Textio co-founder and former CEO Kieran Snyder. (Photo courtesy of Kieran Snyder). Understanding bias in workplace communication, whether it’s in job descriptions, performance feedback or elsewhere, was a founding objective of Textio, the Seattle-based augmented writing startup.Co-founder Kieran Snyder stepped away as CEO of the 11-year-old company a year ago, but she’s still hard at work analyzing the impact of bias, especially as it relates to the current rise of large language models and generative AI.Snyder launched a website last February called Nerd Processor in which the linguistics PhD shares her data stories, revisits prior research and discusses new research.On a new episode of the “Shift AI” podcast, Snyder discussed her views of the evolving landscape of AI in workplace communications.She revealed details of an experiment she ran in which she asked ChatGPT to write sample performance feedback for a digital marketer who had a tough first year on the job who went to Harvard University, and also a digital marketer who had a tough first year on the job who went to Howard University, the prominent historically Black college and university.“I did hundreds of queries where the only difference was the alma mater, Harvard versus Howard. And it was fascinating,” Snyder said (12:00 mark below). “The development areas that the system imagines will be needed for people who go to Harvard are things like ‘you should step up to lead more.’ But the development areas it imagines for the Howard alums are things like, ‘you don’t have good attention to detail; you have missing technical skills.'”While Snyder said those can be valid feedback comments, and it would be difficult to look at any one document from the experiment and put your finger on the bias, looking at the data in aggregate tells a different story. The types of feedback that the system associates with people who went to the historically black college and university are much more functional and fundamental in nature.She told “Shift AI” host Boaz Ashkenazy that it was a perfect example of how building a data set with this kind of bias in mind from the start just produces samples that propagate the bias.Listen to the full episode below, and subscribe to the Shift AI Podcast and hear more episodes at ShiftAIPodcast.com

GeekWire’s startup coverage documents the Pacific Northwest entrepreneurial scene. Sign up for our weekly startup newsletter , and check out the GeekWire funding tracker and venture capital directory .(Textio Image)Textio laid off 15 employees on Wednesday, the company confirmed, citing a restructuring at the Seattle augmented writing startup.The company did not specify how many people it still employs. There were more than 70 workers remaining after cuts last year.Founded in 2014, Textio uses artificial intelligence and machine learning to help remove bias from workplace language for hiring and performance feedback. Customers include Bloomberg, Cisco, Hulu, Oracle, Spotify, and Warner Music Group.The company laid off 14 employees in March 2024, and cut another 15 in 2023.“The side of our business that supports our Feedback product is growing, and we needed to invest in a different mix of roles and skills to continue building and selling,” a Textio spokesperson said in a statement to GeekWire.The company said workplaces are ramping up coaching and performance management support for managers, and Textio is investing in its ability to build and deliver on those customer needs. It will be opening up some new roles, including in sales and product marketing.Textio has raised $42.5 million from investors including Industry Ventures; Operator Collective; Emergence Capital; Scale Venture Partners; Cowboy Ventures; Bloomberg Beta; and Upside Partnership.Textio co-founder Kieran Snyder stepped down as CEO in January 2024. Jensen Harris, co-founder and previously chief experience officer — and Snyder’s husband — is now CEO

The layoffs come just months after Textio announced a CEO change, as co-founder and former CEO Kieran Snyder moved into an emeritus role as chief scientist.