Anti-Hallucination Add-on for AI Services Possibility
Posted: Thu Jul 10, 2025 10:51 am
Posted in News |
Posted onMay 3, 2023by Brewster Kahle
Chatbots, like OpenIA’s ChatGPT, Google’s Bard and others, have a hallucination problem (their term, not ours). It can make something up and state it authoritatively. It is a real problem. But there can be an old-fashioned answer, as a parent might say: “Look it up!”
Imagine for a moment the Internet Archive, working with responsible AI companies and research projects, could automate “Looking it Up” in a vast library to make those services more dependable, reliable, and trustworthy. How?
The Internet Archive and AI companies could offer an anti-hallucination service ‘add-on’ to the chatbots that could cite supporting evidence and counter claims to chatbot assertions by leveraging the library collections at the Internet Archive (most of which were published before generative AI).
By citing evidence for and against assertions based on papers, books, newspapers, magazines, books, TV, radio, government documents, we can build a stronger, more reliable knowledge phone number database infrastructure for a generation that turns to their screens for answers. Although many of these generative AI companies are already, or are intending, to link their models to the internet, what the Internet Archive can uniquely offer is our vast collection of “historical internet” content. We have been archiving the web for 27 years, which means we have decades of human-generated knowledge. This might become invaluable in an age when we might see a drastic increase in AI-generated content. So an Internet Archive add-on is not just a matter of leveraging knowledge available on the internet, but also knowledge available on the history of the internet.
Is this possible? We think yes because we are already doing something like this for Wikipedia by hand and with special-purpose robots like Internet Archive Bot Wikipedia communities, and these bots, have fixed over 17 million broken links, and have linked one million assertions to specific pages in over 250,000 books.
Posted onMay 3, 2023by Brewster Kahle
Chatbots, like OpenIA’s ChatGPT, Google’s Bard and others, have a hallucination problem (their term, not ours). It can make something up and state it authoritatively. It is a real problem. But there can be an old-fashioned answer, as a parent might say: “Look it up!”
Imagine for a moment the Internet Archive, working with responsible AI companies and research projects, could automate “Looking it Up” in a vast library to make those services more dependable, reliable, and trustworthy. How?
The Internet Archive and AI companies could offer an anti-hallucination service ‘add-on’ to the chatbots that could cite supporting evidence and counter claims to chatbot assertions by leveraging the library collections at the Internet Archive (most of which were published before generative AI).
By citing evidence for and against assertions based on papers, books, newspapers, magazines, books, TV, radio, government documents, we can build a stronger, more reliable knowledge phone number database infrastructure for a generation that turns to their screens for answers. Although many of these generative AI companies are already, or are intending, to link their models to the internet, what the Internet Archive can uniquely offer is our vast collection of “historical internet” content. We have been archiving the web for 27 years, which means we have decades of human-generated knowledge. This might become invaluable in an age when we might see a drastic increase in AI-generated content. So an Internet Archive add-on is not just a matter of leveraging knowledge available on the internet, but also knowledge available on the history of the internet.
Is this possible? We think yes because we are already doing something like this for Wikipedia by hand and with special-purpose robots like Internet Archive Bot Wikipedia communities, and these bots, have fixed over 17 million broken links, and have linked one million assertions to specific pages in over 250,000 books.