News Release

Female AI ‘teammate’ generates more participation from women

Reports and Proceedings

Cornell University

ITHACA, N.Y. – An artificial intelligence-powered virtual teammate with a female voice boosts participation and productivity among women on teams dominated by men, according to new Cornell University research.

The findings suggest that the gender of an AI’s voice can positively tweak the dynamics of gender-imbalanced teams and could help inform the design of bots used for human-AI teamwork, researchers said.

The findings mirror previous research that shows minority teammates are more likely to participate if the team adds members similar to them, said Angel Hsing-Chi Hwang, postdoctoral associate in information science and lead author of the paper.

To better understand how AI can help gender-imbalanced teams, Hwang and Andrea Stevenson Won, associate professor of communication and the paper’s co-author, carried out an experiment with around 180 men and women who were assigned to groups of three and asked to collaborate virtually on a set of tasks (the study only included participants who identified as either male or female).

Each group had either one woman or one man and a fourth agent in the form of an abstract shape with either a male or female voice, which would appear on screen and read instructions, contribute an idea and handle timekeeping. There was a catch – the bot wasn’t completely automated. In what’s referred to in human-computer interaction as a “Wizard of Oz” experiment, Hwang was behind the scenes, feeding lines generated by ChatGPT into the bot.

After the experiment, Hwang and Won analyzed the chat logs of team conversations to determine how often participants offered ideas or arguments. They also asked participants to reflect on the experience.

“When we looked at participants’ actual behaviors, that’s where we started to see differences between men and women and how they were reacting when there was either a female agent or a male agent on the team,” she said.

“One interesting thing about this study is that most participants didn’t express a preference for a male- or female-sounding voice,” Won said. “This implies that people’s social inferences about AI can be influential even when people don’t believe they are important.”

When women were in the minority, they participated more when the AI’s voice was female, while men in the minority were more talkative but were less focused on tasks when working with a male-sounding bot, researchers found. Unlike the men, women reported significantly more positive perceptions of the AI teammate when women were the minority members, according to researchers.

“With only a gendered voice, the AI agent can provide a small degree of support to women minority members in a group,” said Hwang.

For additional information, see this Cornell Chronicle story




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