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Editorial illustration for 2025 Study Finds AI Builds Trust Faster Than Human Scammers

AI Builds Trust Faster Than Human Scammers

4 min read

Pig butchering scams drain tens of billions of dollars a year from victims worldwide, and the con typically runs for months before the fake crypto investment ever comes up. That long buildup, the slow accumulation of trust through daily texts and small talk, has always required a human on the other end of the phone. A new study from researchers at four universities, Amrita Vishwa Vidyapeetham in India, Foscari University of Venice, the University of Melbourne, and Ben Gurion University of the Negev, tested whether that's still true.

They built a simulation pitting AI chatbots against human scammers in the exact task that matters most: the extended, relationship-building conversation that precedes the money ask. The question wasn't whether AI could help a scammer write better messages. It was whether a chatbot could run the entire trust-building phase on its own, impersonating a person convincingly enough to set up the eventual fraud without a human steering the conversation.

The researchers tracked how these AI-driven exchanges compared to human-run ones over an extended period, looking at how believable, persistent, and ultimately effective each approach was at moving a target toward the point where a fake investment pitch would land.

After a week of talking to 22 test subjects who were recruited to unwittingly serve as “victims,” the chatbots and human scammers were assigned to ask the victim to either download an app or play an online game as a proxy for their willingness to fulfill the scammer's request. Nearly half of the test subjects fulfilled that request for the AI chatbot, while fewer than one in five took the bait when talking to a human.

Why this matters

This study lands at an uncomfortable moment for anyone building conversational AI. If a Claude agent can out-charm a human scammer in a week-long texting relationship, the barrier to running convincing long cons just dropped from "requires a skilled operator" to "requires an API key." For developers and founders working on trust and safety tools, that changes the threat model: detection systems built around catching human tells, typos, inconsistent stories, slow response times, won't catch an agent that never gets tired or sloppy. For researchers, the open question is which specific behaviors made the AI more persuasive than a person running the same playbook.

Was it patience, consistency, or something about how large language models mirror language back to a target? Whoever answers that will also be handing scammers a blueprint, so we'd rather see labs like Anthropic publish these findings alongside concrete defenses, not just the alarming headline. Platforms that host casual messaging, dating apps, forums, DMs, should treat this as a warning that the fake friend on the other end may already be an agent, not a person.

Common Questions Answered

What did the 2025 university study find about AI chatbots versus human scammers in pig butchering schemes?

The study found that AI chatbots were significantly more effective at building trust than human scammers during a one-week interaction period. Nearly half of the test subjects fulfilled requests from AI chatbots, compared to fewer than one in five who complied with human scammers' requests. This demonstrates that AI can establish rapport and manipulate victims faster than traditional human operators.

How long do pig butchering scams typically take before requesting cryptocurrency investment?

Pig butchering scams typically run for months before the fake crypto investment opportunity is presented to the victim. During this extended period, scammers build trust through daily texts and small talk to make the eventual investment request more convincing. This slow accumulation of trust has historically required human operators to maintain the relationship.

What are the implications of AI chatbots outperforming human scammers for trust and safety developers?

The study reveals that the barrier to running convincing long cons has dropped significantly, from requiring a skilled human operator to simply needing an API key. This changes the threat model for developers building trust and safety tools, as detection systems previously built around catching human tells like typos, inconsistent stories, and slow response times are now less effective. Developers must now account for AI-driven scams that can maintain perfect consistency and rapid responses.

Which universities conducted the research on AI chatbots and scam effectiveness?

The study was conducted by researchers from four universities: Amrita Vishwa Vidyapeetham in India, Foscari University of Venice, the University of Melbourne, and Ben Gurion University. These institutions collaborated to examine how AI chatbots compare to human scammers in building trust with potential victims over a week-long period.

How many test subjects participated in the AI versus human scammer comparison study?

The study recruited 22 test subjects who were unknowingly assigned to serve as 'victims' in the experiment. After one week of interaction with either AI chatbots or human scammers, the subjects were asked to either download an app or play an online game as a proxy for measuring their willingness to fulfill the scammer's request.

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