The author makes an important point, something we relayed in a more homely fashion in a 2017 post:
"When Google was training its self-driving car on the streets of Mountain View, California, the car rounded a corner and encountered a woman in a wheelchair, waving a broom, chasing a duck. The car hadn’t encountered this before so it stopped and waited."
From The National Interest, March 13:
If neural networks and machine learning remain the dominant AI guiding technologies, the operational usefulness of AI in battle will be rather limited.
It’s widely presumed that artificial intelligence (AI) will play a dominant role in future wars. Maybe not Skynet and Terminator-level stuff, but plenty of independent hunter-killer vehicles blasting each other and the rest of us.
However, the way the future unfolds might be nothing like that. AI developments increasingly led by machine learning-enabled technologies, seem to be going in another direction.
The History of Artificial Thinking
AI is a fairly plastic term. Its meaning has shifted over time, reflecting changes in both our understanding of what intelligence is and in the technology available to mimic this. Today, AI is mostly used to describe a broad range of technologies that allow computers to enhance, supplement or replace human decision-making. Machine learning is just one of this family of technologies.
Since the adoption of modern computers, terms such as “artificial intelligence” have conjured-up images like those of the HAL 9000 computer from the movie 2001: A Space Odyssey. While computers that think and function with complete autonomy from human direction are still a ways off, machines with the capacity for a dramatically increased capacity to evaluate information, make choices and act on decisions have made remarkable progress over the last decade and established the foundation for the emerging technologies of machine learning. These technologies have broad applications in many fields, including defense and national security.
Machine learning, developing processes that mimic human brain functioning, is patterned on how brain cells work in a neural network. This approach could be described as “data-driven,” providing inputs that became the basis for establishing cause and effect relationships, in a similar manner to how human brains create knowledge and make judgments....
....MUCH MORE
