This article presents a comparative analysis of the ability of two large language model (LLM)-based chatbots, ChatGPT and Bing Chat, recently rebranded to Microsoft Copilot, to detect veracity of political information. We use AI auditing methodology to investigate how chatbots evaluate true, false, and borderline statements on five topics: COVID-19, Russian aggression against Ukraine, the Holocaust, climate change, and LGBTQ+ related debates. We compare how the chatbots perform in high- and low-resource languages by using prompts in English, Russian, and Ukrainian. Furthermore, we explore the ability of chatbots to evaluate statements according to political communication concepts of disinformation, misinformation, and conspiracy theory, using definition-oriented prompts. We also systematically test how such evaluations are influenced by source bias which we model by attributing specific claims to various political and social actors. The results show high performance of ChatGPT for the baseline veracity evaluation task, with 72 percent of the cases evaluated correctly on average across languages without pre-training. Bing Chat performed worse with a 67 percent accuracy. We observe significant disparities in how chatbots evaluate prompts in high- and low-resource languages and how they adapt their evaluations to political communication concepts with ChatGPT providing more nuanced outputs than Bing Chat. Finally, we find that for some veracity detection-related tasks, the performance of chatbots varied depending on the topic of the statement or the source to which it is attributed. These findings highlight the potential of LLM-based chatbots in tackling different forms of false information in online environments, but also points to the substantial variation in terms of how such potential is realized due to specific factors, such as language of the prompt or the topic.

Knowledge and accuracy: LaMDA can access the internet for the latest information, while both GPT-3 and even GPT-4 have knowledge cut-off dates of September 2021. If asked about more up-to-date events, these models could generate fictional responses. Training data: LaMDA's training dataset comprised primarily of dialog, while GPT-3 used everything from Wikipedia entries to traditional books. That makes GPT-3 more general-purpose and adaptable for applications like ChatGPT. Human training: In the previous section, we talked about how Google hired human workers to fine-tune its model for safety and quality.

Over the past few months, AI chatbots like ChatGPT have captured the world's attention due to their ability to converse in a human-like way on just about any subject. But they come with a serious drawback: They can present convincing false information easily, making them unreliable sources of factual information and potential sources of defamation. Why do AI chatbots make things up, and will we ever be able to fully trust their output? We asked several experts and dug into how these AI models work to find the answers. AI chatbots such as OpenAI's ChatGPT rely on a type of AI called a « large language model » (LLM) to generate their responses.

Over the past few months, AI chatbots like ChatGPT have captured the world's attention due to their ability to converse in a human-like way on just about any subject. But they come with a serious drawback: They can present convincing false information easily, making them unreliable sources of factual information and potential sources of defamation. Why do AI chatbots make things up, and will we ever be able to fully trust their output? We asked several experts and dug into how these AI models work to find the answers. AI chatbots such as OpenAI's ChatGPT rely on a type of AI called a "large language model" (LLM) to generate their responses. An LLM is a computer program trained on millions of text sources that can read and generate "natural language" text--language as humans would naturally write or talk.

Bing Chat and ChatGPT are two of the latest natural language chatbots to become widely available, and both are competing for your attention and text prompts. Both AIs are based on similar language models, but there are some distinct differences between them, making the ChatGPT versus Bing Chat debate one well worth having. If you want to play around with these two exciting tools, here's everything you need to know to pick the right one for you. Both Bing Chat and ChatGPT are available for general use, but the way you access them is a little different. GPT-4 claims to be 40% better at producing'factual responses' Microsoft's Bing Chat: how to join the waitlist now ChatGPT is widely available and accessible through the main OpenAI website.

On Monday, Snapchat announced an experimental AI-powered conversational chatbot called "My AI," powered by ChatGPT-style technology from OpenAI. My AI will be available for $3.99 a month for Snapchat subscribers and is rolling out "this week," according to a news post from Snap, Inc. Users will be able to personalize the AI bot by giving it a custom name. Conversations with the AI model will take place in a similar interface to a regular chat with a human. "The big idea is that in addition to talking to our friends and family every day, we're going to talk to AI every day," Snap CEO Evan Spiegel told The Verge. But like its GPT-powered cousins, ChatGPT and Bing Chat, Snap says that My AI is prone to "hallucinations," which are unexpected falsehoods generated by an AI model. "As with all AI-powered chatbots, My AI is prone to hallucination and can be tricked into saying just about anything.