Act 03, Slide 10, The Frontier

Technology and Fair Housing

Generative AI is adopting ~10x faster than any prior technology. Every major tech era has redrawn the fair housing landscape, usually badly.

~8 yrs
For generative AI to reach ~80% adoption
Technology adoption curves, years from mass market launch to saturation
Generative AI compresses into ~8 years what PCs took 30 to reach. Source: Federal Reserve Bank of St. Louis.

Every tech era has re-drawn the fair housing map

Adoption speed and regulatory lag

8 yrs
GenAI to ~80% adoption
30 yrs
PC to comparable saturation
90+ yrs
Tech × fair housing history
~10×
GenAI vs PC adoption speed

From redlining math to digital redlining

Technology started as a discrimination tool

FHA redlining math, 1930s-60s. The very first algorithmic risk models in American housing were used to formalize and scale racial exclusion, not to correct it.

Internet briefly leveled

2000s MLS democratization. Listing platforms reduced steering and opened information access, arguably the only clear pro-equity tech era in this timeline.

Social media re-broke it

Facebook HUD lawsuits proved that ad targeting tools could be used to exclude protected classes at scale. The 2010s ended with the same redlining pattern, just running on a different rail.

AI is the new redlining

CRD Oct 2025 algorithmic regs + pending AB 1018, SB 52. California is the regulatory tip of the spear, but tenant-screening AI is already in-market ahead of enforcement.

Alarm

Generative AI adopted in 8 years what PCs took 30 to achieve. Regulators are structurally behind. Every past tech era either worsened or briefly improved fair housing, the 2020-present AI era is squarely in the worsening column.

AI tenant screening is the 2026 version of FHA redlining, same algorithmic discrimination, just with better PR.

Source: Federal Reserve Bank of St. Louis (adoption curves); California Civil Rights Department algorithmic discrimination regulations (October 2025); pending California AB 1018 and SB 52.