In a post-apocalyptic world, shopping carts filled with items sit motionless in aisles, left abandoned by the humans who have mysteriously disappeared. At least that's the cliche scene depicted by sci-fi filmmakers over the past two decades. The audience is left to wonder what happened to force people to stop what they were doing and leave everything behind.
If this past weekend was any indication, Armageddon begins when Target's cash registers shut down.
Armageddon begins when Target's cash registers shut down
We have come to expect technology to just, well, work. It has become so integrated into our everyday lives that we hardly give any thought as to what it actually takes to make the complicated code do the things we want it to. We let technology take the wheel even though it's capable of driving us off a cliff.
The Target Corporation endured two days of checkout chaos. Target lost millions of dollars in revenue but received millions of dollars in bad publicity. Its stock fell. People notice disasters, even minor ones.
While Twitter users described #targetdown as "frustrating," "chaotic," and "Armageddon," imagine the potentially life-altering effects of technology failure in other areas we've given it power:
■ Self-driving cars
■ Analysis in medical data
■ Assessment in academics
■ AI-based legal preparation
■ Algorithms determining online loan approval
■ Algorithms for news feeds
What Happened: Is It the Software or Hardware?
Target said the weekend register outages were two separate issues: on Saturday it was an "internal technology issue," and on Sunday, a problem at one of the data centers belonging to Target's payment vendor NCR. They could mean anything, but Target was quick to point out that it wasn't a security issue or data breach — which was the case in 2013 when a data breach exposed millions of customers' credit and debit card information.
Large system outages that last a long time are usually not software issues, or at least not bugs. Sometimes they are of course, but more often it's either a single point of hardware failure or a cascading systematic failure. So some initial digging to discover whether this is a software thing is the first step.
Solving a hardware problem would be easier. Disaster recovery plans are almost always about physical or virtual infrastructure, but this misses where most of today's real disasters happen: in the software.
An Undiagnosed Software Defect Is Like a Ticking Bomb
Companies that were not software companies 10 years ago are now software companies.
Take Target for example. Traditional brick and mortar retailers are constantly warding off threats from e-commerce (specifically Amazon) and relying on software to give them a leg up. More software systems and more points of sale put them at greater risk of failures.
If one point fails it impacts customer sentiment across the entire chain.
The fact therefore is this: as more infrastructure issues become software, and as more systems become interconnected, the cause of disasters is moving around the stack making them much harder to find.
An undiagnosed software defect is like a ticking time bomb. Now imagine that bomb is in your car.
The AI Car vs. the Poodle
Software autonomy in transportation is a much bigger problem that runs the risk of being deadly.
Imagine a Tesla driving on autopilot and a man walking his poodle across the roadway a few feet ahead. The AI vehicle software detects the man and poodle in the road, but a glitch prevents it from taking any action. The poodle gets run over.
How developers go about solving what went wrong requires the developers to do the painstaking task of recreating the entire scenario: the time of day, the road condition, the weather conditions, the height and weight of both the poodle and the man, the pair's movements across the road. It's nearly impossible.
In real life, investigations are still on-going for two Boeing 737 Max crashes in Indonesia and Ethiopia. The Max software has been implicated in the crashes.
In aviation disasters, investigators always look to recover the black box onboard. But a black box can only tell you that the plane crashed because of a software problem. It can't tell you why the software did what it did to lead up to the crash.
In the Terminator movie franchise, Skynet was the autonomous AI antagonist we never saw.
While the movies are science fiction, the reality today is that AI and machine learning are becoming more common in multiple industries.
Software is making decisions and we need the ability to know what it did, preferably before it asks for your clothes, your boots, and your motorcycle.
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