I have two younger brothers, and once a week, the Solberg kids have a phone call. We each hold management positions in the technology world, so we swap notes about work a lot. We may be one of the few families with a running joke about Kubernetes. After our call the other day, my brother Mike sent me this article from the National Bureau of Economic Research, and I have been geeking out over it ever since. From what I can tell, it’s one of the first studies on how generative AI can improve an organization’s effectiveness – and not just in terms of its bottom line.
Something I’ve been thinking about is how to train empathy. If you work in user experience, you understand how important empathy is to good design. Often, we end up working with solutions that suffer from “developer-centered design,” where features are built to check a box while minimizing the work for the development team. Also, we see “stakeholder-centered design,” where software development happens to impress someone with a pile of money. At the end of the day, if the people who need your solution can’t figure out how to use it, none of the rest of it matters.
Empathy means putting yourself in someone else’s shoes. More importantly, it involves caring about other people, which seems hard to come by these days. Wouldn’t it be great if we could make something that teaches people how to do that? For a long time, I wondered whether virtual reality could show you someone else’s perspective, and I still think it could. This study shows there may be a different way.
The study took place in a large software company’s customer support department. Working a help desk is a job where empathy is key to success. Not only do you have to be able to solve an irate and frustrated customer’s problem, you have to ensure they have a positive experience with you. In this research, customer support agents were given an AI chat assistant to help them diagnose problems but also engage with customers in an appropriate way. The assistant was built using the same large language model as the AI chatbot everyone loves to hate, ChatGPT. The assistant monitored the chats between customers and agents and provided agents real-time recommendations for how to respond, which agents could either take or ignore. As a result, overall productivity improved by almost 14% in terms of the number of issues resolved. Inexperienced agents rapidly learned to perform at the same level as more experienced ones. The assistant was trained on expert responses, so following its advice usually gave you the same answer an expert would give.
Here’s where it gets really interesting: a sentiment analysis of the chats showed that as a result of using the assistant, there was an immediate improvement in customer sentiment. The conversations novice agents were having were nicer. The assistant was trained to provide polite, empathetic recommendations, and over a short period of time, inexperienced agents adopted these behaviors in their own chats. Not only were they better at solving their customers’ problems, but the tone of the conversation was overall more positive. The agents learned very quickly how to be nice because the AI modeled that behavior for them. As a result, customers were happier, management needed to intervene less frequently, and employee attrition dropped.
The irony of AI teaching people how to be better human beings is palpable. Are the agents that used the assistant more empathetic? We don’t know, but from a “fake it until you make it” perspective, it’s a good start. That aside, this study is an example of how this technology could help people with all sorts of communication issues function at a high level in emotionally demanding jobs. Maybe we should spend a little more time thinking about how it could help many people succeed where they previously couldn’t and focusing less on how it’s not particularly good at Googling things.
These posts are written or shared by QIC team members. We find this stuff interesting, exciting, and totally awesome! We hope you do too!