There's an interesting trend in technology adoption that seems to repeat itself all the time, but you don't notice it until you stop to take a look. According to a recent survey by Adobe, 54% of US consumers now say voice assistants (such as Siri, Alexa, and Cortana) work well, with another 41% saying they work "well." And only 5% say they do poorly. . Compare that to a similar Adobe mid-2017 survey, which found that only 37 percent of users thought voice assistants did a good job, and 37 percent rated them "not good" or "terrible." stated.
Technically, Google Voice Search has been around for almost a decade, but it's only been in the last few years that we've started using it on a regular basis. Voice assistants like Siri and Cortana were initially derided and little used, largely because they didn't consistently recognize voice patterns, but in part, because users found the user interface difficult. we're not ready for dramatic change. Today, those same speech recognition programs have error rates that rival those of human transcribers.
The pace here has been interesting and says a lot about our relationship with technology.
Skepticism and acceptance
The normative technology acceptance model suggests that consumers, seeing a new technology in action for the first time, will base their feedback on the product's perceived usefulness (ie, how much it helps them in their daily lives). does), and ease of use.
It is useful but difficult to predict consumer behavior patterns. Perceived utility, for example, is not just how much time or effort the technology saves, but how easy it is to see those benefits. Perceived ease of use depends not only on how easy it is to use in the end but also on how easy it is to learn and how different it is from previous tools.
We must also consider the fact that most new technologies are minimally viable products. They are not fully polished final designs, but rather offer an entry point into a new technological paradigm. Ultimately, this is a good thing; If we always waited until new technologies were perfected before distributing them, we would either never make progress or base our progress on bad data.
As a result of these concepts and practices, most technologies that fundamentally change our lives in some way, even if that change is an improvement, are initially met with skepticism. Consumers see a product that:
- This is contrary to your habit.
- It does not offer a flawless experience.
- It is hard to learn.
- It doesn't seem to add much value to their lives.
Voice assistants weren't good at recognizing human speech and thus weren't much of a time saver compared to typed searches, which users were already used to and were good at.
However, the technology attracted enough attention that designers and engineers continued to work on it. They collected more data, refined their approach, and implemented iteration after iteration until we finally reached the low error rate and widespread consumer acceptance we see today: two-thirds More than 100,000 American adults now use a voice assistant on a monthly basis.
But if you ask someone for their perspective on how far voice search has come, they'll be inclined to remind you that voice search has been around for years. It has worked its way to becoming such an integral part of our daily lives that it's hard to remember a time when assistants were clumsy and unreliable.
Main road
So what does this mean for us as technology users, and what should technology developers get out of it?
- New technology is almost always met with skepticism. No matter how revolutionary or innovative technology is, if it is different from what people are used to, they will be skeptical and underestimate its value.
- Consistency drives adoption. The continued availability of technology will inevitably lead to consumer adoption. In this case, as more friends and family use voice search, and as more voice assistants are introduced, you'll eventually become so used to voice search that your initial reluctance to accept it goes away. goes
- Gradual improvement is better but less noticeable. The best way to update technology is slowly, with small updates over time. This leads to a more consistent path to improvement, is less risky, and allows you to rely more on objective data. Unfortunately, this method is lacking; Some big breakthroughs mean customers won't appreciate your progress as much and may better remember the early days of your technology.
The next time you see an emerging technology fail to live up to its promise, or the next time you think about developing the next big technological innovation, remember what happened to voice search. Technology that was laughed at and ignored for years is now something more than half of us don't want to live without.
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