On Juneteenth and Invisibility
It’s Juneteenth today. Juneteenth is a celebration, but also a recognition of the fucked-uppedness of this whole situation. I spent a lot of time in my early twenties thinking and writing about Juneteenth, the unfinished, posthumously published second novel by Ralph Ellison. Now, if you know me at all, you know that I take a very strong stand on this:
Invisible Man is the Great American Novel.
It is lovely for me to debate this point and I welcome all literature nerds to a discussion on this topic, but you’ll never move me off my soapbox about it. I feel so strongly about Ralph Ellison’s place in literature and American literature in particular, and his work made such an impact on my life, that “Ellison” is my oldest child’s middle name (I wanted it for the first name but marriage is about compromise, right?). I don’t think Ellison was really able to write a SECOND great American novel. The concepts that he was working on in Juneteenth were so complex and had so much depth, I’m not sure words on a page could really express what he was attempting to give to us. The work is beautiful nonetheless and I encourage everyone to get a copy and dive in. But do yourself a favor and read (or re-read!) Invisible Man first.
Ellison’s first novel has “invisible” in the title, and Juneteenth (the book and the day) are also about something invisible - the invisible news of the end of legalized slavery (but the continuation of genocide) against Black people in America, which came two years delayed from Washington, DC to Texas. Can you see Freedom? What about Justice?
Now believe it or not, I’m going to tie all this to nonprofit data & technology. Because recently I have been obsessed with what is invisible about data & technology, which in fact is a lot. So much invisible stuff can make it pretty tough to learn, use, and love data & tech for mission-driven work. But with the strength and conviction of Ellison in giving us his writing, we must all give it our best shot at learning and using this stuff, so that we can accelerate our work towards making this world and life better and more fair for all human people.
So today I want to do a little thinking on what is invisible in data & tech work for good, and hopefully make it all a little more accessible!
Databases and Data Models behind User Interfaces
I’ve been opining (or is it complaining) about this for a while. Google the phrase “ditch the spreadsheets” or “spreadsheet alternatives” and you will get a lot of results from software companies and programmers claiming that they have a coding language or a user interface that is just so superior to spreadsheets and will solve all your organization’s problems with data. Right, of course, because everyone working in nonprofit work believes that there is a “silver bullet” to solve problems. Nah. And what these companies don’t tell you is that, surprise surprise, their software is mostly a pretty user interface (a nice looking website) that has made assumptions about what functionality you need built into it and is sitting on top of a good old fashioned database. And what is a database if not a fancy spreadsheet, holding data in little cells that are organized in rows and columns. To really use these systems to help us work towards our missions, it is absolutely integral that we understand the “data model” that is invisibly at work behind the scenes.
A “data model” can be tricky to define, but I like what Wikipedia says, because it uses the word “abstract”: “an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities”.
Sure you can draw a map of what it all looks like, but we don’t keep these maps handy - it is more likely that we hold this invisible knowledge in our heads. Any software that doesn’t make their data model completely transparent and easily accessible (on your websites or in your help docs, please!) is doing you a disservice by saying that they can “get you out of spreadsheets.” You will have the same learning curve issues in those systems as you do with Excel or Google Sheets or anything similar to that. The invisible data model can help us if we keep it visible in our minds’ eye, or it can hurt us if we never learn it or have a vision of it to work within our systems.
Invisible Tables in spreadsheets
Let’s talk about something more fun - you creating something invisible! In programming/coding and more importantly in Excel and Google Sheets, you have the ability to create what I’ve been calling an “invisible table”, but I recently learned from this nerdy but absolutely amazing write-up might also be called “hash tables.” What are these wondrous things? These are groupings of cells, rows, and or columns that you can make exist outside of the boundaries of your lines and boxes in your spreadsheet. Here is an example about using a simple invisible table to make your vlookups even better - it’s only a 2-min long video!
Variables in coding
One of my biggest barriers to learning how to read and write in any programming language has always been the amount of invisible definitions happening. In coding we have something called Variables. I liked this partial definition of variables: “It is helpful to think of variables as containers that hold information. Their sole purpose is to label and store data in memory” (full explanation here). For example, if I use “pi” a lot in my work (hey, maybe I have to calculate the circumference of things a lot!), then instead of typing 3.14 a whole lot of times in my calculations, I have instead create a shorter variable that will stand in for that number. In programming it will look something like:
Pi = 3.14
If I do that in my programming language, then anywhere else in my code that I use the variable “Pi” I will really be using the numbers 3.14. So if I write a line of code that says
Pi * 2
Then it will spit out the answer of 3.14 * 2 = 6.28. Or if I write:
Pi * 2 * 6
Then it will spit out the answer of 3.14 * 2 * 6 = 37.68, which would be the circumference of a circle where 6 is the radius. Hell, let’s define the radiuses of a few circles. We’ll make circle1radius = 6 and circle2radius = 10 and circle3radius = 12. So how do we get the circumference of circle 3?
Pi * 2 * circle3radius
The definitions of these variables often are left invisible and it can make reading and writing programming languages really tough, or at least it made it tough for me. But just understanding the concept of these invisible variables really helped me get better at understanding what these coding languages are all about.
Racism
This one really isn’t that invisible in many ways, and countless experts like Ruha Benjamin have helped shed light on the issue. But racism does persist throughout all of our data & technology systems. Down to those invisible variables in the code, computer programs and data are under the constant misguided design of their creators and users. It isn’t always that easy to see how the technical parts are being racist, but we see it in the real life consequences of things like racists facial recognition software and stats that skew the picture one way or another. There is also racism in the things we leave out of our data and tech. Should all programming languages come with variables that define BIPOC? Should all spreadsheets have invisible tables that have information in them about things like demographic population data? When working with any kind of data and technology, it is a good idea at many points along the way to step back and ask - what am I not seeing? What am I not looking for? What might be racist in this data/technology, visible or invisible?
One more little personal thing about me: I like to practice something I call Radical Transparency. It started out as a way for me to say that I don’t really understand office politics well and am just better at my work when all information is available to all people as soon as possible. I’ve experienced a few workplaces where the “upper management” was trying to dole out information selectively, and I just never saw it work out very well. And I’m not really a secrets-keeper. So of course I want to apply this concept to data & technology. None of this should be 100% invisible to us, and I want to bring it out of the shadows as much as possible.
With that in mind, if there is anything that feels invisible to you about your data & tech, let’s investigate it together! Comment here or get some time on my calendar and let’s make the invisible visible.
A short dedication here, to Samantha Shain who has written extensively about these concepts and the incredible data and tech work of civil rights activists and leaders on her blog. If you liked this piece, you will LOVE her work.
And of course, a dedication to Ralph Ellison - great American author and activist. I shudder to think of the world without you and who I would be if I hadn’t received the incredible gifts of Invisible Man and Juneteenth.
Sorry, I did need more dedications in fact - to Keith Leonard and Michael Manson, two incredible people and educators who took the brunt of my fumbling through Ellison’s work before I was really ready to articulate thoughts on it, and who had to read through countless versions of my senior thesis on Juneteenth. And to my friends who were with me at that time helping me learn, and have had the grace to continue being my friends even as I fumbled through it all.
