Artificial intelligence is no longer just for science fiction films and novels. Today, intelligence exhibited by machines is a reality of our everyday lives.
People rely on these pocket-sized machines for so many tasks. Smartphones remind users about appointments, give directions to locations, and notify them of traffic along the way – all in real-time, and without any human input.
This is just one example of the presence of AI in people’s lives. And it begs the question: what else will AI take over?
Robots and AI are already taking on some traditional IT jobs, such as network security. Today, algorithms identify potential threats by scanning machine-generated data. As already seen in the manufacturing and agriculture industries, we can get to a much higher scale simply by automating repeatable tasks.
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However, it’s unlikely that robots will take over all of our jobs – at least, not anytime soon. AI is perfectly suited for purpose-built tasks, and even highly sophisticated ones like winning at Chess.
IBM’s Watson defeated legendary Jeopardy champ Ken Jennings, after all. But there really is no true automated counterpart for human creativity and discretion. Those characteristics are part of what makes us sentient beings.
Look at Tay, the AI-driven chatbot released by Microsoft in early 2016. Tay was built to mimic tweets on Twitter – and it did so quite successfully. However, given the ability to learn and adapt to the task, Tay became the worst version of a human counterpart it possibly could. The chatbot’s offensive, odd utterances got it shut down in just a day.
The sentience debate
Today, most people believe our brains are different enough that computers will not gain sentience. But is anybody really sure? What we do know is we could possibly plug technology into our own way of living – our evolution – to the point of no return.
That’s the point where we would effectively become cyborgs – biological life forms augmented by technology. Some people would argue that we’ve already made this transformation, considering how attached we are to our smartphones.
Sentience is a concept we’ve always struggled with. At its simplest, it is the ability to prioritise which problems to work on. Machines can’t do that, and our smartphones certainly can’t do that. We are the ones who direct the machines to come up with answers.
What we are doing is continuing to find problems for AI to solve, and then taking those solutions and implementing them.
AI allows us to focus our talents on the tasks that robots will never be able to take on. However, if AI solutions are going to be widely adopted, the user interface (UI) needs to be simple. The analytics that drive them must be embedded seamlessly into the interfaces we use. And that includes the greatest interface of all: our brains.
According to James Mayes, co-founder of UK-based Mind The Product, “The UI is usually visual analytics of some sort. If those analytics are embedded in an application to help solve specific problems, then AI will help us automate data analytics tasks as much as possible. [AI] is very unlikely to replace the human in the process, though – it is likely [we] will make the final decisions.”
Eventually, we may see more direct interfaces between computers (machines) and our brains. But for now, it’s going to be about having these advanced algorithms that move information into context. AI is a learning technology, but a lot of what machines learn comes from human feedback.
In fact, some of the best analytics are based almost completely on human input. A prime example is Google’s search algorithm. If you click the first link and then immediately go back to the search results page, Google knows that wasn’t the right answer. As more people do the same thing, the ranking of that search result will begin to change.
In the short term, people will say that the robots are winning. But in the long term, we’ll see that robots simply allow us to focus on higher order tasks.
Our cognition is no longer independent from the machines. We learn from the machines, and they learn from us. It’s that cyclical process that creates the cyborg relationship.
The future will not be about the robots. It will be about us: the cyborgs. And artificial intelligence becomes intelligence amplification.
Sourced from Charles Caldwell, VP, solutions engineering and services, Logi Analytics