You Can’t Be Discreet Online

Essay 2: Writing a Summary

Throughout your academic career, you will be asked to read and respond to texts. Writing a summary prepares you for reading a text critically and responding to it.

Choose one of the two articles your group selected. In a 1 – 1 ½ page essay, summarize the text accurately and objectively.

Your summary should include:

· The author’s claim

· The title of the text and the full name of the author (the first time you mention the text)

· The author’s reasoning (focusing on the author’s main points)

· The use of signal phrases (like “The author suggests…” or “S/he explains that…”) to indicate the ideas are the author’s (not yours)

· Effective use of transitions to indicate a flow of ideas

· About 350 words (or 1 ½ pages)

Hints and Tips

Focus on the argument.

The point of summary is to identify what you think are the most important aspects of the article that your readers should know about. Do not try to repeat everything in the article. When you try to decide what to include or what to leave out, consider the amount of time the original author spends on the subject. Is this something that the author considers for three to four paragraphs? If so, it should probably receive a bit more attention in your summary. It might help you to look at the article paragraph by paragraph and try to sum each paragraph up. Sometimes paragraphs can be combined in your summary with one or two descriptive sentences. Your summary should discuss the article’s points in the same order as they appear in the original.

Stay focused on your purpose.

Your goal is to describe the article to your reader. In addition to explaining the author’s argument, you may bring in a discussion of the type of evidence used or the way the writer conveys their argument. For example, if there are a lot of charts and graphs or other visuals, you may want to mention that in your summary. Sometimes students tend to get off track and start describing the subject of the article and not the article itself, so be sure to keep in mind that what you are doing is summing up what this actual document says and does.

Remain objective.

One of the most important things to remember about your summary is that you should remain neutral when writing about the article. Do not include any judgments about whether or not the author is right about what he or she is saying, or whether he/she has a well written piece. All that should be included is a basic reporting of what goes on in the article.

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Use primarily your own words, not the author’s.

Be very careful when you are paraphrasing that you don’t repeat too much of the author’s language. It is appropriate to use direct quotes, but do so sparingly and be sure to use correct MLA format.

Grading

Your essay (worth a total of 100 points) will be graded using the following criteria:

Claim – The essay accurately identifies the author’s central claim. 10 points

Reasoning – The essay accurately and objectively represents the author’s key supporting points. The summary does not merely list the main ideas, but shows how the reasons support the claim. The summary is selective about details and examples, choosing only ones that help to illustrate a key point. 30 points

Quotations and Paraphrasing – The essay uses both quotations and paraphrasing that are appropriately integrated into the summary and response. Author’s ideas are effectively attributed using signal phrases. 10 points

Organization – Paper clearly and effectively presents the ideas. Transitions and paragraphing are used when appropriate. 20 points

Mechanics – Demonstrates a command of the standards of edited American English with no major grammatical errors. 20 points

MLA Format – Employs MLA format and documentation style, using in-text citations and including works cited page. Includes correct heading, font size, and spacing. 10 points

You Can’t Be Discreet Online

Summary:

“People concerned about privacy often try to be ‘careful’ online. They stay off social media, or if they’re on it, they post cautiously. They don’t share information about their religious beliefs, personal life, health status or political views. By doing so, they think they are protecting their privacy. But they are wrong. Because of technological advances and the sheer amount of data now available about billions of other people, discretion no longer suffices to protect your privacy.”  (New York Times)  After describing the inevitable loss of privacy incurred by engaging in social media, the author of this viewpoint article advocates for more secure phones and for regulatory laws.

People concerned about privacy often try to be “careful” online. They stay off social media, or if they’re on it, they post cautiously. They don’t share information about their religious beliefs, personal life, health status or political views. By doing so, they think they are protecting their privacy.

But they are wrong. Because of technological advances and the sheer amount of data now available about billions of other people, discretion no longer suffices to protect your privacy. Computer algorithms and network analyses can now infer, with a sufficiently high degree of accuracy, a wide range of things about you that you may have never disclosed, including your moods, your political beliefs, your sexual orientation and your health.

There is no longer such a thing as individually “opting out” of our privacy-compromised world.

The basic idea of data inference is not new. Magazine subscriber lists have long been purchased by retailers, charities and politicians because they provide useful hints about people’s views. A subscriber to The Wall Street Journal is more likely to be a Republican voter than is a subscriber to The Nation, and so on.

But today’s technology works at a far higher level. Consider an example involving Facebook. In 2017, the newspaper The Australian published an article, based on a leaked document from Facebook, revealing that the company had told advertisers that it could predict when younger users, including teenagers, were feeling “insecure,” “worthless” or otherwise in need of a “confidence boost.” Facebook was apparently able to draw these inferences by monitoring photos, posts and other social media data.

Facebook denied letting advertisers target people based on those characteristics, but it’s almost certainly true that it has that capacity. Indeed, academic researchers demonstrated last year that they were able to predict depression in Facebook users by analyzing their social media data — and they had access to far less data than Facebook does. Even if Facebook does not now market its ability to glean your present or future mental health from your social media activity, the fact that it (and any number of other, less visible actors) can do this should worry you.

It is worth stressing that today’s computational inference does not merely check to see if Facebook users posted phrases like “I’m depressed” or “I feel terrible.” The technology is more sophisticated than that: Machine-learning algorithms are fed huge amounts of data, and the computer program itself categorizes who is more likely to become depressed.

Consider another example. In 2017, academic researchers, armed with data from more than 40,000 Instagram photos, used machine-learning tools to accurately identify signs of depression in a group of 166 Instagram users. Their computer models turned out to be better predictors of depression than humans who were asked to rate whether photos were happy or sad and so forth.

Used for honorable purposes, computational inference can be a wonderful thing. Predicting depression before the onset of clinical symptoms would be a boon for public health, which is why academics are researching these tools; they dream of early screening and prevention.

But these tools are worrisome, too. Few people posting photos on Instagram are aware that they may be revealing their mental health status to anyone with the right computational power.

Computational inference can also be a tool of social control. The Chinese government, having gathered biometric data on its citizens, is trying to use big data and artificial intelligence to single out “threats” to Communist rule, including the country’s Uighurs, a mostly Muslim ethnic group.

[As technology advances, will it continue to blur the lines between public and private? Sign up for Charlie Warzel’s limited-run newsletter to explore what’s at stake and what you can do about it.]

Such tools are already being marketed for use in hiring employees, for detecting shoppers’ moods and predicting criminal behavior. Unless they are properly regulated, in the near future we could be hired, fired, granted or denied insurance, accepted to or rejected from college, rented housing and extended or denied credit based on facts that are inferred about us.

This is worrisome enough when it involves correct inferences. But because computational inference is a statistical technique, it also often gets things wrong — and it is hard, and perhaps impossible, to pinpoint the source of the error, for these algorithms offer little to no insights into how they operate. What happens when someone is denied a job on the basis of an inference that we aren’t even sure is correct?

Another troubling example of inference involves your phone number. It is increasingly an identifier that works like a Social Security number — it is unique to you. Even if you have stayed off Facebook and other social media, your phone number is almost certainly in many other people’s contact lists on their phones. If they use Facebook (or Instagram or WhatsApp), they have been prompted to upload their contacts to help find their “friends,” which many people do.

Once your number surfaces in a few uploads, Facebook can place you in a social network, which helps it infer things about you since we tend to resemble the people in our social set. (Facebook even keeps “shadow” profiles of nonusers and deploys “tracking pixels” situated all over the web — not just on Facebook — that transmit information about your behavior to the company.)

Last year, an investigation led by Senator Ron Wyden, Democrat of Oregon, revealed that Verizon, T-Mobile, Sprint and AT&T were selling people’s real-time location data. An investigative report last year by The New York Times also showed that weather apps including the Weather Channel, AccuWeather and WeatherBug were selling their users’ location data. This kind of data isn’t useful just for tracking you but also for inferring things about you. What were you doing at a cancer clinic? Why were you leaving the house of a woman who is not your wife at 5 a.m.?

The journalist Kashmir Hill has reported on cases in which Facebook suggested to a psychiatrist’s patients that they were potential “Facebook friends,” suggested that people “friend” the person with whom their spouse was having an affair and outed prostitutes’ real identities to their clients. We don’t want corporations (or governments) to make such connections, let alone exploit this to “grow” their platform.

What is to be done? Designing phones and other devices to be more privacy-protected would be start, and government regulation of the collection and flow of data would help slow things down. But this is not the complete solution. We also need to start passing laws that directly regulate the use of computational inference: What will we allow to be inferred, and under what conditions, and subject to what kinds of accountability, disclosure, controls and penalties for misuse?

Until we have good answers to these questions, you can expect others to continue to know more and more about you — no matter how discreet you may have been.