The world is becoming
ever-so involved within the technological field at a high rate. As proposed by
David Auerbach in his recent article “The Stupidity of Computers”, the
“dumbness of computers” will eventually become our weakness as humans. Today
more than ever, humans rely on computers for everyday needs ranging from online
banking, shopping, social media, and so forth, and this only means one thing:
there is a great deal of influx of data being entered into computers. Will
computers be able to increase as consumer demands increase? Ultimately, David
examines the relationship between the history of computers and the human world.
The below are summarized findings.
Early inventions of
computer databases paved the way for modern life in the technological arena,
but language barriers presented an issue. Computers are ingrained with certain
functions, such as being able to capture word choices entered by the end user
and finding those word choices on the World Wide Web; however, early inventions
to understanding the mechanisms behind the relationship of input and output
were examined by algorithms as Quicksort, Monte Carlo, and Huffman Compression.
The role of these algorithms was to provide efficiency for computers in
sorting and translating data. Alongside these early inventions came the
introduction of early search engines such as Lycos, AltaVista, and Northern
Light. These engines tried to help the computer understand the language being
inputted but failed at doing so effectively and efficiently. A more modern
search engine most of us may be familiar with is Ask Jeeves. Ask Jeeves captures
data being entered into a search bar differently than most engines captured
data before. For instance, if I were searching for “US best parks to hike”
instead of typing my search directly out, Ask Jeeves' search would require me to
enter a hypothetical question; trailing back to my original search, this could
be for instance “Where is the best park to hike in the US” or perhaps “Which US
state provides the best park to hike”. Ask Jeeves would translate my input into
a code that would then search across web-pages trying to find a precise match
to my question posed. The implication of confusion was met at odds since my
proposed question was somewhat technical and laborious! Since then, humans more
frequently rely on Yahoo, Google, and even social media for answers (which I
will touch base on shortly).
Even with early search
engines, it is notable that language in computers is two-fold. Sentence meaning
has to be precise for computers to understand written request (search), and the
sentence must be free of any potential obscurity. Thus, the search request must
contain normalized values with easily understood principles. For instance, if I
wanted to search for “How many years does an average dog live”, I might be more
prone to instead search for “Average dog life”. Thus, vocabulary is
strengthened while my search find will most likely end up being more precise.
Referring back to early
inventions of search engines, the most notable one of all, Google, was created
into existence middle 1990 by Sergey Brin and Larry Page, who were two students
trying to figure out a way to solve the complex language of computer search
engines. Brin and Page set out on the laborious, head-wrenching mission by
analyzing the topology of web pages. In this way, search pages were match
accordingly to relevant material found by a ranking classification system.
Instead of search results pulling all pages across the web together, the
ranking system identified web pages and results in order of importance based
upon data entered in the search bar. Thus, the system for generating order and
precision in technological search engines was formed, yet the problem of
understanding the language (codes) had not truly been identified. However,
Google did succeed in the search engine world, and as by evident, humans still
rely on Google for everyday life questions. Presently, an evaluation of
searches made daily on the internet and the monies to be gained from “owning”
such a search engine is noteworthy; hence, the stock price of Google—Who would
have thought decades ago that Google would become what is has today? Talk about
revolutionary in modern life technology!
Alongside Google, most
of us are familiar with other search engines/ technological areas, such as
Wikipedia, Amazon, and Facebook. In his work, David Auerbach examines the
relationship between these prominent engines and crowdsourcing (a familiar term
to most of us), and crowdsourcing in this sense means the ways in which humans
are “outsourced” to obtain information from the internet rather via other
areas. First of all, Wikipedia is a searchable databased for nearly all areas;
however, it is meet with the limitation of being user editable. With greater
user accessibility to make real-time edits comes the need for greater control
over what information users are writing for various topics; hence, it may not
always be true. But, with anything in life, one must be knowledgably aware of
what one decides to digest and be mindful to always be critical. Most of us
have been warned to stay away from Wikipedia. Secondly, Amazon has provided
users with a wide range of shopping items based upon categorical areas, such as
gender specific gifts, price range options, and even location based sellers.
With this feature, Amazon has implemented an “ontological” database system,
which helps to store, classify, and sort through the endless amounts of user
entry of Amazon users. Thirdly, Facebook is a tool that allows users to provide
data about themselves, and in return the data is stored internally. Facebook’s
strategy of data collection is both socially and virally. The implication (or
actual advantage) of Facebook is a gold mine for marketing strategists.
However, all three technological areas run the risk of data breach security,
and according to the National Security Agency more than “1.3 billion emails,
calls, and other types of communication” are stored and can be viewed daily.
Overall, search engines
help to make our lives easier, and computers are a true piece of art. There are
implications for every advancement made in technology, particularly those of
computers, but each piece has helped to liberate us from mundane content. As
humans, we have access to nearly all works of information, but it is mindful to
be cautious in what we interpret and store. Computers are a great advantage to
society, but unfortunately, the ability to process, interpret, and transmit
data is a downfall of such technology; computers are only as “smart” as our weakest
link.
Reference:
D.
Auerbach. (2012, Winter). The Stupidity of Computers. Retrieved from https://nplusonemag.com/issue-13/essays/stupidity-of-computers/
Notes:
Further research supporting ideas presented in the above, can be found at the tabs located on the home page. These include the below web-based links:
1. The Amazon Effect https://www.thenation.com/article/amazon-effect/
The article explores
the relationship between the history of Amazon and the effects on society.
Implications for future society needs, wants, and technological areas are
addressed.
2. Overview of Quicksort
https://www.khanacademy.org/computing/computer-science/algorithms/quick-sort/a/overview-of-quicksort
Academic based
publisher, Kahn Academy, provides a deeper understanding of one of the first algorithms
used within computers, as discussed in the above blog.
3. Technology Dependence
Articles http://www.huffingtonpost.com/news/technology-dependence/
One of the most
well-known online editors, Huffington Post, examines a variety of technology
dependent write ups about different areas of life. This assortment provides a
plethora of engaging more within how society is become technologically
dependent more every day.
4. Wikipedia History http://time.com/3667915/wikipedia-anniversary/
Classical Time magazine outlines the history of
infamous Wikipedia and the effects on society.
No comments:
Post a Comment