With the rise of artificial intelligence (AI) and other emerging technologies in the multifamily industry, the Real Estate Technology and Transformation Center (RETTC) has released a blueprint for responsible innovation.
The AI Governance Framework, developed by RETTC’s AI Working Group, has been designed to protect consumers and uphold the Fair Housing Act, the Fair Credit Reporting Act, and other state and local housing laws.
“We can’t solve the nation’s housing challenges with yesterday’s tools,” said Kevin Donnelly, executive director and chief advocacy officer at RETTC. “AI and emerging technologies are already transforming how housing providers operate and serve residents, making housing more efficient, more responsive, and ultimately more attainable. Our new AI Governance Framework provides a road map for housing providers and their technology partners in developing, deploying, and using these technologies responsibly. This framework is something policymakers should look to as safely fueling innovation, grounded in consumer protection and critical to scaling sorely needed housing supply to address affordability.”
The framework breaks down eight key principles to help inform dialogue for multifamily housing and technology partners:
- Establish an organizational philosophy on how AI will be used, governed, and monitored across operations;
- Ensure consumer protection and fairness with AI systems;
- Be transparent when AI influences key decisions in the customer journey;
- Adhere to privacy laws with an emphasis on data security and informed consent;
- Engage people in significant decisions related to the customer journey, including establishing processes, training staff, and developing testing and ongoing evaluation of tools;
- Elevate technologies and explore AI tools that improve the resident experience with the potential feedback from residents;
- Encourage the development of AI tools that benefit residents, prospects, staff, and operators to deliver better experiences and more efficient operations; and
- Invite transparency from third parties regarding their data sources, known risks, and model limitations to ensure responsible adoption.