Pundit ClaimsAI claims by Gary Marcus and Ed Zitron, with the evidence

Gary Marcus Marcus on AI Published

AI risk ≠ AGI risk

We recorded 8 claims from this post. 2 were checked against evidence. 6 can’t be checked. 7 more are held. Read the post at its source.

Claims from this post (8)

In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.

  1. Assessment: Can’t be checkedSaid

    “theirs (from what I can tell) seem to center mainly around what happens if computers rapidly and radically self-improve themselves, which I don’t see as an immediate possibility.”

    What we tested: Marcus does not see computers rapidly and radically improving themselves as an immediate possibility.

  2. Assessment: SupportedSaid

    “A company called Adept.AI just raised $350 million dollars to do just that, to allow large language models to access, well, pretty much everything (aiming to “supercharge your capabilities on any software tool or API in the world” with LLMs, despite their clear tendencies towards hallucination and unreliability).”

    What we tested: Adept.AI just raised $350 million to let large language models access pretty much everything, despite LLMs' clear tendencies toward hallucination and unreliability.

    What happened: The release confirms the announced $350 million financing. It also describes the long-term goal of training an AI teammate to use every software tool and API, and says funding would support products, model training, and hiring. (Adept, reproduced at adept.futurefabric.co, )

  3. Assessment: SupportedSaid

    “But here’s the thing: although a lot of the literature equates artificial intelligence risk with the risk of superintelligence or artificial general intelligence, you don’t have to be superintelligent to create serious problems.”

    What we tested: AI does not need to be superintelligent to create serious problems.

    What happened: The investigation describes a fatal collision while Uber's developmental driving system controlled the vehicle; it failed to classify the pedestrian correctly or predict her path, and its design suppressed emergency braking. This supports a material contribution from limited AI, while the report identifies the distracted operator as the probable cause and also identifies organizational and oversight failures. (National Transportation Safety Board, )

  4. Assessment: Can’t be checkedSaid

    “Perhaps coupled with mass AI-generated propaganda, LLM-enhanced terrorism could in turn lead to nuclear war, or to the deliberate spread of pathogens worse than covid-19, etc. Many, many people could die; civilization could be utterly disrupted.”

    What we tested: LLM-enhanced terrorism, perhaps coupled with mass AI-generated propaganda, could lead to nuclear war or to the deliberate spread of pathogens worse than covid-19, and many, many people could die and civilization could be utterly disrupted.

  5. Assessment: Can’t be checkedSaid

    “We need to stop worrying (just) about Skynet and robots taking over the world, and think a lot more about what criminals, including terrorists, might do with LLMs, and what, if anything, we might do to stop them.”

    What we tested: We should think much more about criminal and terrorist misuse of LLMs and how to stop it, not just about Skynet scenarios.

  6. Assessment: Can’t be checkedSaid

    “But we also need to treat LLMs as a dress rehearsal future synthetic intelligence, and ask ourselves hard questions about what on earth we are going to do with future technology, which might well be even more difficult to control.”

    What we tested: We should treat LLMs as a dress rehearsal for future AI, which may be even harder to control.

  7. Assessment: Can’t be checkedSaid

    “It’s not an either/or situation; current technology already poses enormous risks that we are ill-prepared for. With future technology, things could well get worse.”

    What we tested: Current AI already poses enormous risks we are ill-prepared for, and future AI could well make things worse.

  8. Assessment: Can’t be checkedSaid

    “Whether AI is at number one or number 10, we need to get serious about it, now, given the sudden rapid widespread deployment and lack of clarity about use cases and means of mitigation.”

    What we tested: We need to get serious about AI risk now, given rapid widespread deployment and unclear use cases and mitigations.

Held from this post (7)

These records did not pass every check, so nothing about them is published. Held is not a finding.