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At first glance, US real estate company Opendoor offers pretty good deals. People who want to sell their homes can upload their address, basic information and some photos to the site. It searches for information, cross-references market data and makes quotes. If the offer is accepted, the seller will expedite the transaction, eliminating the need for chains and brokers. After the sale, Opendoor will do some renovations on the home and resell it for a profit: a quick “flip” that disrupts the typically slow real estate system.
The reality is not that simple. Buyers and sellers alike have harsh complaints about Opendoor: “After living in it for a year, the shower walls are all caved in and there’s rotten wood behind the tiles,” complained one typical online review. “They used the cheapest contractor.” Another reported that the quote was low to begin with. It’s an age-old story: A company buys below market value, renovates it and sells it at a markup. But the difference is that Opendoor is powered by “deep learning” algorithms that can do the job faster and more ruthlessly.
According to reports, “iBuyers” such as Opendoor have sold nearly 2 million U.S. homes since 2016, which shows how deeply artificial intelligence tools have penetrated the real estate field. The site is unusual in that it’s geared toward consumers, rather than businesses, and is particularly ambitious in that it attempts to appraise, buy, and flip homes in one go. Opendoor has struggled to become consistently profitable. But this is typical of current real estate AI: a tool that enhances the perception of buildings as assets to be traded and gambled.
Most commonly, real estate AI is used for investment analysis. Companies such as Reonomy, Skyline AI and Cherre offer powerful investor profile processing tools. Compass is an example of “lead generation” or “real estate farming” AI software that helps real estate agents find people whose online activity indicates they are looking for homes. US-based Deepblocks identifies development opportunities based on immigration, market and planning information. All the data is mined to maximize the potential profit from homes and buildings.
There is also an emerging world of artificial intelligence in real estate that is replacing human interactions.McKinsey said: “Simple requests from tenants, such as routine maintenance, can motivate them to [AI] First officer contacts building maintenance personnel directly […] For high-stakes moments—such as commercial lease negotiations with office, warehouse, or retail tenants—gen AI tools can […] Prepare a transcript of the negotiation. Artificial intelligence has the potential to disrupt bureaucracy in this regard.
But there are also huge risks to digital inclusion and surveillance, and how artificial intelligence will address the racial and socioeconomic inequalities entrenched in the housing system. While some are optimistic about its ability to eliminate discrimination, research has found evidence of AI amplifying inequalities in mortgage approvals.
Other software, often called automated valuation models (AVMs), are specifically designed to calculate the cost of a home. These range from processing local price index and sales data to comprehensive image scanning. For example, Homer from Southeast Asian tech startup Oh My Home visually assesses images of homes to check for structural damage as well as “cluttered, untidy rooms and outdated interiors.” AVM’s attempt to reduce a home to a single data point will make the messy balance of factors that make a space livable and likeable weigh into a single estimate.
“Imagine a dystopian future where everyone repaints their houses a specific color to impress the Google Street View car”
This is perhaps where artificial intelligence poses the most direct threat to the architect’s art. MIT researchers warn, “Imagine a dystopian future where everyone repaints their house a specific color to game the system and impress the Google Street View car.”
While none of the above approaches address the most pressing issues in housing, such as environmental impact, affordability, or homelessness, there is the potential for more inspiring approaches. The Turing Institute believes AI can help planners master the technical details of planning applications and spend more time considering political factors, while some AI tools can help increase community engagement. JustFix, a non-profit organization, builds digital tools to help tenants exercise their rights. The emergence of predictive maintenance tools, material passports, and open source BIM from engineering firms can help us democratize knowledge about cities and infrastructure.
Flashy new AI design tools and chatbots threaten to distract us from the speed and depth with which AI is penetrating the built environment. Investors are discovering a world ripe for disruption in a bureaucracy-ridden world where data is abundant and financial speculation has become the norm. Only a handful of tools are seeking to rebuild our ailing homes and buildings; most reduce homes to data points that can be traded at the click of a button. Major changes in the real estate system are already coming.
Martha Dillon is a writer on climate justice, housing, and the built environment
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