In the car rental industry, camera tunnels and inspection apps similarly compare images to damage databases (mistaking dirt or previous marks on vehicles as new also results in billing customers months after rentals). Smoke, Vape and Noise Sensors at Hotels/Rentals — have fees that are generated by machine learning models due to "misfires" (steam/aerosols/street noise). Airlines have a pricing algorithm based on some dynamic system that uses seat maps, demand, and, not to mention, session data to adjust fares, and it may create an illusion of "personalized penalties" with no or minimal transparency. They cause consent to be buried in the fine print, reverse the burden onto the traveler on monetary charges, and malfunction in real environments. The proposed solutions are pre-scan consent with the evidence, human review before charges, audit, publicized disputes, and disclosure of pricing factors. Real examples, policy excerpts, and a traveler checklist to avoid surprise fees.
AI systems work by finding patterns in data. You typically need thousands, sometimes millions, of data points to build a system that performs well. The challenge here is that if the data used to train these systems is biased or incomplete, the AI's predictions can be unfair. A good example of this is a facial recognition system that misidentifies people with darker skin tones because they were underrepresented in the training data. Another example is an AI that uses something like ZIP codes to predict interest rates, not realizing that ZIP codes can serve as a proxy for race due to historical housing segregation, leading to discriminatory outcomes. These problems usually aren't intentional. AI is really good at finding subtle connections between data points, connections humans wouldn't even think about. Those can produce unintended consequences. That's why regular AI audits for bias and fairness are so important. If I can give one tip to travelers, it would be to push for transparency. Ask how a price or fee was determined and whether AI was involved. In an ideal world, companies would provide a clear explanation of how their AI systems arrive at decisions. The reality is that some of the most advanced AI models are "black boxes," which means that even the developers can't fully explain every decision. Regardless, most reputable companies often build in tools to aid explainability and can at least walk you through their decision process. If a company can't or won't provide a reasonable explanation, that can be a red flag.
This is a real story, not a chatgpt, I can provide proof!! In May 2025, I rented a brand-new Audi A6 from Sixt in Germany to finally tick off a childhood dream: driving a fast car on the limitless DE autobahns. That dream nearly killed me. In the middle of the night, on May 24-25, all electronics failed — brakes, airbags, everything (all electronics assistants). I had my wife with me, who suffers from multiple sclerosis. We were stranded for 3 hours in total darkness on a high-speed autobahn, terrified and without help. I lost a prepaid hotel night, paid extra for transport to Berlin, and missed the next day's plans. When I filed a claim, Sixt's AI-driven claims system approved exactly €97.03 — just enough for hotel and transport costs — and rejected my request for moral damages or premium replacement rental. There was no human review, no acknowledgment of the life-threatening aspect, no consideration for my wife's health.
AI in travel can bring surprise charges like damage fees or inflated fares. Always document everything and compare prices before booking.
As someone who splits time between Florida and California and serves as both COO and Senior Attorney at a major law firm, I've seen firsthand how AI is creeping into the travel space. I've also seen how often it gets things wrong. I've experienced the automated vehicle scanners looking for dust smudges or hairline scratches as damage, with no human inspection involved. In my legal work, I see similar problems when insurance companies use AI to review claims and end up missing important details like nuanced medical notes or itemized billing. These systems are fast, but they're not accurate enough to replace trained professionals who can critically think. I expect we'll start to see legal precedents requiring companies to disclose when AI is behind a billing decision and to give consumers a clear path to human review. Until then, travelers need to protect themselves. Take photos, save records, and don't be afraid to ask: was this decision made by a person, or a machine? It sounds like science fiction, but this is where we are now."