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When AI can fake reality, who can you trust? - Sam Gregory

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We're fast approaching a world where widespread, hyper-realistic deepfakes lead us to dismiss reality, says technologist and human rights advocate Sam Gregory. What happens to democracy when we can't trust what we see? Learn three key steps to protecting our ability to distinguish human from synthetic — and why fortifying our perception of truth is crucial to our AI-infused future.

Additional Resources for you to Explore

Learn more via WITNESS's site on generative AI, deepfakes and human rights.

Explore how the human rights community and its allies are working to fortify truth and ensure resilient witnessing practices.

While some research groups report tools that have demonstrated 96 percent and 99 percent accuracy, results for working "in the wild" with with real-world-quality data, unknown methods of synthesis or when a range of AI-based and non-AI-based methods was used in production, are unlikely to ever reach this this level of reliability. You can read more about some of these challenges here.

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Deepfake experts noted that AI can be used as a cover by politicians when embarrassing audio and video clips of them emerge. For example, in 2023, a controversy rocked India when a politician from India’s Hindu nationalist party released two audio clips of an opposition leader, who immediately and vehemently denied them, saying the clips were fabricated. Rest of World asked three independent deepfake experts to analyze the authenticity of the two clips.

Every day, a sea of decisions stretches before us, and it’s impossible to make a perfect choice every time. But there are many ways to improve our chances — and one particularly effective technique is critical thinking. Samantha Agoos describes a 5-step process that may help you with any number of problems.

Today, artificial intelligence helps doctors diagnose patients, pilots fly commercial aircraft, and city planners predict traffic. These AIs are often self-taught, working off a simple set of instructions to create a unique array of rules and strategies. So how exactly does a machine learn? Briana Brownell digs into the three basic ways machines investigate, negotiate, and communicate.

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