Aaron Margolis, a data scientist, says that new chat bots are remarkable but that their answers can conflate fact with fiction. Photo / Valerie Plesch, The New York Times
Siri, Google Search, online marketing and your child’s homework will never be the same. Then there’s the misinformation problem.
This month, Jeremy Howard, an artificial intelligence researcher, introduced an online chatbot called ChatGPT to his 7-year-old daughter. It had been released a few days earlier by OpenAI, one of the world’s most ambitious AI labs.
He told her to ask the experimental chatbot whatever came to mind. She asked what trigonometry was good for, where black holes came from and why chickens incubated their eggs. Each time, it answered in clear, well-punctuated prose. When she asked for a computer program that could predict the path of a ball thrown through the air, it gave her that, too.
Over the next few days, Howard — a data scientist and professor whose work inspired the creation of ChatGPT and similar technologies — came to see the chatbot as a new kind of personal tutor. It could teach his daughter math, science and English, not to mention a few other important lessons. Chief among them: Do not believe everything you are told.
“It is a thrill to see her learn like this,” he said. “But I also told her, ‘Don’t trust everything it gives you. It can make mistakes.’”
OpenAI is among the many companies, academic labs and independent researchers working to build more advanced chatbots. These systems cannot exactly chat like a human, but they often seem to. They can also retrieve and repackage information with a speed that humans never could. They can be thought of as digital assistants — like Siri or Alexa — that are better at understanding what you are looking for and giving it to you.
After the release of ChatGPT — which has been used by more than 1 million people — many experts believe these new chatbots are poised to reinvent or even replace internet search engines such as Google and Bing.
They can serve up information in tight sentences, rather than long lists of blue links. They explain concepts in ways that people can understand. And they can deliver facts, while also generating business plans, term paper topics and other new ideas from scratch.
“You now have a computer that can answer any question in a way that makes sense to a human,” said Aaron Levie, CEO of a Silicon Valley company, Box, and one of the many executives exploring the ways these chatbots will change the technological landscape. “It can extrapolate and take ideas from different contexts and merge them together.”
The new chatbots do this with what seems like complete confidence. But they do not always tell the truth. Sometimes, they even fail at simple arithmetic. They blend fact with fiction. And as they continue to improve, people could use them to generate and spread untruths.
Google recently built a system specifically for conversation, called LaMDA, or Language Model for Dialogue Applications. This spring, a Google engineer claimed it was sentient. It was not, but it captured the public’s imagination.
Aaron Margolis, a data scientist in Arlington, Virginia, was among the limited number of people outside Google allowed to use LaMDA through an experimental Google app, AI Test Kitchen. He was consistently amazed by its talent for open-ended conversation. It kept him entertained. But he warned that it could be a bit of a fabulist — as was to be expected from a system trained from vast amounts of information posted to the internet.
“What it gives you is kind of like an Aaron Sorkin movie,” he said. Sorkin wrote The Social Network, a movie often criticized for stretching the truth about the origin of Facebook. “Parts of it will be true, and parts will not be true.”
He recently asked both LaMDA and ChatGPT to chat with him as if it were Mark Twain. When he asked LaMDA, it soon described a meeting between Twain and Levi Strauss and said the writer had worked for the bluejeans mogul while living in San Francisco in the mid-1800s. It seemed true. But it was not. Twain and Strauss lived in San Francisco at the same time, but they never worked together.
Scientists call that problem “hallucination.” Much like a good storyteller, chatbots have a way of taking what they have learned and reshaping it into something new — with no regard for whether it is true.
LaMDA is what artificial intelligence researchers call a neural network, a mathematical system loosely modelled on the network of neurons in the brain. This is the same technology that translates between French and English on services like Google Translate and identifies pedestrians as self-driving cars navigate city streets.
A neural network learns skills by analyzing data. By pinpointing patterns in thousands of cat photos, for example, it can learn to recognise a cat.
Five years ago, researchers at Google and labs like OpenAI started designing neural networks that analysed enormous amounts of digital text, including books, Wikipedia articles, news stories and online chat logs. Scientists call them “large language models.” Identifying billions of distinct patterns in the way people connect words, numbers and symbols, these systems learned to generate text on their own.
Their ability to generate language surprised many researchers in the field, including many of the researchers who built them. The technology could mimic what people had written and combine disparate concepts. You could ask it to write a Seinfeld scene in which Jerry learns an esoteric mathematical technique called a bubble sort algorithm — and it would.
Best ChatGPT prompt so far 😂 https://t.co/MNWOAJ8XXZ
— Andrej Karpathy (@karpathy) December 2, 2022
With ChatGPT, OpenAI has worked to refine the technology. It does not do free-flowing conversation as well as Google’s LaMDA. It was designed to operate more like Siri, Alexa and other digital assistants. Like LaMDA, ChatGPT was trained on a sea of digital text culled from the internet.
As people tested the system, it asked them to rate its responses. Were they convincing? Were they useful? Were they truthful? Then, through a technique called reinforcement learning, it used the ratings to hone the system and more carefully define what it would and would not do.
“This allows us to get to the point where the model can interact with you and admit when it’s wrong,” said Mira Murati, OpenAI’s chief technology officer. “It can reject something that is inappropriate, and it can challenge a question or a premise that is incorrect.”
The method was not perfect. OpenAI warned those using ChatGPT that it “may occasionally generate incorrect information” and “produce harmful instructions or biased content.” But the company plans to continue refining the technology and reminds people using it that it is still a research project.
Google, Meta and other companies are also addressing accuracy issues. Meta recently removed an online preview of its chatbot, Galactica, because it repeatedly generated incorrect and biased information.
Experts have warned that companies do not control the fate of these technologies. Systems such as ChatGPT, LaMDA and Galactica are based on ideas, research papers and computer code that have circulated freely for years.
Companies such as Google and OpenAI can push the technology forward at a faster rate than others. But their latest technologies have been reproduced and widely distributed. They cannot prevent people from using these systems to spread misinformation.
Just as Howard hoped that his daughter would learn not to trust everything she read on the internet, he hoped society would learn the same lesson.
“You could program millions of these bots to appear like humans, having conversations designed to convince people of a particular point of view,” he said. “I have warned about this for years. Now it is obvious that this is just waiting to happen.”
This article originally appeared in The New York Times.
Written by: Cade Metz
Photographs by: David Kelly and Valerie Plesch
©2022 THE NEW YORK TIMES
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