With the Fourth of July weekend comes fireworks, hot dogs, parades and parties. <\/p>\n
For Airbnb, the short term rental platform, these parties are not exactly a fun time: They are a scourge of noise complaints, injury risks and property damage. <\/p>\n
To counter these disruptions and help enforce the platform\u2019s year-round ban on open-invite parties<\/a>, Airbnb five years ago began using machine-learning technology to weed out what the company describes as \u201chigher-risk\u201d bookings. The technology will likely be working overtime during the country\u2019s 250th birthday celebration this weekend.<\/p>\n The technology, the company says, uses \u201chundreds of signals\u201d \u2014 such as whether a user is making the reservation locally or for a short one- or two-day stint \u2014 to flag whether a booking is characteristic of the kind of reservations that result in a rental turning into a party house.<\/p>\n Guests who are, as a result, prevented from booking an entire home, are instead redirected to book private room listings and hotels on the Airbnb platform.<\/p>\n Last Fourth of July, the company\u2019s system deterred more than 20,000 people in the U.S. from booking an entire home listing on Airbnb, according to company spokesperson Ruthie Kongo. <\/p>\n Around 2,500 people in California were redirected, and in Los Angeles, specifically, some 200 people were deterred, she said.<\/p>\n \u201cThese efforts reflect our ongoing commitment to help reduce the risk of disruptive parties, and we are seeing positive results,\u201d Airbnb said in a statement on its website<\/a>. <\/p>\n In 2025, fewer than 0.06% of stays on Airbnb in the U.S. resulted in a report of a party, the company said. Company filings<\/a> say Airbnb recorded 533 million nights and seats booked in 2025, but did not break out property reservation numbers for the U.S.<\/p>\n Param Vir Singh, a professor of business technologies and marketing at Carnegie Mellon University, sees the anti-party system as a useful tool to screen bookings at scale, given that the company \u201ccan\u2019t have a person sitting and evaluating every booking to see if it will lead to a party.\u201d <\/p>\n But Singh said that any machine-learning tool using vast amounts of consumer data to make decisions may have blind spots or false positives. A case in point is Singh\u2019s study of<\/a> racial disparities in the way hosts use the company\u2019s free algorithm-based smart-pricing tool to set their properties\u2019 daily price automatically. <\/p>\n Airbnb executives say they hope to make deeper inroads with such tech and have various ventures in the works.<\/p>\n During an earnings call in May, Chief Executive Brian Chesky said<\/a> AI now writes nearly 60% of new code, produced by the company\u2019s engineers. <\/p>\n \u201cAI gives huge leverage,\u201d he said on the call.<\/p>\n