While our team starts working on our second season, we'll still be sharing insights, bonus content, behind-the-scenes audio, and "class takeaways" from Stanford Graduate School of Business faculty throughout the summer. Stay Tuned!

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Getting to elect our leaders is certainly a privilege. Yet, even in a representative democracy, the choice that citizens have is often only as good as the candidates they have to choose from. That’s why Professor Andrew B. Hall, The Davies Family Professor of Political Economy, wonders: How do we get society’s best and brightest to participate in politics?

As a political economist at Stanford Graduate School of Business and the Stanford School of Humanities and Sciences, Hall has spent years studying what motivates people to engage in the democratic process. On this episode of If/Then: Business, Leadership, Society, he shares his insights on how we can create a system that attracts a more diverse and qualified pool of candidates to run for public office and encourages greater voter participation at the local, state, and national levels.

Key Takeaways:

• Engagement starts with incentives: Whether encouraging better candidates to run for public office or driving higher voter turnout, Hall says our democratic system must incentivize citizens to actively take part in the process.
• What's at stake?: People are more likely to participate in democratic processes when they understand how the outcome directly affects them. Hall cites how homeowners are more likely to vote on local zoning issues that impact their property values.
• Adapting new technologies thoughtfully: As new technologies emerge, Hall says it's crucial to consider how they can be harnessed to improve democratic participation and address the challenges facing our political system.

More Resources

• Andrew B. Hall, The Davies Family Professor of Political Economy
• What Kinds of Incentives Encourage Participation in Democracy? Evidence from a Massive Online Governance Experiment
• Stanford GSB Insights:
• Inside a Government Where People Are Paid to Vote
• If You Lived Here, You Might Be a Voter By Now

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society.

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If we want to get fair outcomes, then we need to build fairness into algorithms.

Whether you’re looking for a job, a house, or a romantic partner, there’s an app for that. But as people increasingly turn to digital platforms in search of opportunity, Daniela Saban says it’s time we took a critical look at the role of algorithms, the invisible matchmakers operating behind our screens.

Saban is an Associate Professor of Operations, Information & Technology at Stanford Graduate School of Business whose research interests lie at the intersection of operations, economics, and computer science. With algorithms significantly influencing who gets matched with opportunities, she advocates for building “equity into the algorithm.”

In this episode of If/Then: Business, Leadership, Society, Saban explores how properly designed algorithms can improve the fairness and effectiveness of matching processes. If we want algorithms to work for good, then we need to make conscious choices about how we design them.

Key Takeaways:

• Algorithms shape online experiences and real-world outcomes: On dating apps, volunteer matching services, and job websites, algorithms play a crucial role in matching people with opportunities. While these matchups are facilitated in the digital domain, they impact real people in the real world.

• Algorithms are not neutral: Algorithms reflect the values and priorities of their designers and have the power to either perpetuate or mitigate inequities.

• Thoughtful algorithm design can improve outcomes for all: Saban's research demonstrates that algorithms can be optimized to create more balanced and successful matching experiences. By consciously choosing to prioritize fairness and equity in algorithm design, we can create systems that work for the good of all users.

More Resources:

• Daniela Saban, Stanford GSB faculty profile
• Stanford GSB Insights, "Cupid’s Code: Tweaking an Algorithm Can Alter the Course of Finding Love Online"
• "Improving Match Rates in Dating Markets Through Assortment Optimization" as published in Manufacturing & Service Operations Management

If/Then is a podcast from Stanford Graduate School of Business that examines research findings that can help us navigate the complex issues we face in business, leadership, and society. Each episode features an interview with a Stanford GSB faculty member.

See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.