Experts from around the globe have been searching for the answer to a very vexing question: When will machines exceed human performance in every task? Through a series of surveys, the one conclusion that these experts arrived on was that it would take decades for this to become a reality.
Until that day arrives, we can continue to interact with these machines and engage them in learning. Gradually through these interactions, the machines would move past the stage of immaturity as humans get accustomed to a world where machines are capable of exercising their increased agency.
Counter-intuitively, the automotive industry with its safety and security sensitive context is the most active and visible proving ground we have for how society will interact with these technologies – technologies that will be developed and implemented by corporations and likely regulated by government agencies. A wrinkle worth calling attention to is that government agencies with a responsibility to certify Artificial Intelligence implementations or Machine Learning capabilities are unlikely to know how to do so initially.
Technological developments in machine learning have brought out UIs that have the ability to identify dangerous situations and objects in real time with the highest accuracy. These systems have the potential for reducing human error and by doing so these systems have the potential to save lives in the future.
In any deployment scenario where such a technology would be useful, life and death actions are likely to be taken in response to the probability that the machine assigns. Which brings up the question of what probability would be considered high enough to warrant taking life and death action and who would be responsible for that action.
In the case of autonomous vehicles, a fender bender where a Google car was found to be responsible for an accident was taken as the hypothetical scenario for identifying who would be responsible for an autonomous machine’s actions. However, in this scenario Google was termed as the responsible party and we realized that a fender bender would be the least of our worries. Off late a horde of intelligent pieces have been generated specifying the parameters to govern the autonomous vehicles’ decision making in life and death situations.
When human interactions are included into the loop the complexities increase. When a machine with AI interacts with humans, there may be a change in the behavior of the system based on machine learning, the machine will need to know what to expect and understand the limitations and tendencies of the system. For instance, a car might take over the control of the wheel from the driver at certain points during the drive; like when the driver passes a toll gate and the traffic merges from the right, with a barrier on the left in a narrow lane that leads to a bridge. However, this would only happen in certain scenarios, which highlights the complexities that were specified earlier.
Commercial software companies developing either “off the shelf” machine intelligence, the capacity for that intelligence to evolve through machine learning or for environments where that intelligence can execute control functions based on that intelligence will confront new requirements for reliability with profound implications for liability. These requirements will increase as intelligent machines become more prevalent in society and as businesses come to depend increasingly on systems distinguished by AI and the capacity to learn.
As always, safety and security will need to be top of mind as these systems are deployed into the field of operation. The most recent reminder being the WannaCry cyber-attack which struck diverse connected embedded systems — traffic cameras, ticket kiosks, ATMs.
Artificial intelligence and machine learning are unfolding a new world for which we need to be prepared. There is curiosity in the industry to see how this will continue to unveil and at the same time an anticipation to work with companies involved in these emerging technologies.
By: Mychal McCabe, Vice President, Corporate Marketing at Wind River
