Building Equity and Upward Mobility by Making Sure the Technologies That Impact Our Lives Are Fair
The Tech Equity Initiative is a multi-faceted effort designed to eliminate bias in algorithmic-based systems used in housing and financial services, increase transparency and explainability for AI tools, outline ethical standards for responsible tech, advance effective policies for regulating AI tools, and increase diversity and inclusion in the tech field. The goal is to have our “gold standard” of algorithmic fairness adopted by regulators, developers, and consumers of AI-based systems.
Many of the technologies used in housing and financial services are not fair for women and people of color yet they impact every area of our lives. From determinations about whether people can get loans or how much they will pay for them to whether a sick patient can get the healthcare they need, algorithms drive important decisions. A mathematical formula can dictate whether a new college graduate can get a job, a single mom can rent an apartment, or whether a family can get insurance for their new home. Algorithms can be life-altering. That’s why it is so important they are fair and do not infuse bias into the process.
Many factors contribute to unfair and disparate outcomes in tech including structural barriers like residential segregation, the racial wealth gap, and the dual credit market. Adopting solutions that have less or no discriminatory impacts on consumers can help advance equitable opportunities for everyone.
Click the button below to learn more about structural barriers that drive unfair outcomes in tech.
This Initiative Focuses on Five Main Goals:
- Developing solutions for removing bias from the technologies that shape our lives
- Increasing transparency and explainability for AI tools
- Advancing research to help reduce bias in tech
- Developing policies that promote more effective oversight for AI tools
- Supporting efforts to increase diversity, equity, and inclusion in the tech field
How We’ll Do It
In Phase 1, we applied several different AI fairness methodologies to assess whether less expensive home loan pricing could safely, profitably, and more equitably be offered to people of color, women, and other historically underserved groups. Our research concluded that certain AI fairness techniques could yield better pricing for consumers and increased profitability for lenders when applied to mortgage loan underwriting and risk-based pricing algorithms commonly in use today.
In Phase 2, we will build an open-source technology platform designed to showcase various AI fairness methodologies and to let industry stakeholders experiment with tools to debias their algorithmic models. We will also collaborate with civil rights, technology, housing, financial services, regulatory, public policy, research, and academic organizations to conduct research, develop and implement fairer policies, educate key communities, and diversify the AI field to advance tech equity.
NFHA’S Voice on AI and Tech Bias
MIT Technology Review
Join Our Team
If you are interested in being a part of a dynamic team working to eliminate bias and increase transparency, explainability, and responsible policies in the tech space, check out our career opportunities.