I tried to prove I'm not AI. My aunt wasn't convinced

Shared secrets, shibboleths & social defenses

• Many argue families should share offline “codewords” or shibboleths to authenticate unusual calls (e.g., emergencies, ransom scams).
• Others prefer shared private memories instead of new passphrases, doubting people will reliably remember codes.
• Several note scammers create urgency and emotional pressure so victims ignore or can’t recall codewords.
• One concern: once a phrase is used over a network, it can be captured in breaches; the secret degrades over time.
• Some already use shibboleth/duress words with alarm companies or joke about spy‑style countersigns.

Cryptography, cameras & technical fixes

• Strong sentiment that society failed to adopt widespread cryptographic signatures early enough (email, VOIP).
• Proposals: signed emails, signed media, tamper‑proof or authenticated cameras, and provenance chains from capture device to viewer (possibly blockchain‑backed).
• Objections:
  • Device or key compromise and social engineering remain weak points.
  • People may let their own AI agents send signed messages.
  • Editing photos/video breaks simple hash‑based verification and professional workflows rarely use straight‑from‑camera output.
  • Centralized signing by major platforms could further concentrate power.

Trust, scams & economic / social impact

• Multiple anecdotes of hijacked email accounts and AI‑crafted, highly personalized scams.
• Call‑center and “grandparent” scams now potentially enhanced with AI voice and video.
• Some foresee shrinking trust spheres: only in‑person or local, verified relationships are considered reliable.
• Predicted impacts include more in‑person interviews and travel, difficulty trusting online information, and heavier economic and psychological costs.
• Others say misinformation, doctored media, and spam are old problems; AI mainly lowers cost and scales them.

Detection limits & human psychology

• Many feel “spotting AI” visually is already unreliable; context and provenance matter more than artifacts like extra fingers.
• Discussion of phenomena like analysis paralysis, flip‑flopping under doubt, and how manufactured urgency suppresses skepticism.
• Some suggest “reverse captchas” using taboo or disallowed topics to distinguish humans from safety‑constrained corporate models, though this fails for uncensored/local models.

Regulation, watermarking & policy

• Suggestions include legal requirements for AI watermarking and platform‑level labeling of synthetic media.
• Critics argue bad actors will ignore rules, watermarking is technically fragile, and laws may only burden compliant companies.

Cultural, political & philosophical angles

• Worries that deepfakes erode courtroom evidence and public accountability (e.g., plausible deniability for incriminating footage).
• Some see AI as accelerating a “post‑truth” or “spam‑saturated” world; others push for “touching grass” and prioritizing offline community.
• A side debate questions whether human–human interaction is intrinsically more valuable than interaction with convincing AI facsimiles.