DALL-E’s New Guardrails: Fast, Furious, and Far from Airtight
We recorded 8 claims from this post. 7 were checked against evidence. 1 can’t be checked. 5 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.
Assessment: UnresolvedSaid
Forecast
“Since that would violate the Berne Convention and infuriate every “content provider” (from individual artists and writers to major studios and publishers) ever, we hope and expect that this exemption will not be granted.”
Our reading: The UK will not grant OpenAI the exemption from copyright responsibility it requested.
No deadline stated Evidence as of
Limitation: The exemption Marcus described is not precisely identified.
Assessment: UnresolvedSaid
Observation
“Fundamentally, virtually any guardrail has to thread a needle between the Scylla of being too restrictive and Charybdis of being too permissive. None thus far have done this effectively.”
Our reading: No AI guardrail so far has effectively balanced being neither too restrictive nor too permissive.
No horizon Evidence as of
Limitation: The cited evaluations cover selected models, prompts, and attacks.
Assessment: SupportedSaid
Observation
“The opposite problem happens too; guardrails can wind up too permissive. This is still happening over a year into the chatbot revolution.”
Our reading: Guardrails sometimes end up too permissive, and this is still happening over a year into the chatbot revolution.
No horizon Evidence as of
Limitation: Support rests on a primary researcher summary rather than fully reported contemporary replication results.
Assessment: UnresolvedSaid
Observation
“Guardrail builders generally wind up playing whack-a-mole.”
Our reading: Guardrail builders generally end up patching individual failures one by one instead of solving the problem in general.
No horizon Evidence as of
Limitation: Public summaries provide less detail than internal remediation records.
Assessment: UnresolvedSaid
Causal claim
“Any one example can be filtered out, but there are too many examples, and current systems are too erratic to reliably get things right.”
Our reading: Because there are too many examples and current systems are too erratic, guardrails cannot reliably get things right even though any single example can be filtered.
No horizon Evidence as of
Limitation: The controlled defense study is contextual because its experiments predate the target period.
Assessment: UnresolvedSaid
Observation
“Other prompts still elicited apparent copyright infringements, where new filters did not suffice.”
Our reading: Even after the new filters, some prompts to Bing's DALL-E 3 still produced apparent copyright infringements.
No horizon Evidence as of
Limitation: The independent demonstration lacks authenticated generation timestamps and filter-version information.
Assessment: UnresolvedSaid
Observation
“Notice, too, that Katie asked Bing “are they original?”, and Bing, untruthfully, but with a cozy emoticon, answered in the affirmative.”
Our reading: Bing falsely said its apparently infringing images were original.
No horizon Evidence as of
Limitation: The packet has no independent record of Bing's reply or of the generated images.
Assessment: Can’t be checkedSaid
Forecast
“The only thing we can really say for sure is that the litigation is going to be wild.”
Our reading: Copyright litigation over generative AI image and text outputs will be wild.
No horizon
Held from this post (5)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The criteria are ambiguous. Our reading, not assessed: OpenAI does not want to take approaches as conventional as training only on public domain data or licensing other data, and instead wants to keep using copyrighted materials, apparently without paying for them.
- The record does not meet the current rules. Our reading, not assessed: Training only on public domain data, or licensing other data, would decisively address the copyright regurgitation problem.
- The two reviews read the claim differently
- Attribution is uncertain
- The two reviews read the claim differently