AI image fraud will cost $40 billion next year - can

What happened

International standards bodies are stepping up efforts to help provide the tools that end users and companies need to distinguish real images, videos, and other content from deepfakes and AI-generated slop. New standards were recently announced at the AI for Good conference hosted in Geneva under the auspices of the UN.

" Accordingly, JPEG Trust "is not a standard that tells you whether to trust or not trust a video and image," he explained. " Context is another factor to weigh, and it is also contingent on the user. "Trust is very context-dependent," he said. "Some people might trust something because of their profile, because of their context.

" Until now, efforts to identify and combat deepfakes and AI scams have been scattered, with companies promoting their own approaches within their ecosystems and others joining forces to set de facto industry standards, said Ebrahimi. " The IEC and ISO recognize that commonly accepted industry standards are needed.

Why it matters

A credibility crisis has arisen, and it's only getting worse when it comes to imagery, reaching the point where one can no longer distinguish between actual photos and AI-generated fakes. This has implications across society and businesses, raising doubts about the authenticity of images used in news reports, social media postings, and even photographic evidence in crime scenes.

3 billion in 2023, according to estimates from Deloitte's Center for Financial Services. With the flood of imagery now appearing on our mobile phones and personal computers, it's difficult, if not impossible, to determine whether photos, videos, or other content are real or AI-generated. "You now don't know what if something is really fake or not," said Touradj Ebrahimi, professor at the Swiss Federal Institute of Technology.

Ebrahimi is leading efforts to address AI fraud and deepfakes, working with leading international standards bodies -- the International Electrotechnical Commission (IEC), the International Organization for Standardization (ISO), and the International Telecommunication Union (ITU) -- to develop and evangelize common standards to help users and companies distinguish erroneous AI-generated material from real content.

" To that end, the IEC and ISO introduced two additions to their JPEG Trust standards to help verify the authenticity of imagery and data. The first JPEG Trust standard, announced last year, is designed to provide a framework for embedding metadata directly into JPEG files in the form of trust indicators.

The two additions to JPEG Trust, now in progress: According to Ebrahimi, the goal of the JPEG Trust standard is to put verification tools in the hands of end users and is not intended to validate or label imagery or data at the front end when it is created. "Fraudsters will not label their content as AI," he said.

What to watch

Efforts to guard against fraud in multimedia began in earnest in 2018, when the JPEG committee of IEC and ISO first addressed a growing concern about inauthentic content. "They recognized there is a flaw in that JPEG files were being used to spread fake imagery," said Ebrahimi. Now, with AI-generated imagery rampant, the challenge is to extend standards to help users and companies verify the authenticity of images they receive.

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