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What are AI hallucinations? Why AIs sometimes make things up

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When someone sees something that isn’t there, people often refer to the experience as a hallucination.

Hallucinations occur when your sensory perception does not correspond to external stimuli.

Technologies that rely on artificial intelligence can have hallucinations, too.

When an algorithmic system generates information that seems plausible but is actually inaccurate or misleading, computer scientists call it an AI hallucination. Researchers have found these behaviors in different types of AI systems, from chatbots such as ChatGPT to image generators such as Dall-E to autonomous vehicles. We are information science researchers who have studied hallucinations in AI speech recognition systems.

Wherever AI systems are used in daily life, their hallucinations can pose risks. Some may be minor – when a chatbot gives the wrong answer to a simple question, the user may end up ill-informed. But in other cases, the stakes are much higher. From courtrooms where AI software is used to make sentencing decisions to health insurance companies that use algorithms to determine a patient’s eligibility for coverage, AI hallucinations can have life-altering consequences. They can even be life-threatening: Autonomous vehicles use AI to detect obstacles, other vehicles and pedestrians.

Making it up

Hallucinations and their effects depend on the type of AI system. With large language models – the underlying technology of AI chatbots – hallucinations are pieces of information that sound convincing but are incorrect, made up or irrelevant. An AI chatbot might create a reference to a scientific article that doesn’t exist or provide a historical fact that is simply wrong, yet make it sound believable.

In a 2023 court case, for example, a New York attorney submitted a legal brief that he had written with the help of ChatGPT. A discerning judge later noticed that the brief cited a case that ChatGPT had made up. This could lead to different outcomes in courtrooms if humans were not able to detect the hallucinated piece of information.

With AI tools that can recognize objects in images, hallucinations occur when the AI generates captions that are not faithful to the provided image. Imagine asking a system to list objects in an image that only includes a woman from the chest up talking on a phone and receiving a response that says a woman talking on a phone while sitting on a bench. This inaccurate information could lead to different consequences in contexts where accuracy is critical.

What causes hallucinations

Engineers build AI systems by gathering massive amounts of data and feeding it into a computational system that detects patterns in the data. The system develops methods for responding to questions or performing tasks based on those patterns.

Supply an AI system with 1,000 photos of different breeds of dogs, labeled accordingly, and the system will soon learn to detect the difference between a poodle and a golden retriever. But feed it a photo of a blueberry muffin and, as machine learning researchers have shown, it may tell you that the muffin is a chihuahua.

two side-by-side four-by-four grids of images
Object recognition AIs can have trouble distinguishing between chihuahuas and blueberry muffins and between sheepdogs and mops.
Shenkman et al, CC BY

When a system doesn’t understand the question or the information that it is presented with, it may hallucinate. Hallucinations often occur when the model fills in gaps based on similar contexts from its training data, or when it is built using biased or incomplete training data. This leads to incorrect guesses, as in the case of the mislabeled blueberry muffin.

It’s important to distinguish between AI hallucinations and intentionally creative AI outputs. When an AI system is asked to be creative – like when writing a story or generating artistic images – its novel outputs are expected and desired. Hallucinations, on the other hand, occur when an AI system is asked to provide factual information or perform specific tasks but instead generates incorrect or misleading content while presenting it as accurate.

The key difference lies in the context and purpose: Creativity is appropriate for artistic tasks, while hallucinations are problematic when accuracy and reliability are required.

To address these issues, companies have suggested using high-quality training data and limiting AI responses to follow certain guidelines. Nevertheless, these issues may persist in popular AI tools.

Large language models hallucinate in several ways.

What’s at risk

The impact of an output such as calling a blueberry muffin a chihuahua may seem trivial, but consider the different kinds of technologies that use image recognition systems: An autonomous vehicle that fails to identify objects could lead to a fatal traffic accident. An autonomous military drone that misidentifies a target could put civilians’ lives in danger.

For AI tools that provide automatic speech recognition, hallucinations are AI transcriptions that include words or phrases that were never actually spoken. This is more likely to occur in noisy environments, where an AI system may end up adding new or irrelevant words in an attempt to decipher background noise such as a passing truck or a crying infant.

As these systems become more regularly integrated into health care, social service and legal settings, hallucinations in automatic speech recognition could lead to inaccurate clinical or legal outcomes that harm patients, criminal defendants or families in need of social support.

Check AI’s work

Regardless of AI companies’ efforts to mitigate hallucinations, users should stay vigilant and question AI outputs, especially when they are used in contexts that require precision and accuracy. Double-checking AI-generated information with trusted sources, consulting experts when necessary, and recognizing the limitations of these tools are essential steps for minimizing their risks.The Conversation

Anna Choi, Ph.D. Candidate in Information Science, Cornell University and Katelyn Mei, Ph.D. Student in Information Science, University of Washington

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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OpenAI Unveils ChatGPT Atlas: The Future of Browsing?

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OpenAI has taken another giant leap forward with the launch of ChatGPT Atlas — an AI-powered web browser that could redefine how people search, explore, and interact online. Investors and competitors are watching closely as this new technology challenges the dominance of traditional browsers like Google Chrome.

With ChatGPT Atlas, users may soon experience a web that feels less like typing into a search box and more like conversing with an intelligent assistant. The integration of AI could make browsing faster, more intuitive, and more personalised than ever before — but it also raises serious questions about privacy and data use.

As AI becomes more deeply embedded in the digital world, ChatGPT Atlas could represent the next major step toward a fully AI-driven online experience. What does this mean for users — and for the tech giants trying to keep up?

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OpenAI limits deepfakes after Bryan Cranston’s concerns

OpenAI protects against deepfakes on Sora 2 after Bryan Cranston and SAG-AFTRA raise concerns over unauthorized AI-generated content

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OpenAI protects against deepfakes on Sora 2 after Bryan Cranston and SAG-AFTRA raise concerns over unauthorised AI-generated content

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In Short:
– OpenAI partners with Bryan Cranston and unions to combat deepfakes on its Sora app.
– The app now includes options for people to control their likenesses and voices.
OpenAI announced it will work with Bryan Cranston, SAG-AFTRA, and actor unions to combat deepfakes on its AI video app, Sora.Cranston voiced concerns after unauthorized AI-generated clips featuring his likeness emerged after Sora 2’s launch in late September. He showed gratitude to OpenAI for taking steps to safeguard actors’ rights to control their likenesses.

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The partnership aims to enhance protections against unauthorized AI content. The Creative Artists Agency and United Talent Agency had previously criticized OpenAI, citing risks to their clients’ intellectual property.

Last week, OpenAI blocked disrespectful videos of Martin Luther King Jr. at the request of his estate, following similar pressures. Zelda Williams also requested the public refrain from sending her AI-generated clips of her late father, Robin Williams.

Policy Changes

Following tensions post-launch, CEO Sam Altman revised Sora’s policy to give rights holders greater control of their likenesses.

The app now allows individuals to opt-out, reflecting OpenAI’s commitment to respond quickly to concerns from performers.

OpenAI backs the NO FAKES Act, supporting legislation that aims to protect individuals from unauthorized AI-generated representations.

OpenAI is focused on ensuring performers’ rights are respected regarding the misuse of their voices and likenesses. Altman reiterated the company’s dedication to these protections.


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Major apps down as AWS experiences global outage

AWS outage disrupts Fortnite, Snapchat and multiple services globally

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AWS outage disrupts Fortnite, Snapchat and multiple services globally

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In Short:
– AWS outage on Monday disrupted major apps like Fortnite, Snapchat, and affected several global companies.
– UK companies including Lloyds Bank and Vodafone reported issues due to the AWS outage.

Amazon’s AWS experienced a significant outage on Monday, impacting major apps including Fortnite and Snapchat. The disruption affected connectivity for numerous companies globally.AWS reported increased error rates and latencies across multiple services and is attempting to recover quickly.

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The outage marks the first significant internet disruption since a previous incident last year that impacted essential technology systems globally. AWS offers on-demand computing and storage services and is vital for many websites and platforms.

Multiple companies reported disruptions, including AI startup Perplexity, cryptocurrency exchange Coinbase, and trading app Robinhood. Perplexity’s CEO confirmed on X that the outages were linked to AWS issues.

Amazon’s shopping site, Prime Video, and Alexa services also faced difficulties, according to Downdetector. Other affected platforms included popular gaming applications like Clash Royale and financial services such as Venmo and Chime.

Uber competitor Lyft’s app was reported down for numerous users in the U.S. Messaging platform Signal also acknowledged connection problems stemming from the AWS outage.

British Companies

In the UK, Lloyds Bank, Bank of Scotland, and telecom services provider Vodafone were notably affected. The HMRC’s website also encountered issues during this outage.

Elon Musk stated that his platform, X, remained operational despite the widespread disruptions.


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