What ChatGPT and generative AI mean for science

What ChatGPT and generative AI mean for science

Nature reports:

In December, computational biologists Casey Greene and Milton Pividori embarked on an unusual experiment: they asked an assistant who was not a scientist to help them improve three of their research papers. Their assiduous aide suggested revisions to sections of documents in seconds; each manuscript took about five minutes to review. In one biology manuscript, their helper even spotted a mistake in a reference to an equation. The trial didn’t always run smoothly, but the final manuscripts were easier to read — and the fees were modest, at less than US$0.50 per document.

This assistant, as Greene and Pividori reported in a preprint on 23 January, is not a person but an artificial-intelligence (AI) algorithm called GPT-3, first released in 2020. It is one of the much-hyped generative AI chatbot-style tools that can churn out convincingly fluent text, whether asked to produce prose, poetry, computer code or — as in the scientists’ case — to edit research papers (see ‘How an AI chatbot edits a manuscript’ at the end of this article).

The most famous of these tools, also known as large language models, or LLMs, is ChatGPT, a version of GPT-3 that shot to fame after its release in November last year because it was made free and easily accessible. Other generative AIs can produce images, or sounds.

“I’m really impressed,” says Pividori, who works at the University of Pennsylvania in Philadelphia. “This will help us be more productive as researchers.” Other scientists say they now regularly use LLMs not only to edit manuscripts, but also to help them write or check code and to brainstorm ideas. “I use LLMs every day now,” says Hafsteinn Einarsson, a computer scientist at the University of Iceland in Reykjavik. He started with GPT-3, but has since switched to ChatGPT, which helps him to write presentation slides, student exams and coursework problems, and to convert student theses into papers. “Many people are using it as a digital secretary or assistant,” he says.

LLMs form part of search engines, code-writing assistants and even a chatbot that negotiates with other companies’ chatbots to get better prices on products. ChatGPT’s creator, OpenAI in San Francisco, California, has announced a subscription service for $20 per month, promising faster response times and priority access to new features (although its trial version remains free). And tech giant Microsoft, which had already invested in OpenAI, announced a further investment in January, reported to be around $10 billion. LLMs are destined to be incorporated into general word- and data-processing software. Generative AI’s future ubiquity in society seems assured, especially because today’s tools represent the technology in its infancy.

But LLMs have also triggered widespread concern — from their propensity to return falsehoods, to worries about people passing off AI-generated text as their own. When Nature asked researchers about the potential uses of chatbots such as ChatGPT, particularly in science, their excitement was tempered with apprehension. “If you believe that this technology has the potential to be transformative, then I think you have to be nervous about it,” says Greene, at the University of Colorado School of Medicine in Aurora. Much will depend on how future regulations and guidelines might constrain AI chatbots’ use, researchers say. [Continue reading…]

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