Block's new voice AI sounds eerily human, sparking awe and scam fears
Reactions split between amazement at how human it sounds and fears it could fuel scams and deception, with CZ eyeing uses in children’s education.
Jack Dorsey's payments company Block XYZ$76.45·Market Closed has unveiled a voice AI model that sounds remarkably human in company demonstrations, prompting reactions ranging from amazement at its conversational abilities to warnings that such technology could make phone scams harder to detect.
Called Dessa, the model was trained entirely on human speech rather than text and can listen while speaking, allowing it to handle interruptions, laughter and changes in tone during a conversation, according to the Block’s announcement.
“Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence,” Dorsey wrote on X.
In one demonstration, Dessa laughs in the middle of a sentence; in another, it reacts to a surprise with what sounds like genuine emotion. Block says the conversations were recorded live without anyone directing the model's responses.
Unlike systems that first convert speech into text before generating a spoken response, Dessa processes audio directly. Block said it trained Dessa from scratch using a single Nvidia GB200 NVL72 computing system. The model is compact enough to run locally on a MacBook Pro equipped with an M4 Max chip or better, according to the firm’s statement.
For now, Dessa remains a research preview rather than a publicly available product.
Dessa’s demo quickly drew attention on social media, with some users praising how natural the interactions sounded.
X user Alexander Hoff said he had never “heard anything artificial that sounded so… human,” while user Hesamation described it as “straight up sci-fi stuff.
Binance founder Changpeng “CZ” Zhao also chimed in, pointing to potential uses in education, where natural voice interactions could help children learn through conversation.
“This might be very good for GiggleAcademy. Teaching kids in current ‘AI voice’ was a challenge,” Zhao wrote, referring to his education project.
But the same humanlike qualities that impressed some listeners raised concerns among others about the technology's potential for deception.
Filmmaker Justine Bateman questioned why AI voices need to sound human, arguing that it could be used to mislead people. “So you can trick people into lowering their guard,” she wrote.
Journalist Shiv Aroor raised similar concerns about fraud, writing, “Scam calls about to attain pandemic level.”
Dessa comes from Block, which operates Square, Cash App, bitcoin wallet Bitkey and bitcoin mining hardware unit Proto. Its AI research lab reports directly to Dorsey and includes former staff from Toronto-based AI startup Dessa, which Square acquired in 2020.
Block has not disclosed the model’s size, benchmark results or a public release date. Its audio samples remain company demonstrations rather than independent tests.
The company is offering early access to a small group of AI safety researchers. Block says speech-based AI could eventually become better at recognizing emotional cues, such as distress and pain, that text transcripts can miss, while researchers assess risks the company may have overlooked.
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Asanat Analysis — Why it matters
Block's voice AI advancement reflects the broader convergence of consumer tech and crypto infrastructure—a trend where Square/Cash App parent company leverages AI to enhance payment flows and user experience. Voice authentication and AI-driven customer service are increasingly table stakes for fintech platforms competing for retail adoption, particularly in emerging markets where voice interfaces bypass literacy barriers.
The dual narrative—awe vs. scam risk—mirrors historical tech adoption cycles. Deepfake audio poses genuine fraud vectors for custody systems, payment authorization, and identity verification; this is especially material for decentralized finance where social recovery mechanisms and voice-based account recovery could be weaponized. CZ's education angle signals institutional entities see legitimate utility, but regulators will likely demand provenance tracking and detection tools before widespread deployment in financial contexts.
For crypto specifically, this matters because voice AI quality directly impacts attack surface for exchanges, self-custody wallets, and DeFi protocols using voice authentication. The technology is advancing faster than detection/prevention tooling, creating a temporal gap where fraudsters exploit novelty before defenses mature—similar to early phishing against crypto users.