Thanks for the detailed response - this is exactly the kind of domain expertise I need to hear.
You're right that formal institutional workflows (courts, news organizations, professional photography) already handle chain of custody adequately through raw file retention and existing practices. I'm realizing my value proposition isn't for those contexts where authentication has always been critical and processes exist.
Where I see the gap is informal authentication at scale - the billions of images shared daily on social media, used in online discourse, spreading as potential misinformation. Your workflow (keeping raw files, institutional backing, forensic analysis when needed) works great for professional contexts. But:
How does the average person verify an image they see online?
- They don't have access to forensic analysis
- They don't know who has the "earliest/rawest version"
- Trusted institutions are too slow to counter propaganda at internet speed
- Even if institutions could authenticate on demand, would they scale to billions of images?
Blockchain provides automated, scalable verification: platforms could flag images as "no blockchain record found - likely generated/manipulated" without human intervention. Can't generate false positives (hash either matches or doesn't). This doesn't replace institutional workflows - it augments them for contexts where those workflows don't exist.
On the post-AI point: I actually think this is backwards. If we reach a world where we can't even prove "this camera captured this scene," then we have no ground truth at all. Hardware attestation becomes MORE critical, not less. Your blockchain record also includes geotags, timestamp, camera ID - significantly harder to forge a complete fake than just the image itself. Without some method of proving hardware capture, the only option is to stop using images for truth-verification entirely.
On ubiquity: Every standard starts somewhere. HTTPS, GPS in cameras, seatbelts - none were ubiquitous until they were. Even before universal adoption, blockchain authentication can prove a positive ("this image has verifiable provenance") even if it can't yet prove a negative ("this image was generated"). For law enforcement, that's still valuable.
On watermarking: Watermarks can be trained around - that's what GANs do. If you watermark with something requiring a key to decode, you're already halfway to cryptographic signing, just without blockchain's forgery resistance. They're complementary approaches, not competing ones.
On qualitative vs quantitative: As an engineer, quantitative beats qualitative for anything requiring accuracy at scale. Expert judgment works for individual high-stakes cases but doesn't scale to internet-speed misinformation.
You've helped me clarify that my audience isn't professional photographers with institutional backing - it's everyone else who needs to distinguish real from fake at the speed of social media. That's probably a harder problem to solve, but arguably more important given how information spreads today.
Does that reframing make sense, or am I still missing key limitations?