Artificial intelligence (AI) holds a lot of promise when it comes to almost every facet of how businesses are run. Global spending on AI is rising with no signs of slowing down — IDC estimates that organizations will invest $35.8 billion in AI systems this year. That’s an increase of 44% from 2018. With all the fanfare, it’s easy to get lost in the noise and excitement — and with all of the vendors out there touting their various AI-based solutions, it’s also easy to get confused about which is which and what does what.
So, how do you muddle through the noise and make sure you really understand AI? Here are five things I believe you should be aware of when it comes to providing an AI solution or evaluating one for your business.
Because AI is a trending technology that many believe holds great potential, vendors will sometimes claim they have AI-enabled capabilities when they really don’t. There’s no ruling body that defines what “AI” means — vendors are free to use it however they want. The same thing happened when the cloud entered the market, which caused the term “cloud washing” to emerge for products and services that were hyped as cloud-based but weren’t actually in the cloud. The same goes for “greenwashing” where companies lead consumers to believe they follow environmental best practices but really don’t.
Today’s “AI washing” makes it harder to tell truth from fiction. A Gartner press release from 2017 warned that AI washing is creating confusion and obscuring the technology’s real benefits. Many vendors are focused on the goal of “simply marketing their products as AI-based rather than focusing first on identifying the needs, potential uses, and the business value to customers,” according to Gartner research vice president Jim Hare.
It’s important to be clear about what AI is and about how a vendor is using the term. For instance, AI isn’t the same thing as automation. Automation allows process scripts to take care of previously manual, repetitive tasks, but the system isn’t learning and evolving. It’s just doing what it’s told to do. AI’s goal is generally to mimic human behavior and learn as it goes to become better at the tasks assigned to it over time.
2. Potential For Misuse
As with anything, AI can be used for nefarious purposes. A tool is only as “good” or “bad” as the hands that hold it. There are those who seek to use AI to control their citizenry via a nationwide network of facial recognition cameras (paywall) or build autonomous weapons, which I would consider bad applications. Fortunately, many hands have already found beneficial uses for AI, including accurate medical diagnoses, new cancer treatment approaches and language translation.
Another positive sign is that governments are working toward regulation and accountability. France and Canada announced plans to start the International Panel on AI to explore “AI issues and best practices,” and the U.S. Pentagon asked the Defense Innovation Board to create an ethical framework for using AI in warfare.
Ultimately, I believe AI is the best hope for overcoming the potential misuse of AI. For instance, much has been made of the inherent bias that keeps showing up in AI systems. IBM, for example, recently announced its automated bias-detection solutions. Since humanity can’t put the AI genie back in the bottle, we can devise good AI systems to help countermand its potential negative applications.
3. The Idea That AI Will Take People’s Jobs
Yes, it will eliminate some jobs — typically low-level and repetitive work — but it will likely create jobs, too. Gartner forecasted that AI will create more jobs than it eliminates by 2020, with a net increase of over two million jobs in 2025.
I believe AI also will take on tasks which the human brain is simply incapable of handling. AI can be trained to analyze vast data sets to gain insights that could elude the human mind. This could be particularly helpful in the creation of new drugs, saving time, effort and millions of dollars on development and clinical trials. I also believe AI could be useful for finding unique biological markers that enable individual-specific treatment. That said, this doesn’t mean that human oversight and involvement isn’t required.
4. The Idea That AI Will Change The Way People Think
AI probably won’t cause humans to rely on machines to do their jobs and make their decisions. AI, however well-developed it gets, can never replace the complexities of the human brain. That makes it even less reliable than our brains — meaning that AI compliments, rather than replaces, humans.
It’s unlikely that AI will yield flawless results. For instance, AI-powered speech transcriptions still serve up hilarious errors. Facial recognition programs still misidentify people. We can think of AI as an assistant to final human judgment, but a human must still be in the loop.
5. Lack Of Education
Here’s what I think is the biggest problem with AI in today’s world: We just don’t have enough people who are educated on how it works and how to leverage it. I think we’re staring right into the face of a looming skills gap.
For instance, an O’Reilly report on AI (via Information Age) found that over half of respondents felt their organizations needed machine learning experts and data scientists (although O’Reilly is an e-learning provider). And according to Deloitte, “Since nearly every major company is actively looking for data science talent, the demand has rapidly outpaced the supply of people with required skills.” In the United States alone, McKinsey projected (via Deloitte) that there will be a shortfall of 250,000 data scientists by 2024.
Students need to be learning about AI starting as early as middle school. Our children need to be equipped to handle the inevitable future that AI will bring. Otherwise, the shortage of workers who can actually leverage these technologies will expand. And that’s not good for anyone.
Act With Intelligence
Between the extremes of marketing hype and visions of Armageddon lies the truth of AI. Yes, there’s potential for misuse, but the majority of applications are and will be beneficial. You can’t ignore AI; organizations that find appropriate use cases for AI may get started sooner and find success sooner than their laggard competitors.