Real estate professionals now trust algorithms to price the largest purchase most people will ever make. This has gone exactly as well as you'd think.
The data aggregation capabilities sound impressive until you remember these are the same AI models that can't tell the difference between a three-bedroom ranch and a meth lab with optimistic staging. But sure, let some Python script written by a 24-year-old who rents in San Francisco decide what your house is worth.
The shortcomings mentioned in the article are doing heavy lifting. That's like saying the Titanic had shortcomings with iceberg detection. These models scrape Zillow, parse tax records, and spit out a number that enhances expertise the way a drunk friend enhances your parallel parking.
Here's what actually happens. The AI sees your neighbor sold for $500K. It notices you both have two bathrooms. It cannot see that your neighbor renovated while you've been heating the place with a space heater and prayers since 2019. So it averages some comparables, applies a confidence interval it doesn't understand, and tells your agent you're sitting on a goldmine.
You list at $485K because the AI said so. You get one lowball offer from an investor who also used AI and thinks he's getting a deal. You both lose to the cash buyer who just looked at the f*cking house.
The real estate professionals love this because they can blame the algorithm when your house sits on the market for six months. They enhanced their expertise right into plausible deniability.
Nobody's asking why we need AI to do what a comp sheet and basic pattern recognition accomplished for decades. We just decided computers should handle it because computers handle everything now, including making sure you overpay for a starter home in a school district you can't afford anyway.
Photo by Jakub Żerdzicki on Unsplash
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