Simon Says and
Computers: Information is not Intelligence
Computers can only do what you tell
them, making computers akin to participants in the popular children’s game
“Simon Says.” In the children’s game, one person plays the role of Simon and commands
participants to perform certain actions beginning with the phrase, “Simon Says.”
Participants can only do what Simon commands. Similarly, with computers,
the programmer is “Simon” and a computer’s response is limited to its
understanding of what it is being instructed to do. Computers are not able to
act outside of this realm, so the commands (programming) initially received are
critical to computers output, functionality, and effectiveness.
In “The Stupidity of Computers,”
David Auerbach1 explores the intelligence of computers. Filled with numerous
examples, this article takes readers on a journey of computer output. It begins
by discussing how programmers input information so that a computer can
understand and respond to queries. It then evolves into conversations about
search engines, language and ontology, and popular information-generating and
information-gathering websites. Finally, it concludes with greater implications
of how computers impact government, social structure, and individuals’ identification
and categorization of themselves and others. Ultimately, this article sheds
light on the limitations of computer intelligence and the growing dominance of
computer intelligence on human life.
Through a series of examples,
Auerbach explains the growth of computer intelligence. For instance, a simple
sentence such as “Highlight Japan on a map” requires a set of commands that
could be as long as a paragraph. The computer can respond to this request only
if the programmer properly input the necessary commands and also provided a map
and a highlight feature. Computer
instructions must be precise and language matters. Ambiguous language brings
about confusion and in searches, can bring about undesired result. Initial search engines could only search for what
an individual input and could not extract similar information. For instance, if
an individual did a search for “outdoor parks in Alabama,” original search
engines would only be able to generate search results that contained the four
words in the original search. The search results would not generate responses
that referenced “Ruffner Mountain in Birmingham” because this last phrase does
not include any of the key words although Ruffner Mountain is an outdoor park
in Alabama. This example shows that computers can only respond to the
information given them, whereas a human would be able to respond with Ruffner
Mountain if they were asked about outdoor parks. This inability to interpret or
extrapolate answers challenged the effectiveness of internet searches, a
problem that was solved by the search engine Google.
Eventually, Google found a solution
by “using the topology of the web as
opposed to its meaning.” Google began paying attention to which pages were
linked together – in other words, they must have a connection to one another. This helped provide more relevant results.
That way, if someone types in “outdoor parks in Alabama,” anything that
classifies itself as such would pop up. In addition, an individual might even
see advertisements for products relevant to being in the outdoors such as an ad
for Mountain High Outfitters, a store that provides outdoor gear. Today, Google
not only provides more relevant results, but it will also try to “predict” what
you are searching for by creating a drop down menu of choices as you input
letters and words in the search bar. For instance, by simply typing the letter
“a” in my Google search bar, the following pop up “Amazon, Alabama power, AOL,
and Alagasco.” When I type in the entire word I’m looking for “Atlanta,” Google
populates the dropdown menu with “Atlanta Braves, Atlanta, Atlanta Airport, and
Atlanta Braves Schedule.” These are the most popular searches individuals are
currently looking for when they type “Atlanta” into Google. Google is able to return desirable responses
because of how its programmers have set it up to recognize information and its
relationship to other information and also because of metadata categorization. Individuals
can aid how online information is categorized and the frequency in which it is
returned in search results by providing “key words” that are often used in
searches. On Twitter, the key words are proceeded by a hash tag symbol.
The latter half of the essay focuses on the importance of ontology, or
assigning recognizable categories to metadata. This results in comparing and
contrasting the effectiveness of several popular internet giants such as Ask
(formerly Ask Jeeves), Yahoo, Wikipedia, Amazon, Facebook, Twitter, and more.
Due to the massive amount of information online, the web is faced with the challenge
of categorizing information. Amazon successfully does this by categorizing
information in well-accepted categories such as “books, household appliances,
toys.” Facebook successfully does this by having individuals select the
categories to which they belong – people can input their religious group,
college, favorite bands, favorite TV shows, favorite politicians, and more.
These categories or ontology used by Amazon and Facebook create methods in
which to group and analyze people. Auerbach cautions that these categories are
limited to human’s determination of categories and that computers cannot
automatically generate the categories. Auerbach also cautions that the government and
other places are making connections and conclusions between what people have
liked. However, “the sheer number of uncontrolled variables at work makes it
dangerous to take any of these conclusions at face value.”
Other internet-based examples of
the role internet has in shaping how we receive information include blogs,
LinkedIn and Ning. LinkedIn.com uses the slogan, “World’s Largest Professional
Network” and is essentially a place for individuals to house their professional
and academic accomplishments online. People can link/connect/network with other
individuals by searching individuals by profession, college, geographic
location, skills and more. In an attempt to help individuals find other
individuals relevant to them, LinkedIn also features “individuals who looked at
this profile also looked at” and provides a list of other individuals
frequently searched for tangentially with the person currently on their screen.
Ning.com has the slogan “build and cultivate your own community.”
Unlike the other social media websites that connect people who have mutual
connections, Ning.com connections are limited to those within that particular
Ning group. On Ning, one would be a part of multiple Ning groups that don’t
intersect, which is unlike other social media. The information contained on
these websites and other websites are being used to create categories,
correlations, and connections of people and items that would otherwise not be
connected.
Although this article does not go
in-depth into any one subject that it mentions, it provides a comprehensive
overview of the limitations and implications of computers continual integration
in society. The greater implications of
this article are that computers and the internet are only as smart as the
information and algorithms initially input into them. Computers and the
internet are not able to think for themselves and are therefore just an
advanced version of the children’s game Simon Says. Computers can only do what
they are told although they are very good at responding and providing
information, as long as they have access to the information requested. Information
should not be confused with the higher calling of intelligence. Computers can help
humans synthesize and analyze information. Computers cannot replace or create
human intelligence.
1 Auerbach, David. “The Stupidity of Computers.” Machine
Politics: Issue 13, Winter 2012. https://nplusonemag.com/issue-13/essays/stupidity-of-computers/.
