Who are these people? How did they contribute to the development of AI? How do they think “intelligence” could be defined?
Alan Matheson Turing: Alan Turing (1912-1954) is known for his work in breaking codes that were used to encrypt messages during World War II as well as for being the creator of the “Imitation Game”, known now as the “Turing Test”; designed to measure a machine’s ability to display intelligence indistinguishable from human intelligence. His definition of intelligence is linked to the ability to think, and respond to questioning.
John McCarthy: John McCarthy (1927-2011) was a Professor Emeritus of Computer Science at Stanford University, developed the Lisp programming language, and is credited as being the individual who first coined the term “artificial intelligence”. His thoughts on intelligence are “the computational part of the ability to achieve goals in the world” (McCarthy, 2007, p. 1), and he stipulates that there are different degrees of intelligence.
Herb Simon: Herbert A. Simon (1916-2001), a political scientist specializing in decision-making within organizations, was the author of “Administrative Behavior”,and is also credited alongside Allen Newell in the creation of the “Logic Machine Theory” and the “General problem Solver” programs. His view of intelligence is the behavioral cognitive processes relating to making rational decisions, wherein an operational administrative decision should be both correct, efficient, and also practical (Simon, 1947).
Marvin Minsky: Marvin minsky (1927-2016) was a computer and cognitive scientist, and was one of the co-founders of the Massachusetts Institute of Technology’s Artificial intelligence laboratory, and is the author of the paper “A Framework for Representing Knowledge”, published in 1975. His thoughts on what we consider to be intelligence can be summarized as potentially a product of the interaction of non-intelligent parts.
Timmit Gebru: Timmit Gebru (born 1982) is the founder of the Distributed Artificial Intelligence Research Institute, is one of the co-founders of the Black in AI affinity group, and is a vocal proponent of the dangers, potential biases, and shortcomings of AI and facial recognition. Her definition of intelligence is intelligence is the understanding of a topic (such as language), rather than its simple manipulation.
How do “Machine (programming) Languages” differ from human (natural) languages?
One of the key differences between machine languages and human languages is morphology; the study of words, the relationships between words, and the role context plays in defining meaning. Additionally, programming languages tend to be predetermined: the meaning and interplay between each word is laid out beforehand and the rules and definitions of the language are clearly established before its implementation. Additionally, “their grammar is self-defining, and it doesnt change depending on the context” (Harris, 2018). Human languages evolve over time, and the meaning of different words shift and change depending on both context and content. In a machine language, words need to retain their meaning regardless of context in order to function as formulaic as intended.
How does “Machine (artificial) Intelligence” differ from the human equivalent?
Human intelligence is often considered to be an amalgamation of adaptation to new environments, incorporation of prior experiences, and a multitude of differing cognitive processes. On the other hand, Machine intelligence does not have lived experiences to relate to, nor does it typically have to adapt to new environments, and as such usually aims to mimic human behavior and perform human-like actions (Vadapalli, 2022). The difference is between genuine experience and reaction, and replicated or mimicked response. Human Intelligence is driven by the brain’s memory and ability to think, while Artificial Intelligence is fueled by provided data and pre-existing instruction.
How does “Machine Learning” differ from human learning?
One of the key ways in which they differ is in the amount of agency involved in either process; while human learning can absolutely be guided and curtailed depending on several different socio-political factors, there is still some level of agency available to every human learner. On the opposite end of the spectrum, machine learning algorithms are entirely defined by these external factors; the “systems can be biased based on who builds them, how they’re developed, and how they’re ultimately used. This is commonly known as algorithmic bias” (Heilweil, 2020, p. 1). These parameters curtail and define how and what a machine will learn, as a machine learning system lacks agency in what or how it consumes information that it processes.
Personal Turing Test: How do my answers to the above questions differ from what a machine could generate?
The primary way in which my answers differ from how a machine could answer the previous questions revolves around a notion I mentioned in the machine intelligence vs human intelligence segment; previous experience. My answers are based on the (albeit probably biased and flawed) previous experience and prior knowledge I have amassed and consumed over the years regarding these topics. This includes a massive purview of different sources, ranging from pop culture, to works of fiction, to academic sources, all the way to the probably questionable information I have gleaned from talking to and interacting with different people throughout my life. An AI or machine learning algorithm would be wholly devoid of these anecdotes and prior experiences, and even if I was the one to program and provide the informative basis for these algorithms, there is no way I would be able to wholly account for all of my own worldviews and prior experiences in every minutia of how it affects my own responses. This in turn would create unforeseen barriers to the processes of an AI or machine learning system, and would influence how and what these systems would and could answer for these questions.
Sources drawn upon for this post are listed below:
Vadapalli, Pavan. ( August 26, 2022). AI vs Human Intelligence: Difference between AI & Human intelligence. UpGrad.com
MacCarthy, John. (November 12, 2007). What is Artificial intelligence?. Computer Science Department.
Simon, Herbet A. (1947) Administrative Behavior: A Study of Decision Making Processes in Administrative Organization.
Harris, Ana. (October 31, 2018). Human Languages vs. Programming Languages. Medium.com.
Heilweil, Rebecca. (February 18, 2020). Why Algorithms can be Racist and Sexist. Vox.com.
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