In “The Stupidity of Computers,” David Auerbach challenges the concept of real artificial intelligence as well as the ontology of computers. He (2012) reports, “In essence, an ontology is an explicit, formal definition of a conceptual framework for any number of kinds of entities, as well as any number of relationships between them” (p. 16). It is the philosophy of the nature of being, but Auerbach (2012, p. 16, 22) reveals that for computers to be an authentic part of this “nature of being,” they must have a “fixed, discrete ontology.” However, Auerbach argues that computers do not have this fixed, discrete ontology now because of their flaws and limitations. Also according to Auerbach , humans do not always concur to use an ontology nor do they agree on a fixed one either (Auerbach, 2012, p. 22), which definitely applies to a computer or technological “ontology.” While depicting the computer constraints and limits and critiquing the notion that human reality is being radically altered and even re-ontologized because of advances in technology and software, he reminds us that humans still create the hegemonic semantics and devices in the end. “Computers do not invent new categories; they make use of the ones we give them, warts and all” (Auerbach, 2012, p. 24).
In the first section of his article, Auerbach (2012, p. 5) points out the fact that computers cannot understand nor interpret conversations as well as the fact that it is laborious to code algorithms and create precise instructions to have a computer do a task. Auerbach presents a pseudocode for a word count—revealing the problems with having a computer conduct a mere word count much less something really complicated. Thus, Auerbach argues that there is no real artificial intelligence now.
Then in the next sections, Auerbach highlights the flaws with search engines as well as some of their histories (from Lycos and Jeeves to Yahoo and Google). He (2012, p. 15) emphasizes that with all of these engines as well as with a chat box “MGonz,” there is just a “[…] nonsemantic analysis of huge amounts of data” which creates obstacles not only for having a fixed ontology but also for social justice. For instance, Auerbach (2012, p. 16-17) exposes biases (from the “underlying ontology”) that have emerged and have been facilitated by computers such as when gay-themed books on Amazon.com were equated with “porn” and thus deranked as a result.
In the last section, Auerbach points out the problems of bureaucracy, government intelligence, and computer technology. He (2012) explains that while there are not enough human resources and labor to process every signal, computers attempt to help but with a “[…] deficient understanding” and with much more ambiguity, which creates more haphazard errors (p. 21-22). Within this bureaucracy, Auerbach (2012, p. 23-24) posits that an “ad hoc hierarchy” exists instead of the end of hierarchies altogether now because a computer merely “[…] reifies those [top-down] taxonomies.” Thus, he (2012, p. 25-26) argues that in the future, we will bring ourselves to the computers (and bring the computers to us physically) because we are really the controllers and guides in this new bureaucracy and this technical realm. Humans are the intelligent beings not the computers.
Significance and Implications
Auerbach (2012, p. 25-26) reveals that while computers will not “[…] acquire minds anytime soon,” there will be a “reductive ontology” that will eventually emerge with “computer ubiquity.” In this new ontology, he reveals that there will be more “flattening of the self” in which people will embody multiple “overriding ontologies” with blurred boundaries and even conflicts (Auerbach, 2012, p. 25). The advances in computer technology will help humans have a new sense of “self” in the end. Moreover, semantics will become less important, and if that happens, then Auerbach (2012, p. 26) purports that artificial intelligence could become “remotely plausible.”
Other Examples with Links
http://www.ifets.info/journals/17_2/2.pdf
Echoing Auerbach’s theory that computers will eventually become ubiquitous,Gwo-Jen Hwang,Pi-Hsia Hung,Nian-Shing Chen,and Gi-Zen Liu (2014)discuss ubiquitous e-learning which is occurring in Taiwan now. Their research and article,“Mind-tool Assisted In-Field Learning Project in Taiwan,” reveals that students’ learning is significantly improved with “ubiquitous learning” which is facilitated by e-learning and cutting edge technologies.
http://www.ifets.info/journals/17_2/12.pdf
Additionally, Auerbach (2012, p. 26)argues that “we will bring computers to us, not semantically but physically.” Now,that is certainly the case especially for interactive learning with computers and software. For example,in “Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool,” Carlos Melgosa Pedrosa, Basilio Ramos Barbero, and Arturo Román Miguel (2014)compare an interactive learning manager for graphic engineering (which helps develop spatial vision)to traditional methods.They report that this web-based tool is more efficient than traditional methods when students have challenges with spatial vision and when students have no technical drawing experience.
http://ezinearticles.com/?Computers-Are-Stupid,-Stupid,-Stupid!&id=218192
Moreover, in Mike Bryant’s (2006) “Computers Are Stupid, Stupid, Stupid!” article, he reifies Auerbach’s points about the computers’ limitations and the fact that they can only do functions like basic math. Bryant (2006), a software developer, calls the computer a “[…]souped-up calculator”(p. 1).
References
Auerbach, D.(2012). The stupidity of computers. Retrieved from the Machine Politics website:
https://nplusonemag.com/issue-13/essays/stupidity-of-computers/
Bryant, M.(2006). Computers are stupid, stupid, stupid!. Retrieved from Ezine Articles:
http://ezinearticles.com/?Computers-Are-Stupid,-Stupid,-Stupid!&id=218192
Hwang, G., Hung, P., Chen, N., & Liu, G. (2014). Mindtool-assisted in-field learning (MAIL):
An advanced ubiquitous learning project in Taiwan. Educational Technology & Society, 17(2), 4- 16.
Pedrosa, C., Barbero, B., & Miguel, A. (2014). Spatial visualization learning in engineering:
Traditional methods vs. a web-based tool, Educational Technology & Society, 17(2), 142-157.
