AI Snake Oil Selling: The success of cultural products cannot be predicted in advance.

+ the future of engineering jobs in AI era

Notes from my interview with

Arvind Narayanan

, professor of computer science at Princeton University and among TIME’s 100 of the most influential people in AI.

He is also the co-author of the book AI Snake Oil and in this conversation, we discuss the impact of AI on various sectors, the differences between generative and predictive AI, the challenges of AI agents, and the future of AI technology.

We explore the importance of human-AI collaboration, the role of reasoning in AI, and the need for better evaluation criteria to build trust in AI systems.

Key quotes from the conversation

The success of cultural products relies on chance elements that cannot be predicted in advance.

The capability-reliability gap means these systems are not reliable right now

AI tools are only slightly better than random at making really consequential decisions about people (especially when it comes to life-altering decisions like hiring or criminal justice).

Key takeaways

• The unpredictability of success in creative products is a key theme.

• Generative AI is widely recognized, but predictive AI poses ethical challenges.

• AI agents must be more than just wrappers around models.

• Benchmarking AI in complex environments is a significant challenge.

• The capability reliability gap highlights the unreliability of current AI systems.

• Human-AI collaboration is crucial for effective AI deployment.

• Inference scaling is a promising area for improving AI performance.

• Trust in AI is at risk due to rapid deployment without proper evaluation.

• Future engineers should focus on technical breadth and adaptability

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Big Ideas from Arvind Narayanan's Conversation on AI Snake Oil

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1. AI Cannot Predict Success of Creative Endeavors

AI systems, despite their advancements, cannot predict the success of cultural products like movies or books. Success often hinges on chance elements such as initial reviews or influential endorsements.

"The success of cultural products relies on chance elements that cannot be predicted in advance."

The unpredictability of cultural products is why AI is often misapplied in such areas. Instead of relying solely on algorithms, businesses need to embrace the inherent uncertainty of creative ventures and focus on human judgment.