Lessons Learned from Artificial Stupidity

Artificial intelligence is poised to be the next big revolution in healthcare. Are you ready?

There isn’t a day that goes by without a story in the news on artificial intelligence, or AI, as we’ve come to know it. From Amazon’s Alexa and Samsung’s Bixby, to Apple’s Siri and IBM’s Watson, we are experiencing a sea change in the integration of AI into our daily lives.  

We are also learning about AI “bots” that process information thousands of times faster than humans.

We’re learning about autonomous taxis. While this may seem like science fiction, be assured that they’ll be coming to a highway near you…literally. Self-driving taxis will be able to pick you up and take you to the theater or wherever you need to go, and they may promise to get your there for less than you would spend on Uber – or even less than you would spend driving yourself.

Perhaps the most interesting and useful AI developments are occurring in the business world.

For example, consider natural language processing, or NLP, which is the ability to recognize, interpret, and synthesize speech and text. And then there’s machine learning. In machine learning, algorithms and in turn help software applications become more accurate in predicting outcomes, all without programming interaction by humans.

One of my favorite artificial intelligence types is something called “artificial stupidity.” Yes, you read that right. Artificial stupidity is AI that intentionally makes suboptimal decisions. In a chess game, for example, a game bot can make the decision to match the current skill level of human players or to play worse than their human counterparts, all in the name of making the game more accessible and enjoyable to users.

The AI market is projected to reach $36 billion by 2025, and we can find examples in just about every industry imaginable.

In healthcare, there are many AI topics to watch. One of the most talked-about of late is IBM’s Watson for Oncology. Watson mines a patient’s clinical notes, reports, and test results, and combines this with external research to suggest personalized, evidence-based treatment options. Watson also helps to scale knowledge in a way never before imagined.

IBM has launched another project to watch called Medical Sieve: a cognitive assistant designed to assist in clinical decision-making in radiology and cardiology.

And then there’s the role of AI in cybersecurity. Artificial intelligence helps cybersecurity professionals proactively identify behavior patterns at multiple network data points, enabling them to spend more time vetting threats and less time dealing with consequences of security breaches.

Clinical documentation is another important activity for which AI is demonstrating value. Computer-assisted documentation tools help physicians ensure that point-of-care documentation is complete and accurately reflects each patient’s complexity, as well as the care provided.

And of course, there is computer-assisted coding, or CAC. This has not developed as much traction as the industry anticipated, so it may just be a matter of time before CAC is replaced by automated coding within electronic health records (EHRs), using machine learning, cognitive bots, and other AI technologies.

Artificial intelligence is changing our lives – at home, at work, and within our healthcare community. Don’t be surprised when you see news stories about artificial intelligence for many years to come.

And if you don’t believe me, just ask Alexa – she’ll tell you.