If large language models like GPT-3 preferably produce a particular point of view, they may influence people's opinions on an unknown scale. This study investigates whether a language-model-powered writing assistant that generates some opinions more often than others impacts what users write - and what they think. In an online experiment, we asked participants (N=1,506) to write a post discussing whether social media is good for society. Treatment group participants used a language-model-powered writing assistant configured to argue that social media is good or bad for society. Participants then completed a social media attitude survey, and independent judges (N=500) evaluated the opinions expressed in their writing. Using the opinionated language model affected the opinions expressed in participants' writing and shifted their opinions in the subsequent attitude survey. We discuss the wider implications of our results and argue that the opinions built into AI language technologies need to be monitored and engineered more carefully.

The tool, which is available at no charge, is itself based on an AI model. It can detect text generated by not only OpenAI's neural networks but also competing software from other companies. However, the startup cautioned that the tool currently has a number of significant accuracy limitations.

I also got an "unclear" result for some articles written by CNET Money, with others getting an "unlikely" classification. The outlet says these articles were "assisted by an AI engine and reviewed, fact-checked and edited by our editorial staff," so there are likely some human tweaks in there (especially since CNET has added corrections to over half of them). While CNET's owner hasn't said which specific system it's using for the articles, my co-worker Mia Sato has reported that it's used a tool called Wordsmith for some of its content. OpenAI says its tool isn't just for GPT, though, and that it should detect "text written by AIs from a variety of providers."

OpenAI has released a tool to help you determine whether text was more likely written by a human or AI. However, the ChatGPT maker warns that its equivalent of Blade Runner's Voight-Kampff test can also get it wrong. The tool includes a box where you can paste text that's at least 1,000 characters long. It will then spit out a verdict, like "The classifier considers the text to be very unlikely AI-generated" or "The classifier considers the text to be possibly AI-generated." I tested it by prompting ChatGPT to write an essay about the migratory patterns of birds, which the detection tool then described as "possibly AI-generated."

Language is commonly understood to be the "stuff" of thought. People "talk it out" and "speak their mind," follow "trains of thought" or "streams of consciousness." Some of the pinnacles of human creation--music, geometry, computer programming--are framed as metaphorical languages. The underlying assumption is that the brain processes the world and our experience of it through a progression of words. And this supposed link between language and thinking is a large part of what makes ChatGPT and similar programs so uncanny: The ability of AI to answer any prompt with human-sounding language can suggest that the machine has some sort of intent, even sentience.

OpenAI, the creator of the language tool ChatGPT and image generator Dall-E, could be facing some new, three-dimensional competition on the blockchain. In an introductory video, the brand says users will be able to type in text to generate responsive characters with "unique personalities, identities, traits, voices, and bodies." Users can mint the NFTs at mycharacter.ai. It remains to be seen whether CharacterGPT will gain the popularity of either ChatGPT or OpenAI's bot-powered Dall-E, which attracts 1.5 million users a day. The CharacterGPT blockchain product looks poised to more directly compete with Dall-E rather than ChatGPT, which generates text responses to typed questions. It has created massive interest through its ability to write convincing articles, cover letters, emails, and messages on dating apps.

The language in Nature was pretty mild as far as freakouts go. ChatGPT and other similar A.I. tools, the editors wrote, threaten "the transparency and trust-worthiness that the process of generating knowledge relies on … ultimately, research must have transparency in methods, and integrity and truth from authors." The editor of Nature's chief rival, Science, similarly blew his stack in a most genteel manner: "An AI program cannot be an author. A violation of these policies will constitute scientific misconduct no different from altered images or plagiarism of existing works," he wrote. These might seem like gentle warnings, but to academics who submit research papers to peer-reviewed journals like Science and Nature, the specter of being charged with research misconduct--potentially a career-wrecking accusation--for using A.I. is about as subtle as an air-raid siren.

Josh Tobin, the co-founder and CEO of machine learning tool provider Gantry, didn't want to believe it at first. But Tobin, who previously worked as a research scientist at OpenAI, eventually came to the conclusion that it was true: The end of traditional ML modeling is upon us. The idea that you didn't need to train a machine learning model anymore and can get better results by just using off-the-shelf models without any tuning on your own custom data seemed wrong to Tobin, who spent years learning how to build these systems. When he first heard of the idea after starting his ML tool business Gantry, which he co-founded in 2021 with fellow OpenAI alum Vicky Cheung, he didn't want to believe it. "The first four or five times I heard that, my thinking was like, okay, these companies just don't know what they're doing," Tobin said.

Robocorp CMO Dave Dabbah is a full-stack marketing leader with a proven record of success driving growth and brand recognition. The ChatGPT revolution has officially gone into full unicorn mode, which theoretically should mean that marketers across the globe can now significantly increase their ability to produce high-quality content at scale. I'll let the cat out of the bag early in this article to say that I believe the underlying technology that makes ChatGPT so good will revolutionize how marketing teams produce content in the future. Although "revolutionize" is an overused term, the potentially far-reaching effects of an AI-powered service delivering high-quality content are among the most exciting developments in the tech industry that I have seen, reminiscent of the game-changing impact of Napster (in which I may have downloaded the entire Nirvana collection in under 60 seconds). I believe that the introduction of ChatGPT, which utilizes AI to deliver information, will be as impactful on content producers as the birth of the internet.

Not all of us are skilled in the language of love, and when it comes to Valentine's Day, there is all the more pressure to find the right words to express how we feel. Fear not, as artificial intelligence (AI) is here to turn your greetings card into a work of Shakespeare, or at least Enrique Iglesias. Moonpig has revealed it is looking into integrating ChatGPT - the AI chatbot taking the world by storm - into its online platform. This means that customers will be able to use the large language model to write a personalised message for inside their card. OpenAI says its ChatGPT model has been trained using a machine learning technique called Reinforcement Learning from Human Feedback (RLHF). This can simulate dialogue, answer follow-up questions, admit mistakes, challenge incorrect premises and reject inappropriate requests.