Leak Reveals Names of Peter Thiel’s Secret ‘Dialog’ Group

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Key Takeaways

  • Dialog’s members share a common focus on artificial intelligence, longevity, and the near‑future, repeatedly predicting that AI will reshape work, war, education, and belief systems within a few years.
  • The group’s interests are eclectic, ranging from “funhouse construction” and accent imitation to meditative psychedelic inquiry, and their reading list blends stoic philosophy, decision‑making guides, and tech‑optimist manifestos.
  • Dialog operates a matchmaking service (dating.dialog.org) that asks participants if they are “looking for love” and categorizes them as Single Man, Single Woman, or Other for future introductions.
  • Sensitive data collected on the sign‑up form—including political leaning and matchmaking preferences—were inadvertently exposed in a leak, revealing personal details of high‑profile members.
  • The leaked registration list names senior figures from finance, government, NGOs, academia, and tech, such as former Fed governor Randy Kroszner, DEA official Hallie Hoffman, ADL chief Jonathan Greenblatt, Cato Institute head Peter Goettler, Charles Koch Foundation director Ryan Stowers, Nobel economist Roger Myerson, and several Google/DeepMind executives.
  • Internal moderator guidelines emphasize keeping discussions “off the record,” concise, and nonobvious, while coaching facilitators to avoid status signaling among a room of senators, dignitaries, and tycoons.

Dialog, an invitation‑only network that describes itself as a community of “exceptional people,” is united less by formal titles than by a shared fascination with how artificial intelligence, longevity science, and emerging technologies will reshape society in the coming years. When asked on the registration form to predict the future, respondents repeatedly returned to the idea that AI will fundamentally reorder work, war, education, and belief systems within a short horizon. Some foresaw mass labor displacement prompting a resurgence of unions and expanded government programs; others warned of an “AI winter,” domestic terrorism aimed at data centers, criminal defendants opting for AI‑driven legal representation over public defenders, or a religious revival sparked by technological disruption. One participant bluntly warned that “societal degeneration will continue to accelerate.”

Beyond their prognostications, members catalogued a wide array of personal talents and interests that reveal the group’s eclectic makeup. Skills listed ranged from the whimsical—“funhouse construction,” accent imitation, backcountry skiing, urban exploration—to the introspective, such as “meditative and psychedelic inquiry into the nature of reality” and the paradoxical pairing of “compassion and existential dread.” More conventional hobbies like “dinner parties, keeping secrets, remembering birthdays” also appeared. Their reading recommendations reflect a blend of classical wisdom and modern optimization: stoic emperor Marcus Aurelius, novelist Milan Kundera, decision‑making specialist Annie Duke’s Thinking in Bets, longevity expert Peter Attia’s Outlive, and, from at least one attendee, venture‑capitalist Peter Thiel’s Zero to One.

Dialog also functions as a de facto matchmaking service. The participant form explicitly asks whether registrants are “looking for love” and offers to include those who answer “Single Man,” “Single Woman,” or “Other” in a future matchmaking pool. A companion site, dating.dialog.org, hosts an app marketed as facilitating “meaningful connections for exceptional people.” This dual purpose—intellectual exchange paired with romantic networking—underscores the organization’s aim to cultivate both ideas and personal bonds among its elite constituency.

The sign‑up form additionally collects sensitive personal data, notably each registrant’s political leaning, which Dialog promises will “NOT be shared in the app or with other participants, ever.” Unfortunately, that assurance was broken when a leak exposed the underlying Airtable database. The compromised records contain not only political affiliations but also matchmaking responses, membership status, retreat attendance biographies, home cities, and private access tokens (which WIRED refrains from publishing). The leak thus revealed a trove of private information about individuals who occupy prominent positions in finance, government, academia, media, and technology.

Among the names exposed are several high‑profile figures absent from Dialog’s public directory of 113 members. These include Randy Kroszner, former Federal Reserve governor now serving on the Bank of England’s Financial Policy Committee; Hallie Hoffman, former DEA general counsel and acting chief of staff; Jonathan Greenblatt, CEO of the Anti‑Defamation League; Peter Goettler, president of the Cato Institute; Ryan Stowers, executive director of the Charles Koch Foundation; and Roger Myerson, Nobel laureate economist at the University of Chicago. The list also features a cluster of Google and Google DeepMind leaders, such as Tom Lue, who heads global affairs for the company’s frontier AI division, and journalist Souad Mekhennet of The Washington Post, noted for running an “Ulysses Book Club” event. The remainder of the membership spans hedge‑fund and private‑equity billionaires, current and former foreign officials, network television actors, best‑selling authors, and religious leaders.

Accompanying the registration data were internal documents left exposed in the same Airtable base. A guide for event moderators instructs them to remind participants that all discussion is “off the record,” to keep comments concise and “nonobvious,” and to model brief introductions that avoid status signaling—crucial tactics in a setting that regularly brings together senators, dignitaries, and titans of industry. Together, these elements paint a picture of Dialog as a tightly knit, ideologically driven network where forecasts about AI’s societal impact, personal eccentricities, elite matchmaking, and discreet deliberations intersect—sometimes with unintended consequences when data safeguards fail.

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