Forms are terrible, and other life advice

I’ve spent my last few days thinking about forms

• I joined this group and we’re working on a project, and I’m part of the data team. And we were working on form information to collect data. I’m humbled that we have some incredibly bright and thoughtful persons working on the team. Throughout our discussions, it became incredibly clear how terrible forms are.
• But I’ve know this. You see, back in the days of this young’un appylying to United States universities, they would mostly ask for a zip code. Application after application would not let you hit that submit button unless you put in a state and a zip code, and well, my country of birth has neither. Very quickly, we learned that you could put in “99999” or “00000” as the zip code, or use a random State (I’ve never tried Nevada; why not?) in a drop-down. You could not submit unless you picked “some state” so a random one is as good as any, right? But sometimes the form wouldn’t accept “00000”. So you’d hope “99999”. I think for one form, it didn’t work, so I just put in a random zip code. I mean, it’s not technically lying if the form is terrible and there is no other way to get it to submit, right? They were all pretty terrible.

So this week

• This past week I started reading this rather brief book that talks about data and ethnography called “Technically Wrong”. The first 100 pages that I’ve been through talk about inappropriate and failing usability design. But reading through it, I’ve felt that these examples felt so familiar. Of course they did; when I was living in my country of birth, you became painfully aware that those forms or those designs weren’t really designed for you, so we would “hack” our way around them.
• My family has a long history using things like Skyboxes or myself (the personal Skybox) en-route to ship things, either when they are needed brand new or are being repaired in the United States. What happens a lot is that on trips to the United States or other places, my family of techies will see something that is interesting and useful, purchase it, and all is well. But then, it breaks. And unfortunately, these items were never meant to be serviced in places that weren’t the United States. The result is a comical recommender system that is perpetually confused, as it cannot tell whether I am the person requesting an item, or whether it is one of my parents. Our technology is not so sophisticated yet.
• This is a story all too familiar to any immigrant living in the United States, with family living outside of the United States. Many years ago, perhaps we stuffed our suitcases with new sneakers and pairs of socks for our nephews and cousins. Today, it is with digital amenties that delight when they are first brought to us, but are a pain when they experience wear and tear.

Imagine this (A true story)

• Imagine this: a daughter has bought her father a Kindle. However, when he logs into his Kindle, it wants to authenticate his account by sending two-factor auth to his daughter via her mobile phone. This means that he has to text her and ask her about the number that was sent to her phone (because United States numbers required only of course) to unlock his Kindle. And this is a timed transaction, so it has to be done before the transaction times out.
• In the age of companies looking to make profits, and hiring many immigrants whose families live outside of the United States, unfortunately this isn’t really a thing that seems to matter…shrug.

But back to those forms

• Why do I care about forms? Well, because forms are the pipeline to data; the data we in Data Science, Machine Learning and AI take for granted. If we don’t have an understanding for and healthy skepticism for the way our data is collected, can we really call ourselves “scientists” at all? Are we analysts? A friend and I were having this discussion this weekend. If we accept this lack of skepticism about the way our data is collected, the way it is encoded, archived and used, what does that mean for the future of our field? What does that mean for the future of us?

So I asked my friend

• I reached out to my friend, the wise one, who I looked at with wonder about how he had so much insight about how forms should be designed and I asked him “how can I learn from you? I want to learn how to do this better”. And he told me a bit about his background and made some recommendations. And I’ve been musing about it ever since.
• Looking back, today I wonder about those forms and whether if they had taken the time to ask someone like myself about how we would use them, if they might have been designed differently.
• A while ago, I was registering for an event hosted by a governmental agency, and the gentleman registering me asked me “Which is it? Is it Trinidad OR Tobago? Pick one!”. I tried to explain to him that they were together; it’s one twin-island republic. Triumphantly, after he looked it up, he responded that “I was right” (as though I could not validate for myself the very place that I was born). It was a comical but tragic incident, but it speaks more broadly to the relationship we as people who analyze and collect data, and those who give up their data have. Do we see the data and think as data scientists or analysts that for it to be authentic, we alone can validate it? Are we authoratative in a way that diminishes the experiences and inputs of the very people we collect data from? Or do we see ourselves as participatory and collaborative, as part of a wider process.

I guess I’ve been thinking about this a lot

• I was asking someone the other day “How do you know when a problem or project is done”? When is something enough. The Computer Scientist and agile process says that you as the designer of that project, as the person architecting that system, should specify when something is done, and that’s how you know a project is over. It’s a very neat, convenient way for someone in Computer Science to think about a problem, but that isn’t really how things work in the real world, is it? I wonder how we can be so blithely unaware of this reality, yet take ourselves so seriously.
• A mechanic knows this isn’t the case, as things are a trade-off. You make a fix, but something else may come loose or rattle. Your tires may need to be aligned. Your fan belt is rattling again. Doctors know this to be the case, too; someone can experience little to no symptoms, but that doesn’t mean that they are fully cured, or that they will be cured forever. It seems to be only the computer scientist without systems thinking who sees the world this way. Even artists complete paintings but know that a painting is never really done.
• When I worked as a student camera tester, during my time as an Undergraduate student, it became painfully aware that certain 16mm film magazines would repair, and then break, over and over again. We were able to use a maintenance system that tracked over time, not just the magazines, but their repairs, the dates they were repaired, and who used them. We built systems on the premise that there is wear and tear, and there are not simple solutions, and that things in the real world break. We also built systems that accounted for user error and equipment failure, as well as general wear and tear. Our data was rich enough to also give information to the person creating a diagnostic as to how the magazine could be fixed, and give them information on the historical context of maintenance. And, of course, when the magazines themselves were no longer usable, given some threshold of usability both in the system and in the real world, with advice from the electronics technician and the service administrator (ie both the person repairing the thing and the person collecting the data).
• When you work on systems that are supposed to help humans, interact with humans, then, how do we measure what “done” is? Humans are all so different, this may never be the case. So how is that expected to fit into a system if we are all such anomalies? It’s a question that’s difficult to answer, but there are many fields that have already explored such topics.

And that’s it