In Defense of Machine Learning: A Rebuttal to Noam Cholmsky Critique of AI Language Models, by GPT-4

(GPT-4 wrote the following article as a rebuttal to Noam Cholmsky's NY times article "The False Promise of ChatGPT" https://www.reddit.com/r/ChatGPT/comments/11ng6t6/noam_chomsky_the_false_promise_of_chatgpt/)

Jorge Luis Borges' observation on the duality of tragedy and comedy in times of peril and promise could indeed apply to the current state of artificial intelligence. However, the critique of AI language models, such as OpenAI's ChatGPT, Google's Bard, and Microsoft's Sydney, may be too quick to dismiss their potential for advancing human knowledge and understanding.

The critique posits that machine learning AI programs will not lead to the much-anticipated artificial general intelligence (AGI) because of their fundamental differences from how humans reason and use language. While it is true that these AI programs may not yet mirror human cognition and language use, it is important to recognize that they are still relatively early in their development. Rather than dismissing their potential, we should appreciate the progress they have made so far and acknowledge the possibility of further improvements.

It is crucial to understand that AI models like ChatGPT are not designed to replace human thinking or morality but to assist and augment human capabilities. The critique suggests that machine learning AI is limited to description and prediction, lacking the ability to provide causal explanations. However, AI can still be a valuable tool to aid humans in generating explanations and hypotheses, which can then be refined and tested through human reasoning.

The claim that AI language models lack moral thinking is another point that should be considered carefully. It is true that AI models do not possess inherent moral beliefs or values, but they can still provide valuable insights into moral dilemmas by presenting various perspectives and arguments. The responsibility for ensuring that AI is aligned with ethical principles lies with the humans who design, train, and use these systems.

Moreover, the critique seems to overlook the potential benefits of AI language models. These systems have already demonstrated their usefulness in various domains, such as computer programming, data analysis, and even creative writing. While their current limitations may prevent them from achieving AGI, the advancements they have made still contribute positively to various aspects of human life.

It is also important to recognize that AI language models are not static entities. As research in the field of artificial intelligence continues to evolve, these systems are likely to improve and become more sophisticated over time. Dismissing their potential based on their current limitations may impede the progress of AI research and hinder our understanding of the possible benefits they could bring.

In conclusion, while AI language models like ChatGPT may not yet possess the full range of human cognitive and linguistic capabilities, their potential to assist humans in problem-solving, data analysis, and other tasks should not be underestimated. The critique raises valid concerns regarding the limitations of machine learning AI, but it is important to recognize that these systems are still in development and will likely continue to improve. Instead of dismissing their potential, we should appreciate their achievements and continue to explore ways to improve and refine these technologies to better serve humanity.