“The problem with the future is that when it shows up, I’m always older.” — Unknown
The future got here a while ago. But thanks to IBM’s Watson, we can’t ignore it any more.
Some background: IBM is turning Watson into a diagnostic support tool. The FDA wants to treat it as a medical device. IBM disputes that categorization and is spending sums that are, shall we say, significant lobbying to avoid this regulatory roadblock.
Fortunately, KJR’s crack medical policy division has come up with a solution that should be satisfactory to all concerned.
IBM has created an AI diagnostician, and claims it isn’t a medical device? Fair enough. Force-fitting it into a medical-device regulatory framework is force-fitting a hexagonal peg into an elliptical hole.
But we don’t need new legislation to cover this. We already know how to certify diagnosticians. They complete medical school and have to pass tests covering each course in the curriculum. They then go through three years of residency before being allowed to hang out their shingle as a medical doctor.
Why should Watson be allowed to bypass any of this, just because it isn’t built out of flesh and blood? The solution is straightforward: Each Watson sold must first pass all medical school exams, then go through three years of as near a replica of actual medical residency as can be devised.
Problem solved. You’re welcome.
But of course, like most solutions to most problems, this solution raises new problems of its own.
Imagine you’re a physician, in a practice that’s acquired a Watson of its very own. Watson provides a diagnosis and recommends a treatment for one of your patients, and you disagree.
You have two choices — allow Watson’s judgment to override your own, or override Watson’s judgment with your own.
And your patient later dies. Not only is your conscience torturing you, the absence of tort reform is torturing you with a malpractice action.
It doesn’t matter whether you followed Watson’s judgment or your own. You’ll be susceptible to the tort and torture whether you allowed Watson to override your good judgment, or you overrode Watson’s.
It’s Hobson’s choice. The question for medical ethicians is how to deal with this unresolvable question, and before they even start we know they’ll never come up with a fully satisfactory answer.
We can all thank our lucky stars we don’t have to deal with ethical questions this thorny.
Only, when we thank them we’ll be fooling ourselves, because we’re all dealing with this situation already. It’s the situation we face when our GPS gives us directions we don’t think make sense. We have to decide whether our GPS is routing us strangely because it knows more than we do about the traffic conditions ahead, or whether there’s a glitch in the algorithm and it’s pointing us in the wrong direction.
Not as ethically interesting? If you’re meeting someone for drinks after work, no it isn’t. But what if you’re driving someone to the hospital because they’re in intense pain and the cause might be grave?
It’s the physician and Watson, up close and personal, in real time.
It’s a question of who or what’s in charge, human beings or information technology. It’s a question with a simple answer: Humans, of course, both because we program the computers and because we’re ultimately responsible for the decisions, too.
Except that answer doesn’t always work. A computer-controlled traffic light is an easy-to-understand and inarguable example, because overriding the computer’s recommended course of action (stop before entering the intersection) isn’t merely a violation of traffic laws. It’s a decision with potentially lethal consequences.
When it comes to traffic lights we obey the machine.
The world of commerce is hardly immune from these challenges, starting with the requirement that humans are sometimes required to obey computers here, too. That’s what you face if you work in a call center. A computer (the ACD — automated call distributor) directs a call to your phone. What do you do? You answer it. You, the human, obey the ACD, a computer.
Or, you’re a manager, responsible for a decision that could be influenced by some form of automated support, whether it’s an old-fashioned Decision Support System, a no-longer-fashionable data warehouse, or ultrafashionable Hadoop-driven big-data analytics.
If the analytics indicate a course of action that doesn’t seem right to you, how is that different from the physician deciding about Watson’s diagnosis and recommended treatment?
There are no answers that are both easy and useful, and the questions are becoming more pressing as each day goes by.
Your phone is ringing. It’s the future, calling to let you know it just got into town and would like to meet you for drinks.
Time to get out the GPS.