Almost two years ago, I published my personal contribution to the “Google’s Autocompletion algorithms discriminate against women” debate by adding some context about Google and about algorithms.
Today, I could write something very similar regarding the headlines informing us that, according to a recent study, Google’s advertising algorithms discriminate against women. And it is probably a handy opportunity to let you know that my phd research in social sciences – still ongoing – is precisely about interaction with Google’s advertising algorithms…
However, this blog post is not going to be about my research. But when I saw the headlines about “discriminating advertising algorithms” I simply couldn’t *not* blog about it.
Luckily, WIRED has already taken care of asking the very same question I asked in my 2013 blog post about Google’s autocompletion algorithms: who or what is to blame? In a short but discerning piece WIRED explains the complex configuration of Google AdSense:
Who—or What’s—to Blame?
While the study’s findings would suggest Google is enabling discrimination, the situation is much more complicated.Currently, Google allows advertisers to target their ads based on gender. That means it’s possible for an advertiser promoting high-paying job listings to directly target men. However, Google’s algorithm may have also determined that men are more relevant for the position and made the decision on its own. And then there’s the possibility that user behavior taught Google to serve ads in this manner. It’s impossible to know if one party here is to blame or if it’s a combination of account targeting from all sources at play.
This configuration has allowed powerful companies to present their services as ‘platforms’, phenomenal and simultaneously neutral vessels of communication filled by numerous individual users’ actions only. The complexity of the algorithmic systems at hand – because it is never simply Google’s algorithm (sing.) lest we forget – contributes to make locating accountability impossible if we keep looking for intentionality.
However, the authors of the “discriminating advertising algorithms” research argue that the effects they have uncovered, whether intended or not, are a matter of concern in any case:
… we are comfortable describing the results as “discrimination”. From a strictly scientific view point, we have shown discrimination in the non-normative sense of the word. Personally, we also believe the results show discrimination in the normative sense of the word. Male candidates getting more encouragement to seek coaching services for high-paying jobs could further the current gender pay gap. Thus, we do not see the found discrimination in our vision of a just society even if we are incapable of blaming any particular parties for this outcome.
Furthermore, we know of no justification for such customization of the ads in question. Indeed, our concern about this outcome does not depend upon how the ads were selected. Even if this decision was made solely for economic reasons, it would continue to be discrimination. In particular, we would remain concerned if the cause of the discrimination was an algorithm ran by Google and/or the advertiser automatically determining that males are more likely than females to click on the ads in question. The amoral status of an algorithm does not negate its effects on society.
Btw, the idea of starting with a focus on the “effects on society” and working backward has also been suggested in a recent Atlantic article about Google’s search results (just ignore the arguable opposition of “expert” vs. “neutral” if you can). The article was brought to my attention by Philippe Wampfler who explicitly suggests Google should take responsibility for the company’s decisions by showing face and not hiding behind the ‘platform’ discourse.
And before everyone turns – deservedly – to the Great Glitch of July 8, let me share three more links from my online advertising bookmark folder:
- Discrimination in Online Ad Delivery
- Google ads and the blindspot debate
- Credit Scores, Life Chances, and Algorithms
It goes without saying that the three articles are recommended reading. They are all related to online advertising and approach the topic from very different angles.
Then again: several issues of the current ‘advertising algorithm debate’ resemble what has already been discussed, e.g. in the context of other Google algorithms (poke: my 2013 piece on autocompletion and the links within).
And one day I might write more specifically about Google and big data and demographics and targeting and profiling…