Is AI Really Artificial?
When the conversation turns to AI—artificial intelligence—most of us are happy to accept what we’re told without question. AI is purported to be the next big thing in software development; an almost mystic technology leveraging complicated algorithms and user input to develop patterns and learn on its own.
For those unfamiliar with it, the idea is a bit hard to conceptualize. But for those who work in the field, there’s nothing mystic about it at all. And when you consider just how much input goes into even a simple AI algorithm, it’s clear that there’s nothing artificial about the intelligence at all.
The Human Element
To illustrate, let’s consider voice assistant tools like Amazon’s Alexa and its Echo family of smart speakers. Smart assistants are a common example of consumer-facing AI, with technology learning our speech patterns and adapting their results based on our previous behaviors. According to Amazon, this is done through “requests to Alexa to train our speech recognition and natural language understanding systems.”
But then you consider newer reports from the company detailing how they, in fact, hire legions of employees to personally comb through this data, cultivating concepts and annotations to be fed back into the system. In other words, this smart speaker intelligence isn’t “artificial” in the sense that it operates on its own. It’s powered by good old-fashioned human effort.
Of course, there are certainly algorithmic components at play here as well. A company like Amazon couldn’t function without some automation behind the scenes. But it’s important to keep things in context, particularly when looking at AI’s growing role in the job landscape.
AI and the Workforce
According to an AI whitepaper by software company Docebo, we’re still not quite to the point where we have to worry about AI replacing jobs. (Based on Amazon’s above admission, it’s not hard to see why.)
Even the biggest tech companies can use AI only in limited capacities. As of now, the role of AI is relegated to logic-based decisions and pattern recognition. Sophisticated as it may be, AI learning still requires humans to properly tag content with metadata that gives the algorithms context. It’s a tedious process that companies don’t like to talk about when espousing the virtues of their AI-enabled platforms.
This isn’t to say that the humans involved aren’t important. Just the opposite. There’s a reason why the job outlook for AI engineers features steady job growth and six figure salaries. As more companies get on board with entry-level machine learning solutions, they’ll need more engineers to put the systems into practice.
Making AI More Natural
AI is thought to be brilliantly complex. And it is—but it has its limitations. Humans still need to steer the ship, and that fact isn’t going away any time soon. But as time goes on, we may reach a point where this input isn’t required. And then, we may see intelligent systems that are truly artificial in every sense of the word.
We’ll be keeping a close eye on these issues at Urgenci—and we’ll keep you updated with any new advancements in AI that may affect your career plans.