The podcast discusses the potential impact of AI on Wikipedia and the concerns raised by editors. It explores the flaws and strengths of Wikipedia as a source of information and the challenges of generative AI. The chapter also explores the use of AI models to assist Wikipedia volunteers and the importance of human involvement in AI systems.
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Quick takeaways
Wikipedia's structured format and vast factual information make it a valuable resource for training AI language models.
AI chatbots face challenges in maintaining factual accuracy and risk the inclusion of fictional elements.
Deep dives
Importance of Diverse Representation in Clinical Trials
The podcast highlights the need for diverse representation in clinical trials, particularly among black patients. The speaker, Dr. Priscilla Pemu, emphasizes that black patients are often not asked to participate or lack access to trials. Inclusivity is crucial for medical innovation.
The Role of Wikipedia in AI Model Training
The podcast explores the significant role that Wikipedia plays in training AI language models. Large language models like GPT-3 rely on massive knowledge banks, often ingesting over a trillion words. Wikipedia's structured format and vast factual information, maintained by dedicated editors, make it a valuable resource for AI model training.
Challenges of AI Chatbots and Factual Accuracy
The podcast discusses the challenges faced by AI chatbots in maintaining factual accuracy. These chatbots aim to converse fluently like humans but may mix fictional elements, hallucinate, or oversimplify complex topics. Dependence on synthetic data and self-generated content poses potential risks of factual unreliability.
The Future of Wikipedia in the Age of AI
The podcast explores the future of Wikipedia in the context of advancing AI technologies. While AI poses challenges, such as reduced traffic and the potential use of AI-generated content, there is hope that collaborative efforts between Wikipedia and AI companies can lead to improvements in factuality, attribution, and alignment.
In early 2021, a Wikipedia editor peered into the future and saw what looked like a funnel cloud on the horizon: the rise of GPT-3, a precursor to the new chatbots from OpenAI. When this editor — a prolific Wikipedian who goes by the handle Barkeep49 on the site — gave the new technology a try, he could see that it was untrustworthy. The bot would readily mix fictional elements (a false name, a false academic citation) into otherwise factual and coherent answers. But he had no doubts about its potential. “I think A.I.’s day of writing a high-quality encyclopedia is coming sooner rather than later,” he wrote in “Death of Wikipedia,” an essay that he posted under his handle on Wikipedia itself. He speculated that a computerized model could, in time, displace his beloved website and its human editors, just as Wikipedia had supplanted the Encyclopaedia Britannica, which in 2012 announced it was discontinuing its print publication.
Recently, when I asked this editor if he still worried about his encyclopedia’s fate, he told me that the newer versions made him more convinced that ChatGPT was a threat. “It wouldn’t surprise me if things are fine for the next three years,” he said of Wikipedia, “and then, all of a sudden, in Year 4 or 5, things drop off a cliff.”
This story was recorded by Audm. To hear more audio stories from publications like The New York Times, download Audm for iPhone or Android.
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