Biased models can cause ethical and legal problems. While your specific example is not a huge deal, the article gives the example of making hiring decisions in part based on sentiment analysis of candidates' text reviews. In this context, an engineer has responsibility to ensure that the model has no gender, race, or age bias towards candidates' names.

For a real life example, in 2017 Google was more likely to filter the comment "I am a woman" than "I am a man": https://www.engadget.com/2017/09/01/google-perspective-comme...

Or consider the impact of any bias in AI for criminal sentencing recommendations: https://www.wired.com/2017/04/courts-using-ai-sentence-crimi...