Invisible Matchmakers: How Algorithms Pair People with Opportunities, with Daniela Saban

Challenges in Volunteer Matching

• Building a system to absorb volunteers requires infrastructure and supervision to ensure a positive experience for both volunteers and organizations.
• Matching people with the right opportunities can be challenging, especially when too many volunteers want the same thing.
• Algorithms play a crucial role in matching volunteers with opportunities but can lead to situations where too many people chase the same option, resulting in disappointment.

Daniela Savan's Research on Matching Algorithms

• Daniela Savan, an associate professor at Stanford Graduate School of Business, studies algorithms and their impact on matching markets, including dating apps and volunteer matching.
• Savan's research focuses on designing algorithms that promote fairness and equity in online platforms.
• In the case of Bumble, where women initiate contact, the research found that this actually benefits men. Despite sending fewer messages, men's messages are more likely to be answered, leading to more matches.

Volunteer Match Case Study

• Volunteer Match, an online platform connecting volunteers with organizations, faced an issue where popular opportunities received an overwhelming number of signups, while others received none.
• Daniela's team recommended adjusting the search algorithm to reduce the visibility of opportunities that had already received a sufficient number of signups.
• This change resulted in an 8-9% increase in the number of opportunities receiving at least one signup without significantly affecting the total number of signups.
• The findings suggest that the imbalance was primarily due to display prominence rather than inherent popularity of certain opportunities.
• Volunteer Match implemented these insights nationwide, demonstrating the broader applicability of the research in the nonprofit sector.

Importance of Equity in Algorithm Design

• Daniela emphasizes the importance of designing algorithms with equity in mind, ensuring that all opportunities have a fair chance of being seen and attracting volunteers.