Same time, same route — can two people really be charged different fares?
There's evidence it happens — "surveillance pricing," where fares are set based on personal data estimating how much you individually will pay, drew consumer-advocacy scrutiny in 2025-2026.
What to do now
- There's evidence it happens — "surveillance pricing," where fares are set based on personal data estimating how much you individually will pay, drew consumer-advocacy scrutiny in 2025-2026.
Who owns the resolution
Dynamic / Surge Pricing (Uber & KakaoT)'s own support/policy team decides this -- AMS explains the policy but has no account access and cannot make this decision for you.
Evidence to prepare
- Your account email or user ID
- Screenshots or a confirmation number for the specific order/booking/transaction
- Any messages you already exchanged with support about this
Turn this answer into a question about your case
Give another AI the facts it needs—not just “what should I do?”
I need practical help with a Dynamic / Surge Pricing (Uber & KakaoT) issue. The policy question: Same time, same route — can two people really be charged different fares? Useful context I found: There's evidence it happens — "surveillance pricing," where fares are set based on personal data estimating how much you individually will pay, drew consumer-advocacy scrutiny in 2025-2026. My specific situation: [Describe what happened, including dates and messages shown] The outcome I want: [Refund, verification, appeal, account recovery, explanation, etc.] Important constraints: [Country, deadline, booking/account status, documents already submitted, budget, or other limits] Please: 1. Identify any missing facts you need before reaching a conclusion. 2. Separate platform policy, local law, and your own inference. 3. Give me the safest next steps in priority order. 4. Use current official sources where possible and flag anything that may have changed. 5. Draft a concise message I can paste to customer support. 6. Do not invent account access, guarantees, refund rights, or legal conclusions.
Why this policy exists
Classic surge pricing responds to a supply signal ("this zone is short on cars"). What drew separate controversy was pricing based on individual data — location history, past search/purchase patterns, device signals — used to estimate a person's ability/willingness to pay, charging different people different fares for the same trip. US consumer groups including Consumer Reports documented the scale of this "AI-driven surveillance pricing" through 2025-2026, and the backlash has pushed regulators to consider frameworks that preserve pricing efficiency while banning the use of data that specifically targets individual vulnerability. One frequently repeated claim — that a low phone battery triggers higher fares — has no confirmed research or company admission behind it; treat it as an unverified inference riding on the "surge exploits urgency" narrative, not an established fact.
Need to act on your account?
AMS explains the rule but cannot access your account, issue a refund or change a platform decision.