The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
We recorded 10 claims from this post. 3 were checked against evidence. 7 can’t be checked. 4 more are held. Read the post at its source.
Claims from this post (10)
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.
Assessment: Can’t be checkedSaid
“Anyone who thinks about how AI is used should know about it—especially as we are about to head into an era of ubiquitous yet fallible AI.”
What we tested: Anyone thinking about how AI is used should understand Mackworth's finding that human vigilance breaks down.
Assessment: UnresolvedSaid
“Anyone who thinks about how AI is used should know about it—especially as we are about to head into an era of ubiquitous yet fallible AI.”
What we tested: We are about to enter an era in which AI is ubiquitous but still fallible.
Assessment: Can’t be checkedSaid
“Elon Musk has spent the last several years trying to build cars with partial driver-assistance—which does require humans to stay focused at all times. Mackworth’s Dictum suggests this is not necessarily the best idea.”
What we tested: Mackworth's Dictum suggests that Elon Musk's effort to build cars with partial driver-assistance, which requires humans to stay focused at all times, is not necessarily the best idea.
Assessment: Can’t be checkedSaid
“To me, all this reads as a paper that nobody is willing to stand behind.”
What we tested: The Fridman-led paper claiming Tesla Autopilot drivers maintain vigilance appears to be one nobody is willing to stand behind.
Assessment: SupportedSaid
“Fact is, “Mack” Mackworth was right: humans can’t pay attention 100% of the time.”
What we tested: Mackworth was right that humans can't pay attention 100% of the time.
What happened: The reported experiment demonstrates a vigilance decrement during sustained monitoring. The same abstract reports that intermittent task switches prevented the decrement, limiting any claim that decline is unavoidable under every task design. (Cognition / Elsevier; author abstract indexed by PubMed, )
Assessment: MixedSaid
“Automation is a double-edged sword, and there is a kind of uncanny valley. We know perfectly well not to trust lousy systems; and wouldn’t need to pay attention to truly reliable systems, but the closer they get to perfect, the easier it is for mere mortals to space out.”
What we tested: As automated systems approach but do not reach perfection, humans overseeing them become more likely to stop paying attention.
What held: The experiment compared 50% and 90% reliability during simulated cockpit multitasking and found poorer monitoring with greater reliability. The availability date conservatively uses the university record's stated repository date. (Human Factors and Ergonomics Society; record hosted by University of Central Florida, )
What did not: Sixteen participants supervised an autopilot under two reliability conditions lasting 45 minutes each. Reliability changed trust and perceived demand, but the study did not find the predicted increase in task-unrelated mind wandering, limiting the broad causal claim. (Frontiers in Human Neuroscience, )
Assessment: Can’t be checkedSaid
“Few people are likely ever to pay enough attention.”
What we tested: Few people are likely ever to pay enough attention to catch errors in AI-generated output.
Assessment: Can’t be checkedSaid
“The stakes may get even higher if people start to rely on immature AI—which is all we have got, so far—for legal or medical advice.”
What we tested: If people start relying on current immature AI for legal or medical advice, the stakes of over-trust may become even higher.
Assessment: Can’t be checkedSaid
“The stakes may get even higher if people start to rely on immature AI—which is all we have got, so far—for legal or medical advice.”
What we tested: All AI available so far is immature.
Assessment: Can’t be checkedSaid
“We all need to be on our guard.”
What we tested: Everyone needs to be on guard against over-trusting fallible AI output.
Held from this post (4)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews reached different assessments. Our reading, not assessed: CNET published AI-generated articles, 41 of 77 of which contained errors that inattentive editors missed.
- The criteria are ambiguous. Our reading, not assessed: Because CNET's AI-generated articles looked superficially good, editors trusted them and false information got published.
- The two reviews reached different assessments. Our reading, not assessed: In 2023, false information in AI-generated articles slipping past over-trusting editors will happen much more often.
- The two reviews reached different assessments. Our reading, not assessed: Large language model systems inherently cannot keep track of the truth, yet too many people are starting to rely on them.