Brief Thoughts on "Tech Literacy"

impact

Jul 31, 2020 • matt • ~ 13 minute read • 2401 words


The Setup

It seems like the idea of “technology literacy” has become popular over the past few days, given the recent congressional antitrust hearing (NYT, WSJ, WaPo, The Economist, The Guardian) and Rep. Alexandria Ocasio-Cortez’s amendment to block the Military from recruiting on Twitch (Vice, The Verge, Fox).

Here are a few choice takes:

Is Twitter Facebook?

Twitch?

This last one is a bit disingenuous, but…

In the context of politics, complaining about technology illiteracy isn’t new. In past hearings, we’ve seen a smattering of… well, take a look for yourself:

The infamous “we run ads”

Is user data stored somewhere (from cnet)?

How many data categories do you store, does Facebook store, on the categories that you collect?

How much? All of it? Everything we click on? Is that in storage somewhere?”

— Deb Fischer (R-NE)

And… is Twitter Facebook (from cnet)?

Is Twitter the same as what you do?

— Lindsey Graham (R-SC)

And some articles:

In light of this, I want to spend a tiny bit of time to talk about the different kinds of tech literacy there are, and some very rough ideas on how we’d provide each of them.

The Breakdown

I think there are four distinct types of things that could be called “technology literacy”, which are often conflated with each other:

  1. The ability to use computers and phones efficiently in everyday situations. I’ll call this “digital literacy”. Examples would include sending emails, using a word processor, downloading an app, find information with Google or Wikipedia, or adding a friend on Facebook.
  2. A basic understanding of how some of modern computing and the internet work, and how this interfaces in our everyday lives. To me, this is what I mean when I normally say “technology literacy”, but for clarity, I’m going to call this “digital awareness”. Examples would include knowing what a cookie is, understanding new business platforms such as advertisements, analytics, or subscriptions, and roughly knowing where artificial intelligence, cloud computing, or location services appears in life.
  3. A nuanced understanding of the impacts and limitations of technology. I’ll call this “digital citizenship”. Notice that this is not understanding the actual implementation of the technology; instead, the focus is on how it behaves. Examples would be understanding that AI can be biased, knowing what two-factor authentication is and why it’s used, generally understanding what cryptocurrencies are and what caused the Bitcoin speculation/crash, or knowing what the “Great Firewall of China” is.
  4. A true, implementation-focused level of understanding in technology and its ripple effects. I’ll call this “digital expertise”. For example, this would be an understanding of where AI research is now (e.g. GPT-3), how quantum computing could change cryptography, or how Apple can make iPhones secure against law enforcement.

As you could guess from a framing perspective, I think everybody should be at the digital citizenship level. Obviously, this is not the case, but I want to muse a bit on why - and what we (as I wear a few different hats) can do.

I’ll also spend a bit of time talking about who needs to be at level 4 (digital expertise), and why it’s not as important as you might think.

An Interlude: Where are We Now?

Digital citizenship seems like a high bar. Anecdotally, I would say most people that I know are not at that level of understanding, and that’s considering the fact that I am a young computer science student at a university in California. I’d be willing to wager that at least two-thirds (if not more) of people in the United States have large knowledge gaps in understanding the impacts of technology.

While I don’t have concrete statistics to back up this claim (since this is a distinction that I am mostly conjuring up), this 2019 study by Pew Research has some interesting statistics (that you should, as always, take with a grain of salt):

In fact, some of these questions even had to do with digital awareness:

In my personal opinion, this is rather troubling. Another 2016 Pew study says that 14% of Americans are completely unprepared to use technology (e.g. do not use the internet for learning, and need help setting up new tech devices), and another 38% are “relatively hesitant” (e.g. have low level awareness of new technology concepts).

And of course, I’m sure you’ve met your fair share of people who are not digitally literate. I’ve worked with kids, adults, and elderly people who do not know how to type effectively, struggle to use Google, or ask me for help setting up their new phone - and that’s not even including questions like “why is it important to have a strong password”.

Why Digital Citizenship?

You might ask then, “Matt. Shouldn’t your focus be to solving digital literacy and awareness? Fight one battle at a time!”. And to some extent, you’re right. People who are digitally illiterate (probably to no fault of their own) are significantly vulnerable and disadvantaged: they’re more susceptible to phishing attacks, are gated in the types of things that they can do, and are missing out on things that would probably make their lives significantly easier and more productive.

At the same time, I think it’s bad that people often end their technology education there. People often have the attitude that things like net neutrality, digital privacy, or tech monopolies are too technical for the average person to understand.

To be frank, that’s just not true.

In conversations with friends, I’ve been able to explain complex CS policy decisions without leaning on technical understanding - and I think many others will share similar experiences as well! And these conversations are important: as technology envelopes more and more of our lives, it’s more crucial than ever to understand how technology impacts our lives.

Specifically, I think the level of nuance that comes with digital citizenship is the most important. Let’s take the general topic of AI; here are a common set of misconceptions about AI (and its subset of ML):

Some of these stem from not understanding the field at all (e.g. “AI can do everything”), but others are more nuanced: anecdotally, the concept that most machine learning algorithms are “black boxes” of some sort is a very novel idea with non-techy friends of mine (and remember, I’m a young, college-age CS student in California). Yet, understanding that concept is crucial when we consider the policies where we should use AI.

More broadly, this kind of knowledge should affect you in a few ways:

I think people tend to only focus on the political aspect - and don’t get me wrong, it’s very important to understand what net neutrality is when you vote for your representative - but it’s equally important in the other aspects as well! If you’re the type of person who practices ethical consumption (which to some extent, should be everybody), then you should take into consideration what principles tech companies uphold: are they pro open-source? Pro consumer privacy? Pro diversity in tech design?

It also impacts your career. No matter what you do in life, technology is taking up more and more of the workforce. The differences in correctly and incorrectly applying new technology can have drastic costs: maybe to you, or your employer, but often to people who aren’t even part of the decision-making process! Consider, for example, the idea of web accessibility: chances are that the average person hiring a web contractor doesn’t think about these kinds of things, but a lack of web accessibility disproportionately impacts a part of the population - in this case, people who are visually impaired or have other disabilities that prevent them from browsing the web.

Now, I’m not saying every person needs to know colour contrast ratios, or WCAG accessibility guidelines, or what tabindex means - but they should have a general understanding that these types of things are important! And similarly, I’m not saying everybody needs to even understand what a neural network is: but they should understand all the strings that come attached with machine learning, in particular those around data sourcing and biases. This level of understanding is digital citizenship, and I think it’s just as important as “regular citizenship” (e.g. knowing how to vote, how taxes work, etc.).

So, what?

The question then needs to be: why aren’t we having more of these conversations now? There are, off the top of my head, lots of reasons:

Some of these problems are institutional, and some of them are cultural. Still, I think all of us can do something.

In particular, I’ll make two kinds of calls to action:

And, if you feel like you’re missing gaps in your digital citizenship, that’s okay! Everybody has these kinds of gaps, and it’s not a mark against the kind of person that you are - instead, take time and try to slowly build up your digital citizenship, bit by bit. If you know me personally, I’d be more than happy to sit down and talk to you about tech, at least in whatever capacity I’m qualified for. And if you don’t know me personally, there are countless resources available online - I encourage you to look!

I realize that I’m not really doing this topic justice - I could write another 20,000 words on this topic. But for now, I wanted to outline the importance of digital citizenship, at the very least so I can reflect on it and think about what I can do to help solve this problem.

Hopefully, we’ll all be digital citizens, together.


Thank you for reading Brief Thoughts on "Tech Literacy". It was written on Jul 31, 2020 by matt. It was 2401 words long, and should be a ~ 13 minute read. It was categorized under impact.