurant) I'll be happy to save some of my operations. On the other hand, as the 9374.html > World Economic Forum Report on personal data says: "Predicting the data gives the impression that the omniscient big Brother is staring at the surveillance tape." ”

One of the worries is that big data companies that have the ability to master such software are hard to contend with. The more data I and other users provide, the more accurate they are at predicting our intentions. The more the machine brain uses the smarter it is.

Another is concerned with trust. Social networks do poorly to protect user data, and they only have a small fragment of information about user behavior, habits, and willingness. It is clear why the NSA is targeting social networks as a target--nsa, and they need data materials.

The 3rd is the question of ownership. We all have a certain right to our information. But what would happen if the information and other people's information were integrated into a massive willingness database? If I change my mind, how do I get the information back to the status quo?

Most importantly, we don't know what this technology means because we're still in the early stages of the big data age. Admittedly, big data has many places to spend, but it takes some time for people to love it.

(Responsible editor: The good of the Legacy)