Airbnb Goes To Battle Against Party Incidents: The AI Solution

The nightmare of returning to your rented home after a short-term stay to find it transformed into a loud party venue is a scenario that stirs a potent blend of anger and frustration. Such occurrences surged globally during the COVID-19 pandemic when bars and nightclubs shuttered, leaving young adults in search of alternative party spots. Airbnb (NASDAQ: ABNB), a major player in the short-term rental market, initiated a “global party ban” in response. This involved banning offenders and imposing restrictions on under-25s without excellent reviews. As a result, reported parties decreased by 55% between 2020 and last year.

To further reinforce their stance, Airbnb introduced an AI-powered software system. This system, now active worldwide, scrutinizes factors like account creation date, proximity to the host’s location, stay duration (one-night stays raise red flags), and festive periods like Halloween and New Year’s Eve. Naba Banerjee, head of safety and trust at Airbnb, emphasizes the system’s role in preventing party bookings and guiding users to partner hotels when the risk is high.

Hosts, like Lucy Paterson, find this use of AI reassuring. As Banerjee points out, the AI will continue to improve as it processes more data. Turo, a prominent car-sharing marketplace, also employs AI for safety and convenience. Its DataRobot AI detects theft risks, determines car rental prices, and recommends vehicles based on user preferences.

Edward McFowland III, an assistant professor at Harvard Business School, acknowledges the advantages of AI in weeding out problematic customers. However, he cautions that AI models can still generate false negatives.

Hosts like Lara Bozabalian in Toronto have their own vetting strategies to complement AI’s efforts. Nevertheless, in the evolving landscape of short-term rentals and sharing economy platforms, AI serves as a valuable ally, improving the trust and security of both hosts and guests.

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Photo by Tobias Tullius on Unsplash