The Time is Now: AI for Everyone

CIOs have named artificial intelligence as the most disruptive technology that will transform their businesses and business models, according to Gartner's annual survey of these top technology executives.

But just because many people agree that it will be disruptive doesn't mean everybody understands what it can do. Indeed, at the most recent Gartner Symposium in October 2018, analysts were advising CIOs to spend time resetting their top executive leadership's expectations about what they can expect from their AI initiatives.

Educating the non-technical staff, especially top executives, about the potential and capabilities and requirements of a technology has become an important job of the IT leadership. You can't really set strategy unless you know what a particular technology can do.

That's the impetus behind a new Coursera course, AI for Everyone, that made its debut at the beginning of March on the online educational platform. Taught by Andrew Ng, Coursera co-founder, Stanford Adjunct Professor of Computer Science, and a former executive with Baidu and Google, Coursera is pitching the 7-hour course as one that covers the key AI concepts, provides help with spotting opportunities to apply AI in your own organization, offers guidance on understanding how AI is impacting society.

Does the arrival of an AI-for-Everyone course mark an inflection point on our knowledge and acceptance of artificial intelligence as a society? Maybe. Consider that Salesforce.com CEO Marc Benioff declared that AI is a new human right. "Those who have the artificial intelligence will be smarter, will be healthier, will be richer, and of course, you've seen their warfare will be significantly more advanced," he said during a press conference at the World Economic Forum in Davos. "That is why it is critical that we look now at what we are doing with this amazing technology."

The Coursera course offers some specific help geared towards the non-technical staff -- both leadership and individual contributors -- in understanding just what AI is and what it is not, and provides definitions of some of the buzz words out there, concrete examples of how AI can be applied in business, and a look at a few of the mistakes executives make when it comes to investing in AI.

For instance, Ng advises against spending multiple years building the perfect data sets before you get started building your AI team.

"Because often, the AI team can give feedback to your IT team on what types of data to collect and what types of IT infrastructure to keep on building," Ng said in the What is Data video from week one of the course. For instance, the AI team might tell you that you should collect data from a piece of manufacturing equipment once every minute instead of once every 10 minutes. If you wait to collect all the data first, you will miss out on the feedback loop and may end up missing the collection of important data or end up collecting more data than you need.

"There's often this interplay of this back and forth between IT and AI teams and my advice is usually try to get the feedback from AI earlier, because it can help you guide the development of your IT infrastructure."

The second big misuse of data is in believing all of it that you have is valuable. More data is usually better than less data, Ng said.

"But I wouldn't take it for granted that just because you have many terabytes or gigabytes of data that an AI team can actually make it valuable." In one extreme case, Ng said, one company acquired a whole string of other companies, thinking that their data would be valuable, but a few years later the engineers have not yet figured out how to turn all that data into value.

"So sometimes it works, and sometimes it doesn't," Ng said. But don't "… overinvest in just acquiring data for the sake of data unless you're also getting an AI team to take a look at it."

The course also touches on what Ng calls the AI Transformation Playbook, which is also something offered by his consulting company, Landing AI.

Whether it marks an inflection point for AI or not, the course could be a valuable tool for educating non-technical professionals about AI and its capabilities. The price is right, too -- free to audit, and $49 if you want to take the quizzes and get the certificate.

The course includes definitions, explanations of terms, common pitfalls, how to identify AI projects, discrimination and bias, adversarial attacks on AI, adverse uses of AI, AI and jobs, and more.

For more on the state of AI, read these articles:

AI as a Human Right

The Future of AI in America: What All Leaders Should Consider

Planning a Trustworthy Citizen Data Science Initiative

Take A Deeper Look at Deep Learning