Since age bias is something that could affect nearly all HR professionals, I am surprised that it does not get more attention. But, with the average age of employees in the U.S. going up (see here) and companies likely to recruit more older workers due to the unemployment rate being near recent lows, we are likely to see more attention paid to it, particularly in the technology field.
As with most bias, it can be introduced in a subtle way. For example, the term “digital native” describes those born roughly after 1990 that have had current technology (internet, smart phones, etc) pretty much their whole lives. A quick Indeed.com search shows many jobs where “digital native” is part of the description. Put another way, those older than 35ish should think twice before applying. Similarly, there is a whole literature (this article is an example) on how gender loaded terms in job postings affect who will respond to them.
Now, I get that you are advertising for tech jobs you are looking for employees who are completely comfortable in a digital environment and communicating with others who are. But, those are behaviors that can be assessed for with valid pre-employment tests without having to make assumptions about a person’s age.
And that is really the point about implicit bias—we make assumptions about groups without understanding people as individuals. We face a challenge in employee selection of creating processes that treat everyone fairly, but at the same time learn about them as individuals. It is a challenging needle to thread, but one that our businesses depend on us to do well. Using a combination of unbiased language and valid pre-employment tools can help us get there.
Or, if you would rather beat them than join them, you can open an art gallery that only focuses on artists ages 60 and older.