“Aviation laws were written in blood. Let’s not reproduce that methodology with ai” — ai/en/community/simeon-campos” rel=”noopener ugc nofollow” target=”_blank”>Simeon Campos
In 2018, the Bloomberg story “tech-algorithms” rel=”noopener ugc nofollow” target=”_blank”>Zillow’s algorithm-driven buying spree doomed its home flipping experiment” was a great headline. It described Zillow’s bold entry into the iBuy world, betting on its ML driven Zestimate Algorithm to revolutionize for-profit housing flipping. Despite a carefully structured start, bringing in local real estate experts to authenticate the algorithm’s price, Zillow shifted to a fully algorithmic approach in finding the fastest deals. This measure, however, did not bear fruit.
Zestimate struggled to adapt to rapid inflation in the 2021 real estate market, prompting Zillow to take steps to improve the attractiveness of its offerings. The company embarked on an ambitious buying spree, reportedly acquiring up to 10,000 homes per quarter. However, the human workforce struggled to keep up with the magnitude and speed of these acquisitions, a challenge exacerbated by the simultaneous outbreak of the pandemic. Facing mounting difficulties, including a backlog of unsold properties, Zillow decided to pause its offerings in October 2021. In the following months, homes were resold at a loss, leading to a significant inventory write-down exceeding $500 million. .
In In addition to the huge monetary loss from its failed company, Zillow announced it would lay off about 2,000 employees, a quarter of the company.
We begin our discussion with a rather unfortunate incident, since the fall of Zillow’s iBuying company is immersed in a complex framework of causes. Although it is impossible to separate this incident from the 2020 global pandemic that disrupted the real estate market…
