Who were these people, and how did/does each contribute to the development of artificial intelligence? How did/does each think “intelligence” could be identified?
Alan Matheson Turing was a British mathematician who used the theory of machine learning and computing to take a leading role in breaking Nazi cipher during WWII. In one of Turning’s papers he discussed how to build and test intelligent machines. He believed if a machine could engage with a human, without being detected as a machine, it demonstrated intelligence (Frankenfield, 2022).
John McCarthy was a professor whose research focused on artificial intelligence. He has been referred to as the Father of AI and is known to have coined the term artificial intelligence at the Dartmouth Summer Research Project on Artificial Intelligence. McCarthy defined intelligence as an ability and believed that a system could process that ability to various degrees (Sutton, 2020).
Herb Simon has been referred to as one of the founding fathers of AI. He is known for working with Allen Newell to develop a computer program that simulated human decision making. Simon defined human intelligence, as a behaving system, and thought that the more complex environments we find ourselves in, the more complex our decision making becomes (The Decision Lab, 2021).
Marvin Minsky was a mathematician and computer scientist who cofounded the Massachusetts Institute of Technology’s Artificial Intelligence Lab in 1959 with John McCarthy (BBC News, 2016). He believed a computer could replicate the functions of the human brain. Minsky was driven by the concept that human intelligence for common sense reasoning could be imparted to computers or machines.
Timnit Gebru is a well-known scholar in the AI ethics community. As a computer scientist she researches algorithmic bias. Gebru believes intelligence can be used or misused for harmful, illegal, or unintentional purposes though human bias in coding. Gebru believes that intelligence is embedded in everyday products and as humans we aren’t always able to distinguish between AI and machine learning (Woolery, 2022).
How do “machine (programming) languages” differ from human (natural) ones?
Human language is the principal method of communication, it is a system of spoken and written symbols, that humans have used to express themselves and their identities. As time goes on, language evolves and changes. Machine language is also a method of communication created by humans to communicate instructions to a machine or a computer (Harris, 2018). There are several differences between human and machine language. The most obvious may be that programming language was intended for machines. Machine language doesn’t follow grammar rules and it doesn’t change depending on the context. It also doesn’t evolve and develop like human languages do; there is no room for errors or improvement. Finally, machine language is non-emotional; intonation or body language have no effect on machine language.
How does “machine (artificial) intelligence” differ from the human version?
Human intelligence is our ability to acquire skills and knowledge. As Challot (2019) indicates, the AI community often measure intelligence by the skills exhibited by AI. There are several ways that AI differs from human intelligence. As humans we are able to adapt to changing environments by using different cognitive processes, AI has the ability to mimic human behaviour and actions. As humans we use our brains to solve problems, remember, and think; AI relies on data and instructions from humans. Humans rely on learning from past knowledge and experience; AI doesn’t think, it learns from data and performs tasks efficiently, however, it relies on human commands. Finally, AI is designed to mimic human behavior, it isn’t able to make rationale decisions like humans (Vadapalli, 2021).
How does “machine learning” differ from human learning?
Machine learning involves exposing a computer to training data, and based on that data, the computer learns to process the data, which allows the computer to form predictions and judgments (Heilweil, 2020). Human learning involves actively making sense of the world around us by acquiring new knowledge, behaviours, and skills. Humans use their brains, bodies, and environment to learn; if humans are given new information, we can change how we think or feel about knowledge that we have. As Heilweil (2020) points out, AI doesn’t have the ability to change how it predicts information. This has led to AI predictions being biased; we often don’t know how bias is built into data or what data helped build it.
How do YOUR answers to these questions differ from what a machine could generate?
My responses to the above questions were derived by reviewing course contents, doing my own online searches and research, from my past work experience, and from my past learning through the MET program. If I imagined responses to the above questions that only included artificial intelligence, it would exclude any information that I personally learned through the course readings, past work experience, and my past learning experiences in the MET program. My reasoning process uses the knowledge that I currently have to draw the conclusions and create the explanations for the above questions. For me personally, this knowledge and experience is drawn from my own teaching experience, as well as, my current and past experience and knowledge gained through work and educational experiences. Artificial intelligence may not have the same experiences and knowledge that I possess, and therefore, if I compared my thoughts to what AI would produce on this topic, we would likely draw different conclusions. Based on the research I’ve done for this assignment; I believe that my conclusions are more in-depth and thoughtful then if generated by AI. I believe that humans form opinions better than machines and although humans have their own bias, they have the ability to identify their bias and have the ability to exclude their bias in thoughtful conclusions and explanations.
References
BBC News. (2016, January 26). AI pioneer Marvin Minsky dies aged 88. BBC News. https://www.bbc.com/news/technology-35409119
Biography.com Editors. (2020, July 22). Alan Turing. Biography. https://www.biography.com/scientist/alan-turing
Chollet, F. (2019, November 5). On the measure of intelligence. https://doi.org/10.48550/arXiv.1911.01547
Frankenfield, J. (2022, February 22). What is the Turing test? Investopedia. https://www.investopedia.com/terms/t/turing-test.asp
Harris, A. (2018, November 2). Human languages vs. programming languages – Ana Harris. Medium. https://medium.com/@anaharris/human-languages-vs-programming-languages-c89410f13252
Heilweil, R. (2020, February 18). Algorithms and bias, explained. Vox. https://www.vox.com/recode/2020/2/18/21121286/algorithms-bias-discrimination-facial-recognition-transparency
Sutton, R. S. (2020). John McCarthy’s definition of intelligence. Journal of Artificial General Intelligence, 11(2), 66-67. https://doi.org/10.2478/jagi-2020-0003
The Decision Lab. (2021, March 2). Herbert Simon. The Decision Lab. https://thedecisionlab.com/thinkers/computer-science/herbert-simon
Vadapalli, P. (2021, December 20). AI vs Human Intelligence: Difference Between AI & Human Intelligence. upGrad Blog. https://www.upgrad.com/blog/ai-vs-human-intelligence/#:%7E:text=While%20Human%20Intelligence%20aims%20to,analogous%2C%20but%20machines%20are%20digital.
Woolery, E. (2022). Timnit Gebru: Machine learning, bias, and product design. Timnit Gebru: Machine Learning, Bias, and Product Design – DesignBetter. https://www.designbetter.co/conversations/timnit-gebru