When I first started writing freelance, I asked a friend of mine for advice on which online marketplaces I should use, and how I should present myself. After giving me loads of helpful advice (thanks, Jock!), my white, male friend speculated that I — as a woman of color — "would be a hit."
I wouldn't say that was my experience. I certainly received a lot of interest and a lot of personal messages. But they were not of a type I would call positive.
My experience appears to be fairly normal for Black people entering online marketplaces. Despite the fact that freelancers are covered by anti-discrimination legislation, research shows that Black freelancers — especially women of color — face a significant level of discrimination on these platforms.
In this article, I'll show you the evidence for that, share a few of my own experiences, and then think about what can be done about it.
Research into racial discrimination in online freelance marketplaces is rare. This is partially because of a design feature of these marketplaces: they don't collect data on the ethnicity of their users. Despite collecting a vast amount of other data, presumably in order that employers can search for precisely the freelancer they want, most platforms are strangely color-blind.
That’s understandable, of course. These platforms probably don't include racial data because they don't want hiring parties to filter search results to exclude freelancers of any particular racial background, instead presenting all people "on their merits." But, unfortunately, proclaiming color-blindness just exacerbates internal biases and can be equally harmful, while directly addressing race allows people to confront those biases head-on.
Because of this lack of data, research into racial bias on these platforms is time-consuming and of limited scope. As you probably understand by now, it’s impossible to know even little but important things such as how frequently Black freelancers have their invoices paid compared to their white peers. Equally, researchers do not have access to the private messages (and therefore the private experiences) of Black users of these platforms.
To date, this has meant that just one recent research paper has sought to analyze racial bias on these platforms. The findings make for depressing reading. "Our findings illustrate," say the authors, "that real-world biases can manifest in online labor markets and ... impact the visibility of some workers. This may cause negative outcomes for workers in the form of reduced job opportunities and income."
This research strikes a chord with me. My experience of these marketplaces — one shared with my Black freelancer friends — is that we appear to receive significantly lower reviews for our work than our white peers. This was also a key finding of the research I've mentioned, in which the researchers note that lower reviews result in Black (and Asian) freelancers being less visible on these platforms, and ultimately getting hired less.
A slightly more personal trend I've noticed is that employers on these platforms tend to "talk down" to Black and female freelancers, assuming that they don't know the basics of their business, even when they've been working in the industry for years. Just in the past few months, I've had employers explain to me basic financial literacy and try to “explain” to me how to code (I have a compsci MsC), despite lacking any dev experience themselves.
Even worse, where employers are keen to hire Black, female freelancers, it often appears to be part of a reputation management attempt, rather than being based on merit. I've been asked, for instance, to be "the face" of some employers, despite having a fairly low-level role for them, so they can fairly transparently prove their progressive credentials.
Fixing racism and sexism is not, of course, within the scope of this article!
However, I do think that there are some basic things that could be put in place in order to level the playing field for Black and minority ethnic women on these platforms. One would simply be for these platforms to collect basic information on race. The fact they do not is slightly strange, given that several studies have shown that even the most basic email marketing systems practice this method. Collecting this information would make research into racial bias on these platforms much more efficient, and allow us to plan further measures for the future.
Another approach could be for these platforms to make greater use of automation. AI bots could be deployed to automatically adjust review scores based on race, or even to interview prospective candidates. Almost 20% of marketing companies now use AI as part of their customer service, and these bots could have a huge advantage over (some) humans: They are color blind. Or at least some are: There is also research that indicates that AIs can have bias problems, largely as a result of the subconscious biases of the people (white, male) who design these programs. Because of this, we should treat this kind of automation with a little caution.
Third, employers looking to put in place fairer hiring practices would do well to explore employee referral programs, which can take some of the bias out of hiring decisions by distributing responsibility for them across a larger portion of your organization. Pay transparency can also help reduce bias across your entire organization, as well as indicate your responsible approach to prospective freelancers, who are more likely to want to work with you if you are open about your business.
The Bottom Line
It's important not to blame freelancing platforms unduly. Much of the discrimination that Black freelancers face on these platforms is nothing to do with the way in which they are built or run, but merely mirrors more widespread discrimination in hiring practices.
Nevertheless, these platforms should assume some responsibility to protect their users from discrimination and provide protection from harassment, and at the moment they are not meeting that bar. Merely collecting more information on their users would make investigations into racial bias easier to research, and deploying automated tools on these platforms might help to counteract some of the discrimination that is already apparent.