越而胜己 / Beyond awesome

This article was submitted as my ENGL 131 major paper.

We live in an era of information explosion. The internet has linked
resources all over the world and converged them into the greatest
database human beings have ever possessed. Thanks to the internet, we
are now able to access thousands of times more information than we could
ever before. The enormous amount of information provided by the internet
has enriched our reading resources and we have thus naturally shaped the
habit of reading thanks to its convenience. According to Amy
Goldwasser’s article “What’s the Matter with Kids Today?”, an average
teenager today spends 16.7 hours reading and writing online, which is a
considerable amount of time. However, as President Obama said in his
speech at Rutgers University,

today, in every phone in one of your pockets, we have access to more
information than at any time in human history, at a touch of a button.
But, ironically, the flood of information hasn’t made us more
discerning of the truth. In some ways, it’s just made us more
confident in our ignorance. (Obama)

despite the vast stores of information on the internet, we are mostly
only exposed to a very limited portion of it, because we tend to be only
seeing things that we already like or agree with. While enjoying such
convenience, we should be aware that technology might hide facts from
us. We are only provided information that we want to see, making us
narrow-minded and arrogant. Since that information presented on the
internet could be biased, inaccurate or even fake, we could easily be
seduced into the abyss of ignorance. Long-term exposure to this
arbitrary environment can cause biased opinion and compromise our
ability to view questions from a critical perspective.

The concept of machine learning has been around for years. Machine
Learning is a fairly recent technology that allows computers to make
predictions merely by learning data, without being explicitly
programmed. In other words, machine learning algorithms take in our
habits and interpret them into our preferences, and thus provide more
information that matches our predilections. It has widely been applied
in our daily lives—when we go to Amazon.com, we see recommended items
selected by the machine learning algorithms; online music streaming
services, such as Spotify and Pandora, use machine learning to guess
songs that we like; search engines such as Google use machine learning
to learn our searching habits and suggest websites that we most likely
want to visit. Indeed, machine learning has made our lives much easier
to some extent. However, machine learning might also bias our views.
Personal assistant services, such as Siri and Cortana, study our habits
and use that data to filter and select what we prefer to see and present
them to us; Facebook pushes news to our timelines, but only those
machine learning algorithms think we are interested in; search engines
like Google and Bing record our search preferences and tailor the page
ranking for our taste.

Many might think that machine learning is a sort of algorithm or
program, and programs don’t have stances. However, this is simply not
true. Per Zeynep Tufekci, an assistant professor at the School of
Information and Library Science at the University of North Carolina, the
algorithm that selects trending news is the root of Facebook’s bias. She
says that although Zuckerberg claimed that the trending stories were
“surfaced by an algorithm,” it doesn’t mean that the process is
neutral—the algorithm itself is biased towards those “like”-able
stories. Although programmers can’t control what the machine learns from
the data, there are parameters that can be adjusted to control what at
last show up on the trending page. As Tufekci concluded in her article
The Real Bias Built in at Facebook, “what we are shown is shaped by
these algorithms, which are shaped by what the companies want from us,
and there is nothing neutral about that.”

Except the fact that machines have been deciding what we are exposed to
on the internet, people around us have also been blinding us from
alternative opinions. Google News first allowed its users to customize
their news feeds so that they can read only “short stories pertaining to
their interests” (Pogue). People started to concern at that time that we
would never be exposed to other news we don’t expect to read (Pogue). In
2004 and 2006 respectively, Facebook and Twitter started to bring people
together on the internet. While enjoying sharing our experiences and
feelings and on Facebook and Twitter with the touch of a button, we have
fallen victim to potential information traps. In fact, according to
David Pogue, a columnist for Scientific American, social networks are
“a thousand times worse” than Google News—you choose what you read on
Google News, while on Facebook, it’s your friends who choose what you
read; on Twitter, it’s the people you follow who choose what you read.
However, it is human nature to focus on things and people that match our
value and avoid the people we disagree with. Therefore, we are most
likely Facebook friends with only those who have similar views as ours,
and we follow only those who we respect and identify with on Twitter.
Consequently, as we frequently visit those social network sites, we are
given the false impression that everyone in the world believes what our
friends and we believe. People out of our social circles and their
opinions thus become invisible to us. Therefore, we see individuals who
disagree with us not as human beings, but as enemies (Headlee). As
Journalist Celeste Headlee said in her speech at TEDxSeattle 2016, “We
can ignore evidence that refutes our beliefs, and we unfriend people
both online and in real life.” Thus, in November 2016, when Donald Trump
was elected the 45th President of the United States, many
Democrats were shocked by the “unexpected” result because they had
hardly seen opinions from the other side (Headlee). Supporters of
Hillary Clinton, always having seen their friends criticizing Trump for
his racist and sexist speech, couldn’t see how Trump was supported in
other parts of the United States (Headlee).

Another issue that called extensive attention worldwide in the Election
of 2016 was fake news. Fake news such as Pope Francis endorsing Donald
Trump and Hillary Clinton using a body double deceived quite a few
(Ritchie). It’s evident that information on the internet isn’t always
reliable. Unfortunately, according to a study at Stanford University,
students, who are the primary users of social networks, are particularly
vulnerable to fake news (Donald). The directors of that study report
that,

students may focus more on the content of social media posts than on
their sources… Despite their fluency with social media, many students
are unaware of basic conventions for indicating verified digital
information. (quoted in Donald)

Possibly, the quick-paced nature of the internet has contributed to
students’ lack of critical thinking abilities. Dr. Iyad Rahwan, an
honorary fellow at the University of Edinburgh, warns us that today
“people are unwilling to reflect more because it takes time and effort”
(quoted in Macrae). Thanks to social networks, we are able to post our
ideas on Twitter easily—but due to the 140-character limit, we only have
space to express our claim but not any evidence or explanation.
Gradually, we get used to making short claims without any proof or
argument, and we fall into the habit of reading without reflecting or
questioning. Even worse, such 140-character culture might affect our
writing skills because we are growing out of the habit of reasoning. We
see anything we see on the internet as true and repost it without even
thinking about its authenticity. Hence, we become part of the spreading
of fake news as well. The problem is not merely present in social media,
though. Every online article generated from the public is a potential
source of unreliable information. For example, the biggest and most
popular online encyclopedia, Wikipedia, isn’t reliable sometimes.
Harvard Guide to Using Sources explicitly says that students “should
be extremely cautious about using Wikipedia” because anyone could edit
the website to provide misinformation, whether intentionally or not.
Since many people today use this online encyclopedia, which till now has
30 million users, as a source of truths, errors on Wikipedia could
contaminate tons of articles, causing massive misconception. Therefore,
we must be critical even when viewing the most popular websites on the
internet.

Although Mark Zuckerberg, the founder of Facebook, claimed that 99% of
the news on Facebook is authentic, we need to be aware of the bias from
the selection process itself (Pogue). The truth is like a
photograph—people say that cameras don’t lie, but sometimes they don’t
realize that cameras don’t necessarily tell the truth all the time,
either. Photographs are also subjective artwork, in that the
photographer can choose what to include in the photo and what not to.
Even if the news is not “fake,” it might be interpreted and exaggerated
subjectively, so we need to view them critically to see the truth.

To conclude, the internet is neither truthful nor neutral. President
Obama warned us that “We search for sites that just reinforce our own
predispositions. Opinions masquerade as facts. The wildest conspiracy
theories are taken for gospel.” These are all facts that deserve our
attention. But every element of our society is linked to the internet
nowadays and we’ve become so dependent on the internet that we can’t
live without it. Nevertheless, this doesn’t mean that we have no
alternative but to passively accept the current situation. On the
contrary, exactly because we live in the age of big data, we must
develop our critical analysis capacity and view all the information on
the internet more objectively. Educators today have realized the stake
of the issue. The University of Washington has even started a course
called “Calling Bullshit in the Age of Big Data”, to increase awareness
of fake information on the internet. We must be particularly prudent
when viewing unofficial information, and the best alternative would be
visiting the library or consulting experts when accurate data or
information is needed. As David Pogue says, although algorithms will
probably be able to eradicate all fake news someday, our healthy
skepticism and critical awareness will be the ultimate cure to the
problem.

Donald, Brooke. "Stanford Researchers Find Students Have Trouble Judging
the Credibility of Information Online." Stanford Graduate School of
Education
. N.p., 22 Nov. 2016. Web. 25 Jan. 2017.

Goldwasser, Amy. "What’s the Matter with Kids Today?" Salon. N.p., 14
Mar. 2008. Web. 24 Jan. 2017.

Headlee, Celeste. "Help Make America Talk Again." TED Talk. TED.com,
19 Nov. 2016. Web. 23 Jan. 2017.

Macrae, Fiona. "Is Twitter Making You STUPID? Social Networking Sites
Are Making It Hard for People to Think for Themselves." Daily Mail
Online
. Associated Newspapers, 05 Feb. 2014. Web. 25 Jan. 2017.

Obama, Barack. "Remarks by the President at Commencement Address at
Rutgers, the State University of New Jersey." National Archives and
Records Administration
. National Archives and Records Administration,
15 May 2016. Web. 21 Jan. 2017.

Pogue, David. "The Ultimate Cure for the Fake-News Epidemic Will Be More
Skeptical Readers." Scientific American. N.p., 03 Jan. 2017. Web. 23
Jan. 2017.

Ritchie, Hannah. "Read All about It: The Fakest News Stories of
2016." CNBC. CNBC, 30 Dec. 2016. Web. 09 Mar. 2017.

Tufekci, Zeynep. "The Real Bias Built in at Facebook." New York Times.
N.p., 19 May 2016. Web. 23 Jan. 2017.