Invisible Matchmakers: How Algorithms Pair People with Opportunities

In the digital age, algorithms act as the invisible matchmakers of our lives, influencing everything from job searches and house hunting to finding romantic partners. In a recent episode of the Stanford Graduate School of Business podcast "If/Then: Business, Leadership, Society," Daniela Saban, an associate professor at Stanford, discusses the profound impact of algorithms on matchmaking processes and advocates for building equity into these systems.

The Role of Algorithms in Modern Matchmaking

Algorithms are omnipresent in our daily lives, subtly guiding our decisions and interactions. Saban's research spans operations, economics, and computer science, focusing on "matching markets," where two-sided preferences are crucial. Her studies have delved into diverse applications, including online dating and volunteer matching, showcasing how well-designed algorithms can improve fairness and efficiency.

Enhancing Online Dating Algorithms

Saban's passion for online dating led her to partner with a major U.S. dating platform. She developed a model that prioritised potential matches based not only on user preferences but also on the likelihood of mutual interest. This "two-sided approach" significantly boosted match rates in field experiments, increasing matches by 27% in Houston and byover 37% in Austin. By incorporating user activity levels and recent experiences, the algorithm could better predict and facilitate successful connections.

Equitable Volunteer Matching

In another study, Saban addressed imbalances in volunteer matching on the platform VolunteerMatch. Some organisations were overwhelmed with volunteers, while others struggled to attract any. Saban's team adjusted the search algorithm to consider the number of volunteers needed and already received by each organisation. This change led to a more equitable distribution of volunteers, increasing the number of opportunities that received at least one signup by 8-9% without significantly reducing the overall number of signups.

Building Equity into Algorithms

Saban emphasises that while the technical details of algorithms can be complex, the commitment to fairness is straightforward. By consciously designing algorithms to consider equity, we can create systems that serve a broader range of users more effectively. This approach is particularly relevant for nonprofit organisations that often lack the resources to conduct extensive data analysis.

Conclusion

Daniela Saban's research highlights the transformative potential of algorithms when designed with equity in mind. Whether on dating apps or volunteer matching platforms, these invisible matchmakers can significantly enhance user experiences and outcomes. As Saban and her colleagues have shown, thoughtful algorithm design can lead to more fair and efficient matching processes, ultimately benefiting society as a whole.

For more insights and to explore other episodes of the "If/Then" podcast, visit the Stanford Graduate School of Business website or follow them on social media.