You probably interact with artificial intelligence (AI) on a daily basis and don’t even realize it.
Many people still associate AI with science-fiction dystopias, but that characterization is waning as AI develops and becomes more commonplace in our daily lives. Today, artificial intelligence is a household name – and sometimes even a household presence (hi, Alexa!).
While acceptance of AI in mainstream society is a new phenomenon, it is not a new concept. The modern field of AI came into existence in 1956, but it took decades of work to make significant progress toward developing an AI system and making it a technological reality.
In business, artificial intelligence has a wide range of uses. In fact, most of us interact with AI in some form or another daily. From the mundane to the breathtaking, artificial intelligence is already disrupting virtually every business process in every industry. As AI technologies proliferate, they are becoming imperative to maintain a competitive edge.
What is AI?
Before examining how AI technologies are impacting the business world, it’s important to define the term. “Artificial intelligence” is a broad term that refers to any type of computer software that engages in humanlike activities – including learning, planning and problem-solving. Calling specific applications “artificial intelligence” is like calling a car a “vehicle” – it’s technically correct, but it doesn’t cover any of the specifics. To understand what type of AI is predominant in business, we have to dig deeper.
Machine learning
Machine learning is one of the most common types of AI in development for business purposes today. Machine learning is primarily used to process large amounts of data quickly. These types of AIs are algorithms that appear to “learn” over time.
If you feed a machine-learning algorithm more data its modeling should improve. Machine learning is useful for putting vast troves of data – increasingly captured by connected devices and the Internet of Things – into a digestible context for humans.
For example, if you manage a manufacturing plant, your machinery is likely hooked up to the network. Connected devices feed a constant stream of data about functionality, production and more to a central location. Unfortunately, it’s too much data for a human to ever sift through; and even if they could, they would likely miss most of the patterns.
Machine learning can rapidly analyze the data as it comes in, identifying patterns and anomalies. If a machine in the manufacturing plant is working at a reduced capacity, a machine-learning algorithm can catch it and notify decision-makers that it’s time to dispatch a preventive maintenance team.
But machine learning is also a relatively broad category. The development of artificial neural networks – an interconnected web of artificial intelligence “nodes” – has given rise to what is known as deep learning.
What does AI mean for the worker?
With all these new AI uses comes the daunting question of whether machines will force humans out of work. The jury is still out: Some experts vehemently deny that AI will automate so many jobs that millions of people find themselves unemployed, while other experts see it as a pressing problem.
“The structure of the workforce is changing, but I don’t think artificial intelligence is essentially replacing jobs,” Rahnama said. “It allows us to really create a knowledge-based economy and leverage that to create better automation for a better form of life. It might be a little bit theoretical, but I think if you have to worry about artificial intelligence and robots replacing our jobs, it’s probably algorithms replacing white-collar jobs such as business analysts, hedge fund managers and lawyers.”
While there is still some debate on how, exactly, the rise of artificial intelligence will change the workforce, experts agree there are some trends we can expect to see.
Will AI create jobs?
Some experts believe that, as AI is integrated into the workforce, it will actually create more jobs – at least in the short term.
Wilson said the shift toward AI-based systems will likely cause the economy to add jobs that facilitate the transition.
“Artificial intelligence will create more wealth than it destroys,” he said, “but it will not be equitably distributed, especially at first. The changes will be subliminally felt and not overt. A tax accountant won’t one day receive a pink slip and meet the robot that is now going to sit at her desk. Rather, the next time the tax accountant applies for a job, it will be a bit harder to find one.”
Wilson said he anticipates that AI in the workplace will fragment long-standing workflows, creating many human jobs to integrate those workflows.
What about after the transition?
First and foremost, this is a transition that will take years – if not decades – across different sectors of the workforce. So, these projections are harder to identify, but some other experts like Husain are worried that once AI becomes ubiquitous, those additional jobs (and the ones that already existed) may start to dwindle.
Because of this, Husain said he wonders where those workers will go in the long term. “In the past, there were opportunities to move from farming to manufacturing to services. Now, that’s not the case. Why? The industry has been completely robotized, and we see that automation makes more sense economically.”
Husain pointed to self-driving trucks and AI concierges like Siri and Cortana as examples, stating that as these technologies improve, widespread use could eliminate as many as 8 million jobs in the U.S. alone.
“When all these jobs start going away, we need to ask, ‘What is it that makes us productive? What does productivity mean?'” he added. “Now we’re confronting the changing reality and questioning society’s underlying assumptions. We must really think about this and decide what makes us productive and what is the value of people in society. We need to have this debate and have it quickly because the technology won’t wait for us.”
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