Arvind Narayanan, a computer science professor at Princeton University, and PhD candidate Sayash Kapoor want to dispel myths about artificial intelligence (AI). Their book, AI Snake Oil, is based on their Substack weekly of the same name and takes a critical look at the hype around AI. They do, however, explain that they are not opposed to AI technology in general, but rather to particular groups’ deceptive statements and excessive promises.
Narayanan and Kapoor contend that the present AI hype cycle is fueled by three key groups: firms selling AI, researchers pushing AI, and journalists reporting it. Their book delves into how these organizations lead to uncertainty and misinterpretation of AI’s genuine capabilities.
The Misleading Claims of AI Companies
Companies that employ AI to anticipate the future, frequently with negative effects, are among the most heavily chastised in the book. For example, they highlight a Dutch algorithm that mistakenly identified women and immigrants as benefit fraud merely because they did not fit the typical description. Narayanan and Kapoor contend that such AI technologies are defective and unfairly impact minority areas.
They also look at firms that focus on the long-term dangers of AI, such as the concept of developing artificial general intelligence (AGI)—a system smarter than humans. While they do not completely deny AGI, they blame firms for emphasizing long-term existential dangers over the immediate harm that AI systems might inflict in the present.
Faulty Research and Data Leakage
The researchers also criticize low-quality studies, particularly those affected by “data leakage,” a widespread problem in AI research. This occurs when AI models are tested using part of the same data on which they were trained, resulting in unduly optimistic outcomes. Kapoor argues that such inaccuracies lead to unreasonable expectations of AI performance.
The Role of Journalists in Spreading AI Hype
According to Narayanan and Kapoor, media play an important role in disseminating AI hype. Many news stories regarding AI are just rehashed versions of company press releases, providing the public an inaccurate picture of the technology. The writers also criticize hyperbolic tales, such as one in The New York Times that inflated a chatbot’s capabilities, giving the impression that the AI had human-like aspirations. This sort of coverage, they claim, misleads the public into believing AI is more advanced than it is.
Education: The Key to Understanding AI
Narayanan and Kapoor feel that greater education is the key to combating the AI hype. They think that people should have a better knowledge of what AI is and isn’t. AI comprises a vast range of tools and approaches, yet the phrase is frequently used loosely, making it difficult to understand its full potential. In their book, they categorize AI into two types: predictive AI, which utilizes data to forecast future events, and generative AI, which creates content based on previous data.
Understanding these distinctions and mastering the fundamentals of AI, such as machine learning and neural networks, can assist to demystify the technology. Narayanan even thinks that teaching children about AI from an early age is critical, as he has done with his own children.
The authors emphasize that AI is here to stay, and its impact will only expand. As a result, individuals must get a better knowledge of AI’s capabilities and limits, which can only be accomplished via education.
This article is based on the original story by Reece Rogers, which appeared in WIRED on September 24, 2024. You can check out the full article here.
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