What is AI?) // just tech/science, no magic
Artificial intelligence (AI) is a very broad concept with many different definitions from various perspectives.
One definition of AI is the imitation of cognitive functions that humans can perform, but computers typically cannot.
All modern AI revolves around statistics, but it cannot solve newly emerging problems. Old symbolic reasoning doesn’t work either; it is limited by computing power. There is no real AI, but a lot of speculations around..
Summary from the article:
Artificial intelligence (AI) is a term that encompasses a variety of technologies designed to perform tasks requiring human-like intelligence, such as recognizing faces, understanding speech, and writing sentences. The debate around AI is highly polarized and multifaceted, with enthusiasts claiming it will revolutionize the world and critics warning of its potential dangers and limitations. Despite its widespread influence on the economy, education, and daily life, there is no consensus on what AI truly is, partly due to the rapid pace of its development and the complexity of the underlying science. This ambiguity fuels passionate and often contentious discussions among researchers, industry leaders, and the public, highlighting the need for a clearer understanding of AI’s capabilities and implications.
The debate surrounding AI, particularly large language models like GPT-4, centers on whether these models represent true artificial intelligence or are merely sophisticated statistical tools. The “Shoggoth” meme illustrates the perceived dual nature of AI: a friendly, accessible exterior hiding complex, potentially concerning underpinnings. Despite the AI industry’s optimistic claims about the transformative potential of AI, critics argue that these models lack genuine understanding and reasoning, operating instead as advanced pattern-matching systems. This skepticism is bolstered by concerns about the societal and ethical implications of AI. The controversy is further fueled by the lack of clear definitions and verifiable evidence supporting claims of emerging artificial general intelligence (AGI), leading to polarized views among researchers and industry leaders on the true capabilities and future impact of AI technology.
Margaret Boden, an influential cognitive scientist, discussed the long-standing challenges and debates in AI in a 2014 interview. She emphasized that while there’s no inherent limitation preventing computers from replicating human thinking, the field still lacks “powerful ideas” and theories necessary to achieve this goal. Boden’s reflection on AI’s history reveals that despite over 70 years of progress, we still grapple with defining and recognizing intelligence. The origin of AI, marked by John McCarthy’s 1955 Dartmouth proposal, laid the groundwork for symbolic AI and neural networks, both of which continue to shape the field. The persistent debates reflect deep-rooted disagreements and the enduring allure of creating human-like machines, a vision perpetuated by science fiction and ongoing technological advancements.
The debate around AI transcends academic and scientific realms, incorporating political and moral dimensions that are crucial to understand because AI technology is inevitable and will impact everyone. The motivations and ideologies of influential figures in the tech world, particularly those aligned with the TESCREAL framework — which includes transhumanism and longtermism — significantly shape the development of AI. These ideologies propose that AGI can solve global issues and elevate humanity, yet also harbor risks of catastrophic failure. Critics like Timnit Gebru and Émile Torres argue these techno-utopian beliefs might prioritize the interests of a privileged few while neglecting present-day societal costs such as bias and exploitation. Understanding these ideological underpinnings is essential for making informed decisions about AI’s future and its governance.
