Artificial Intelligence (AI) ethics: 5 questions CIOs should ask
You may not realize it, but artificial intelligence (AI) is already enhancing our lives in a multitude of ways. AI systems already man our call centers, drive our cars, and take orders through kiosks at local fast food restaurants. In the days ahead, AI and machine learning will become a more prominent fixture, disrupting industries and extracting tediousness from our everyday lives. As we hand over larger chunks of our lives to the machines, we need to lift the hood to see what kind of ethics are driving them, and who is defining the rules of the road.
Many CIOs have begun experimenting with AI in areas that may not be very visible to end users, such as automating warehouses. But particularly as CIOs look to expand their use of AI into more customer-facing areas, they must be aware of the ethical questions that need to be answered or risk becoming part of the liability.
Here are five questions in need of answers to uncover how ethics influences AI systems, as well as why CIOs need to be aware of these debates now.
In 2019, Elaine Herzberg was killed crossing the road by an autonomous SUV powered by Uber. The car didn’t recognize the figure as a pedestrian because she wasn’t near a crosswalk. As human drivers, we realize people jaywalk, and we have awareness that people don’t always cross the street where they’re supposed to. Who was liable for this oversight?
An Arizona court found the “safety driver” was negligent, but there will come a day when no one is behind the wheel. In that case, is Uber responsible? Is it lidar technology (which measures distances using laser light and sensors)? Is it a caffeine-infused programmer if they inexplicably forgot to account for jaywalkers?
Even though autonomous automobiles are expected to be much safer than tired, drunk, or distracted drivers, they will kill people. How many? There were 1.16 fatalities per 100 million miles driven in 2017, according to the U.S. Department of Transportation’s National Highway Traffic Safety Administration. In contrast, Waymo logged 10 million miles since it launched in 2009. Without billions of miles under their belt, there is no way of knowing how safe autonomous automobiles will be.
Every death at the hands of an autonomous vehicle is sure to be litigated to pin blame on the responsible party. Does every rideshare and automobile company get drawn into the wave of lawsuits that are sure to come?
Why CIOs should ask this question: With AI, the liability model could shift to the producer rather than the consumer. For those executing these solutions, we need to explore how this potentially impacts our business so we can adequately prepare for it.
Artificial intelligence and machine learning models are being tasked with making critical decisions that have a sizable impact on people’s lives. They can tell us which job candidate to hire. They can hand down a jail sentence to a criminal. They decide which target to bomb. Our problem is we can’t always explain why a decision was made.
Deep learning models work off of neural networks that receive inputs which are synthesized into a result. We can’t easily trace through that web of decisions to find out how the decision was made. It’s a problem when we can’t explain why one inmate received a two-month sentence while another received one year for the same crime.
We fail at this in the real world as racial bias creeps into human decision making in the judicial process. This bias can unknowingly be passed along through our datasets to taint our model. Accountability is key.
Why CIOs should ask this question: Everyone wants to know how software landed on its conclusion – especially when that decision looks wrong. Neural networks make it hard to answer those questions.
