Personally, I’m interested in A.I. and how it applies to my work as an Information Architect and how chatbots and content recommendation engines can help my users more easily and naturally find what they are looking for. I’m interested in IoT as it applies to my newbie-level work on e-textiles.
With so many impressions and ideas tucked into my head, I left the conference inspired and yet tongue-tied. I knew that something profound needed to be teased out, but what?
***
As I prepared for and traveled to the conference, I monitored Twitter #ghc17 to get a preview of the scene at the conference.
The top tweet was a supportive rallying cry from a tireless male ally and I was inspired. As the day went on, this tweet remained as the top tweet, and it made me wonder.
As I prepared to write this post, I checked Medium itself to see impressions from Grace Hopper.
The top result was a thoughtful post from a male attendee of Grace Hopper 2016. This also made me wonder.
How can it be that representative voices of this conference about women in computing — one rising to the top for the first 24 hours and one rising to the top a year later — are not the voices of women?
As a woman of color, I’m not shocked, as I see an endless queue of folks who don’t know my experience, put into positions of being the dominant voices speaking about and around my experience, whether they like it or not.
And, I’m not asking in outrage. Here’s a :-) to prove it. I’m asking because it’s an interesting question.
***
I see three factors at work that produced these results:
Content
User behavior
Algorithms
The content emitted an information scent and evoked user behavior that made algorithms identify it as highly relevant to users looking for information about Grace Hopper.
This is a loaded potion.
One could make guesses about why a man’s tweet supporting women would rise to the top of Twitter, besting tweets from women supporting women.
One could make guesses about why more womens’ voices speaking on Grace Hopper are not surfaced in Medium’s top search results, instead making the top story a man’s experience at the conference a year ago.
But I want to talk about the algorithm.
al·go·rithm
a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.
Why the algorithm?
The algorithm is the god from the machine powering them all, for good or ill. (from How Algorithms Rule the World)
These Medium and Twitter examples illustrate symptoms of the issue that rose to the top of everything I took away from Grace Hopper: monochromatic algorithms.
The lack of diversity in technology we see today is kindling a humanitarian crisis in which ubiquitous monochromatic algorithms will marginalize any people who were not represented in their design and creation.
At this point in the flow, we’re hearing the issue surfaced at this level:
Women are paid less than men doing the same job.
Discrimination in the hiring process keeps women and minorities out of the tech workforce.
We don’t have enough women and minorities in the tech workforce candidate pipeline.
But to be clear, what I’m talking about is the long-tail problem that will manifest as a result of these initial factors.
If we don’t course-correct, our lives in the future will be shaped by algorithms produced by a monochromatic tech workforce that does not understand, reflect, or empathize with its user population.
Here are just a couple of examples of these monochromatic algorithms at work:
