Snap still has a lot of work to do to meet its diversity goals. The company released its second diversity report, which confirms the company is still predominantly white and male.
In fact, Snap’s numbers haven’t changed much since. , when the diversity data was first published. Snap’s workforce is 65% male and 47% white, according to the report. It’s very similar to his previous figures where he was 66 percent male and 51 percent white. (It should be noted that Snap says it has changed the way it collects data, so this year’s numbers are not an “apples to apples” comparison to last year, even though “the numbers of representation have remained broadly the same ”overall)
The numbers aren’t much better when you look at the leadership and technology roles. Technical roles are still dominated by men who make up 81% of tech jobs, including software engineers, product designers and researchers. At executive level and above, women held 26 percent of roles even though they made up 33 percent of the total workforce. At the same time, the company notes that it has almost doubled the number of women in “technology leadership” jobs.
In other areas, Snap has actually done worse than its last report. Asian representation in leadership roles actually declined from 16% to 14%. And overall Hispanic representation also declined slightly (from 6.8% to 6.8%). Despite these setbacks, the company says it is optimistic for the years to come and is “on track” to double the number of women in tech jobs by 2023 and double the number of people from racial backgrounds under. -represented in the company by 2025.
The report also highlights other internal work being done to make Snap “a fairer, more inclusive and anti-racist company”, such as rewriting its algorithms “to eliminate unconscious bias.” For example, the report states that Snapchat’s in-app camera can be improved, noting that while the camera’s face detection lenses are mostly trained on white faces, people with darker skin may have a worse experience. In addition, the company has a team of employees who “develop a solid framework for how we think about prejudice and fairness in the field of artificial intelligence”.
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