The Insightful Leader
Sent to subscribers on June 29, 2022
How’s your summer going? Here in Chicago, at least, we’ve had some really hot days already. And while I know some people love the summer heat, I unequivocally do not. And it turns out I’m not alone.
Today, we’ll look at research that shows how heat can lead to negative behavior by employees. And, switching gears, we’ll also hear about a school district fiasco that lays out the limits of AI when it’s used to solve complex human problems.
Is It Too Hot to Help?
About a decade ago, Moscow experienced its worst heat wave in centuries. Then, the following summer, temperatures returned to normal.
This dramatic swing created an intriguing natural experiment for Maryam Kouchaki and a coauthor who were interested in understanding how environmental factors, like excessive heat, shape our behavior. In particular, they wondered whether “prosocial” behaviors—helpful, ethical acts for which people are not explicitly rewarded—took a hit during the sweltering heat.
They used a data set from a large Russian retailer that had used mystery shoppers to visit its stores and report on how the staff treated customers. Did the salesperson volunteer to help customers? Did the salesperson greet customers? Did they ask questions to find out what customers were looking for?
The researchers found that employees were more than twice as likely to offer help during the cooler summer than during the sweltering one. A second study, which looked at whether students would volunteer to fill out a survey, found similar results: those in a comfortably air-conditioned room answered many more survey questions than those in a hot, stuffy room.
Additional studies showed that people’s unwillingness to help could be explained by their feelings of fatigue and their negative mood.
“People know they are expected to display positive attitudes and help the client or their instructor,” says Kouchaki, who is an associate professor of management and organizations at Kellogg, “but because of discomfort, your cognitive resources are depleted, so you have less ability to regulate your emotions.”
For Kouchaki, the results reinforce the idea that employees’ behavior can be influenced by their environment. So if you can provide a comfortable work environment—beyond just air-conditioning—you’ll improve performance. And if an employee disappoints, it is worth taking the extra effort to investigate whether outside factors may have played a role.
“My goal is to increase awareness of these contextual factors,” Kouchaki says, “and at the same time to increase conversations in organizations to help people learn and grow.”
You can read more about the research here.
How a School District’s Fiasco Sheds Light on the Limits of AI
Let’s shift from the height of summer to the end of summer, when kids go back to school. We’ve got a really interesting new The Insightful Leader podcast episode that looks at the strengths and weaknesses of AI through the lens of a school-bussing fiasco in Boston a few years ago.
In 2017, Boston’s public school district announced a contest to help it save money on transportation. Sebastien Martin, now an assistant professor of operations, was at the time a PhD student at MIT. He and a couple MIT colleagues worked on an algorithm that offered up a solution that would save the district millions of dollars by allowing each bus to travel more efficiently between multiple schools, thus cutting down on overall transportation costs. Not so controversial, right?
But the algorithm was recommending something else: to change some school start times. This would allow the buses to be even more efficient and would right some historic inequities, since the most desirable school start times–not too early, not too late–were clustered in whiter, wealthier neighborhoods. Yet when this plan was introduced to the public, many parents—of all races and income levels—were furious because the new start times would disrupt their family and work schedules.
You’ll hear in the podcast from parents and school officials who lived through this very public, acrimonious debate. For Martin, the main takeaway is that while AI can offer some very good solutions that human brains could not come up with, we still need humans to evaluate the solutions in whatever messy contexts they sit.
Martin says it’s important for leaders to understand how to use public policy and algorithms in tandem with each other.
“You need translators; you need people who know both worlds.”
You can listen to the full podcast here, and can read an article about Martin’s research and experience in Boston here.
LEADERSHIP TIP
“Is their experience actually relevant to us? What if their careers are fundamentally different from ours, the mere mortals?”
—Professor Dashun Wang in Insight, on whether Nobel Prize winners’ career paths tend to be unique.
How’s your summer going? Here in Chicago, at least, we’ve had some really hot days already. And while I know some people love the summer heat, I unequivocally do not. And it turns out I’m not alone.
Today, we’ll look at research that shows how heat can lead to negative behavior by employees. And, switching gears, we’ll also hear about a school district fiasco that lays out the limits of AI when it’s used to solve complex human problems.
Is It Too Hot to Help?
About a decade ago, Moscow experienced its worst heat wave in centuries. Then, the following summer, temperatures returned to normal.
This dramatic swing created an intriguing natural experiment for Maryam Kouchaki and a coauthor who were interested in understanding how environmental factors, like excessive heat, shape our behavior. In particular, they wondered whether “prosocial” behaviors—helpful, ethical acts for which people are not explicitly rewarded—took a hit during the sweltering heat.
They used a data set from a large Russian retailer that had used mystery shoppers to visit its stores and report on how the staff treated customers. Did the salesperson volunteer to help customers? Did the salesperson greet customers? Did they ask questions to find out what customers were looking for?
The researchers found that employees were more than twice as likely to offer help during the cooler summer than during the sweltering one. A second study, which looked at whether students would volunteer to fill out a survey, found similar results: those in a comfortably air-conditioned room answered many more survey questions than those in a hot, stuffy room.
Additional studies showed that people’s unwillingness to help could be explained by their feelings of fatigue and their negative mood.
“People know they are expected to display positive attitudes and help the client or their instructor,” says Kouchaki, who is an associate professor of management and organizations at Kellogg, “but because of discomfort, your cognitive resources are depleted, so you have less ability to regulate your emotions.”
For Kouchaki, the results reinforce the idea that employees’ behavior can be influenced by their environment. So if you can provide a comfortable work environment—beyond just air-conditioning—you’ll improve performance. And if an employee disappoints, it is worth taking the extra effort to investigate whether outside factors may have played a role.
“My goal is to increase awareness of these contextual factors,” Kouchaki says, “and at the same time to increase conversations in organizations to help people learn and grow.”
You can read more about the research here.
How a School District’s Fiasco Sheds Light on the Limits of AI
Let’s shift from the height of summer to the end of summer, when kids go back to school. We’ve got a really interesting new The Insightful Leader podcast episode that looks at the strengths and weaknesses of AI through the lens of a school-bussing fiasco in Boston a few years ago.
In 2017, Boston’s public school district announced a contest to help it save money on transportation. Sebastien Martin, now an assistant professor of operations, was at the time a PhD student at MIT. He and a couple MIT colleagues worked on an algorithm that offered up a solution that would save the district millions of dollars by allowing each bus to travel more efficiently between multiple schools, thus cutting down on overall transportation costs. Not so controversial, right?
But the algorithm was recommending something else: to change some school start times. This would allow the buses to be even more efficient and would right some historic inequities, since the most desirable school start times–not too early, not too late–were clustered in whiter, wealthier neighborhoods. Yet when this plan was introduced to the public, many parents—of all races and income levels—were furious because the new start times would disrupt their family and work schedules.
You’ll hear in the podcast from parents and school officials who lived through this very public, acrimonious debate. For Martin, the main takeaway is that while AI can offer some very good solutions that human brains could not come up with, we still need humans to evaluate the solutions in whatever messy contexts they sit.
Martin says it’s important for leaders to understand how to use public policy and algorithms in tandem with each other.
“You need translators; you need people who know both worlds.”
You can listen to the full podcast here, and can read an article about Martin’s research and experience in Boston here.
LEADERSHIP TIP
“Is their experience actually relevant to us? What if their careers are fundamentally different from ours, the mere mortals?”
—Professor Dashun Wang in Insight, on whether Nobel Prize winners’ career paths tend to be unique.