Question 1
Alan Turing
Alan Turing, an English Mathematician who highlights his talents in machine learning and cryptanalysis (Biography.com Editors, 2020). Some big milestones of his life are introducing the foundational idea of artificial intelligence and leading the argument of machine thinking (Biography.com Editors, 2020). The Turing Test is intended to assess a machine’s capacity to display intelligent behaviour that is comparable to that of a person (Turing, 1950).
Alan Turing was a brilliant British mathematician and computer scientist. He contributed to the development of artificial intelligence by proposing the concept of a universal computing machine (Turing machine) and by formulating the famous Turing test to identify intelligence based on a machine’s ability to mimic human conversation. Turing believed that intelligence could be identified through a machine’s capability to engage in indistinguishable conversation with a human evaluator (OpenAI, 2023).
John McCarthy
John McCarthy, an American Computer Scientist who we now known as “the Father of AI”. He dedicated his research to Artificial Intelligence by developing time-sharing and inventing the first programming language – LISP (Stanford University, n.d.). His idea about intelligence is about the computational part of the ability to solve problems, which could apply to people, animals and even machines (McCarthy, 2007)
John McCarthy was an American computer scientist and one of the pioneers in the field of artificial intelligence (AI). He made significant contributions to AI by coining the term “artificial intelligence” and developing the programming language LISP, which became widely used in AI research. McCarthy believed that intelligence could be identified through the ability to solve complex problems, reason logically, learn from experience, and exhibit human-like behavior in various domains (OpenAI, 2023).
Herbert Simon
Coming from a social science background, Herbert Simon emphasizes data collection as the fundamental key to better analyzing situations and helping people make choices (UBS Nobel Perspective, n.d.). He also introduced a new way of looking at problems and solutions. Compared to the other AI giants, he took a step back to tackle of source of machine learning (UBS Nobel Perspective, n.d.).
Herbert Simon was an American economist and cognitive psychologist. He contributed to the development of artificial intelligence by proposing the concept of “bounded rationality” and developing decision-making models. He believed that intelligence could be identified through problem-solving abilities and the ability to achieve goals efficiently (OpenAI, 2023).
Marvin Minsky
Marvin Minsky was an AI researcher who co-founded MIT’s AI Laboratory and created some of the first neural network learning machines (BBC, 2016). Minsky believed that the brain was a basically a machine that could be replicated in a computer, including the ability for common sense reasoning (BBC, 2016).
Marvin Minsky was a pioneering AI researcher known for his contributions to artificial intelligence. He co-founded the MIT AI Laboratory, developed the concept of neural networks, and explored the idea that intelligence could be understood as a collection of problem-solving heuristics rather than a single algorithm (OpenAI, 2023).
Timnit Gebru
Timnit Gebru is a leading researcher on diversity and Artificial Intelligence who Google forced out, it seems to produce research that in part brings into question Google’s (and others) practices around the use of AI (Hao, 2020). Gebru believed that models like ChatGPT would be dangerous due to its inability to understand cultures that were less represented on the internet and cultural nuances of language (Hao, 2020).
Timnit Gebru was a prominent AI researcher and advocate for diversity in the field. She co-authored influential research on bias in AI systems. Her work emphasized the importance of addressing ethical and social implications in AI, and she believed that intelligence could not be identified without considering broader societal contexts (OpenAI, 2023).
Question 2
How do “machine (programming) languages” differ from human (natural) ones? (~100 words).
Machine and human languages both contain structures and are both used for the same purpose, which is to communicate. That be said there is few key difference between people language and programming language that important as demonstrat this write. Human language changes and evolves and an important aspect of human languages and communication is that even with all the errors in my previous sentence, it can still be understood (Harris, 2018). Programming languages must be perfect or cannot be understood by the machine, will produce errors and not run properly (Harris, 2018). Humans can understand language despite imperfections.
Programming languages are artificial, formal systems designed for instructing computers, emphasizing precision, and using strict syntax and semantics. They serve to create algorithms and software. In contrast, human languages are natural, evolving communication tools used by people to convey thoughts and emotions, featuring nuanced grammar, context, and cultural elements. While human languages prioritize expressive communication, programming languages focus on conveying explicit instructions to machines (OpenAI, 2023).
Question 3
How does “machine (artificial) intelligence” differ from the human version? (~100 words).
Machine/AI Intelligence is basically the level of intelligence of a poorly done research paper, one where a student just pieces together data from a bunch of different sources and inputs without adding in their own original thoughts and ideas. Based on the competence of the people who designed the AI, the AI will be more or less effective at these tasks but at this point, AI does not appear to be able to handle tasks which deviates significantly from its training data or assumptions of its creators (Chollet, 2019, p. 3).
Machine intelligence, or artificial intelligence (AI), refers to computer systems designed to perform tasks that typically require human intelligence, like learning, problem-solving, and decision-making, but it operates based on algorithms and data. Human intelligence, on the other hand, encompasses a broader range of capabilities, including emotional understanding, creativity, empathy, and complex reasoning, often influenced by emotions and consciousness. Human intelligence is highly adaptable, can handle diverse tasks with minimal training, and possesses the ability to understand context, nuances, and the world’s intricacies, whereas machine intelligence is limited to specific, programmed tasks and lacks consciousness or emotional understanding (OpenAI, 2023).
Question 4
How does “machine learning” differ from human learning? (~100 words)
Machine learning differs from human learning in that it does not adapt or evolve unless given new data and it’s outputs will be determined based off of the inputs it has received. An easy example of this is that a machine that is fed racist data will always end up racist (Buolamwini, 2019). A child with racist parents may and is probably more likely to end up racist but could also determine on their own that even though they have received prominently racist data, they reject the data and the ideas and do not hold onto those racist ideas (Heilweil, 2020).
Machine learning is a subset of artificial intelligence where computers learn from data and make predictions or decisions without being explicitly programmed. It relies on algorithms and statistical patterns. Human learning is the cognitive process by which individuals acquire knowledge, skills, and understanding through experience, education, and observation. It involves complex cognitive functions, emotional awareness, and the ability to generalize knowledge across various domains. Unlike machines, humans can adapt to new situations, demonstrate creativity, and possess consciousness, making their learning process far more versatile and nuanced than that of machines (OpenAI, 2023).
Question 5
How do YOUR answers to these questions differ from what a machine could generate? make sure you reference the specific differences between your answers and ChatGPT's. (~200 words)
Extrapolating based on a comparison between ChatGPT and my own writing there are a couple of key differences between the writing of the machine versus my own writing. Machines will put out formal, grammatically correct responses each and every time, unless instructed otherwise. The machines do not have the ability to judge context in the same way we do in order to determine the structure or level of formality to give its output. In order to prove a point, I intentionally made errors in one of my responses, something I would be shocked to see from a machine answering the same question. As a EAL learner, I also know I may not have perfect syntax, structure or word choices but am generally forgiven for these mistakes as most people do not get hung up on small mistakes. I would not expect to see the same types of mistakes made by a machine, nor do I think people would be as forgiving of a machine as they are of me. I also have never fabricated sources for my research (Neumeister, 2023). My answers also incorporated life experience, general knowledge and personal opinion, something the machine responses did not.
References:
BBC. (2016, January 26). Ai pioneer Marvin Minsky dies aged 88. BBC News. https://www.bbc.com/news/technology-35409119
Biography.com Editors. (2020, July 23). Alan Turing Biography. The Biography.com. https://www.biography.com/scientists/alan-turing
Buolamwini, J. (2019, February 7). Artificial intelligence has a problem with gender and racial bias. Here’s how to solve it. Time. Retrieved from https://time.com/5520558/ai-artificial-intelligence-bias-gender-race/
Chollet, F. (2019). On the measure of intelligence. https://doi.org/10.48550/arxiv.1911.01547
Harris, A. (2018, October 31). Human languages vs. programming languages. Medium.
Hao, K. (2020). We read the paper that forced Timnit Gebru out of Google. Here’s what it says. MIT Technology Review.https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru
Heilweil, R. (2020, February 18). Why algorithms can be racist and sexist. A computer can make a decision faster. That doesn’t make it fair. Vox. Retrieved from https://www.vox.com/recode/2020/2/18/21028526/algorithms-ai-machine-learning-race-gender-bias
McCarthy, J. (2007). What Is Artificial Intelligence? http://jmc.stanford.edu/articles/whatisai/whatisai.pdf
Neumeister, L. (2023, June 8). Lawyers blame ChatGPT for tricking them into citing bogus case law. AP News. https://apnews.com/article/artificial-intelligence-chatgpt-courts-e15023d7e6fdf4f099aa122437dbb59b
OpenAI. (2023). ChatGPT (GPT-3.5 version) [Large language model]. https://chat.openai.com
Stanford University (n.d.). Professor John McCarthy. http://jmc.stanford.edu/index.html
UBS Nobel Perspectives. (n.d.). Herbert Simon: Father of Artificial Intelligence. https://www.ubs.com/microsites/nobel-perspectives/en/laureates/herbert-simon.html