Update March 1, 2023: An expanded (i.e. better) version of this article has been published on Medium at UX Collective. At this point, probably read that one.
In the tech industry we want the next big thing to be here so badly that we jump very quickly to pronouncing its arrival. Driven partly by genuine enthusiasm, partly by inbuilt capitalist incentives, we generate wave after wave of hype. And there is a special flavor of this zeal reserved for technologies that realize that pinnacle of sci-fi fantasy: human-like artificial intelligence.
One problem with the term “artificial intelligence” is that it gets tossed around so carelessly. Google Search has been using natural language processing (NLP) in its search results for a long time. This is what allows you to type in “Why do I get sad when the sun goes down?” instead of a disjointed, keyword-based search like “Sunset sad problem” (Just me?). AI is a marketing term used to generate hype, and the tech media is buying right into it.
I’m not saying AI has no place in technology. But we must be able to distinguish the true value from the hype. It wasn’t too long ago that Microsoft’s Cortana, Amazon’s Alexa, and the Google Assistant were ramping up to change the world. The way people talked back then, it seemed inevitable that these digital assistants would become copilots in our lives, unburdening us of its tedium.
These companies have claimed victory, boasting of high sales, but 5 years on the trend is clear: although useful for certain things, the robots have not changed society in any meaningful way.1 The low adoption isn’t a result of pushback from luddite activists, restrictive government regulation, or fears about evil machines. The issue is one of inertia – there simply aren’t that many reasons to go out of your way to use the thing, as it turns out. (Ranjan Roy over at Margins published a piece just this morning on his growing disenchantment with Amazon’s Alexa.)
Changing human behavior is no trivial feat. There is both an academic discipline and a self-help industry dedicated to understanding its nuances. Sometimes tech companies strike gold and create products compelling enough to work their way into our everyday lives — personal computers, smartphones, and social media — but generally speaking, it takes a lot for people to change their habits. In order for a new technology to catch on, it needs to hit a specific note at just the right pitch, at just the right time. Billions of dollars have been spent trying to figure out how to consistently hit this note, but it remains elusive.
There are a few key reasons, though, why chatbots in particular are challenging and make it hard to support the claim that they are the next big thing in technology.
Text only
With a chat interface, text is presented in a linear way. Imagine holding a pencil in your hand, and trying to discern its color. If you’re staring down the nose of a pencil, it’s going to be difficult. If you can move the pencil around and look at it from various angles, it’s much easier.
Using a chatbot is like staring down the nose of the pencil. When you ask it a question, and get a response in the form of text, you’re getting one piece of information at a time. Instead of typing a query into a search box and getting a list of answers in the form of text and other UI elements like buttons and tabs, you get one text response that may or may not be helpful.
This is why I’m highly skeptical about Bing’s new ChatGPT-powered search. When we’re searching for something on the internet, there’s not necessarily one right answer. For this reason, Google Search has evolved away from simple lists to a much more robust UI with different tabs, expandable cards, and summarizing elements known as knowledge panels. A well-structured UI doesn’t make headlines, but there’s a reason Google Search has dominated for the last 20 years.
Ambiguous input
Another issue with chatbots is that you never know exactly what to say in order to get the response you’re looking for. This is why if you’ve ever used a digital assistant it will offer up suggestions about things it can do. Without those prompts, users have no idea how to interact with it.
Admittedly, ChatGPT helps solve this problem by having an incredibly sophisticated model that can respond very naturalistically to most user-generated messages. But the fact remains: if you’re looking for a nuanced response to a complex answer, it’s frustrating to go back-and-forth with a chatbot until you hit on what you’re looking for. Much better to just get all the information in an instant and sift through it yourself.
Graphical user interfaces were actually invented to solve this exact problem. In the early days of computing, you needed command line interfaces to execute functions. When the people at Xerox PARC invented GUI, they empowered an entire population of non-programmers to use computers by recreating familiar models (e.g. files, folders) on a screen.
Novelty isn’t enough
The main value of a chatbot or any AI is its novelty factor. People love to play around with the thing – it’s cool! But once you realize that the coolness is the main reason people are using it, that becomes a problem for the product’s longevity.
Calling something “artificially intelligent” is hubristic. And the main response to this by the general public is going to be testing the limits of this supposedly intelligent thing, hoping to break it.2 We've already seen journalists create news cycles by doing this. Aside from the harmful rhetoric unfettered chatbots could potentially disseminate, it’s probably not good for business if a main way people are engaging with your product is by trying to prove it doesn’t work very well.
ChatGPT is being heralded as a breakthrough technology, but chatbots are in fact a stale idea. Our attachment to the fantasy of a sentient AI is what makes this a big story, while the real use value is glossed over and the hype train keeps rolling. We need to break the mold of our delusions to unlock technology that’s actually useful. If you want to read a bunch of text that contains moderate amounts of semi-useful information, just subscribe to Long Press.
This is very likely a good thing.