IP 2:
artificial
intelligence
A set of questions to learn about important figures in the development of AI and think critically about the differences between machine and human intelligence.
Alan Turing (1912-1954)
Alan Turing, was an English mathematical, computer scientist, cryptanalyst, and logician who is widely considered to be the father of theoretical computer science and artificial intelligence.
He developed the Turing machine, a mathematical model of computation that formalized the concept of algorithms. His famous Turing test attempted to define a standard for assessing machine intelligence.
According to Turing, If a machine can engage in a conversation with a human without being detected as a machine, it has demonstrated human intelligence.
Even though machines and human languages have similarities, such as communicative functions, structure, syntax, and semantics they differ on several dimensions. Harris (2018) notes that contrary to humans, machine language doesn’t have morphological functions, which refers to the ways context can change a word’s meaning and pronunciation.
One of the main differences between machine intelligence and human intelligence is that, according to Jones (2020), the ability to understand context and identity in algorithms is “extremely reductive and limited to information that can be digitized and made legible to computers”(p.29). Jones (2020) also notes that humans are more efficient at adapting to subtle changes in the physical and social environment to frame and reframe contexts.
Crawford (2021) notes that “human intelligence and expertise rely heavily on many unconscious and subconscious processes, while computers require all processes and data to be explicit and formalized” (p.6). This points at how human learning is much more complex, as it contains multiple dimensions of the mind, while machine learning is based on data training (Heilweil, 2020), hence superficial.
While a machine would have had the ability to process larger amounts of information more swiftly, it doesn’t possess a direct experience of human intelligence that gives it the authority to evaluate the descriptions and consider their validity. As explained by Crawford (2021), human intelligence operates on evaluation while machine intelligence operates on correlation.
references
Chollet, F. (2019, November 5). On the measure of intelligence. Google, Inc. https://arxiv.org/pdf/1911.01547.pdf
Crawford, K. (2021). Atlas of AI. Yale University Press.
Jones, R. (2020). The rise of the pragmatic web: Implications for rethinking meaning and interaction. In C. Tagg. and M. Evans (Eds.). Message and Medium (pp. 17-37). De Gruyter Mouton.
Harris, A. (2018, October 31). Human languages vs. programming languages. Medium. https://medium.com/@anaharris/human-languages-vs-programming-languages-c89410f13252
Heilweil, R. (2020, February 18) Why algorithms can be racist and sexist. Vox. https://www.vox.com/recode/2020/2/18/21121286/algorithms-bias-discrimination-facial-recognition-transparency