AI’s Learning Curve Clashes With Proprietary Data: Processing Originality Raises Legal, Ethical Questions
Originality is often talked about but difficult to attain. An equation that adds effort and time with patience attempting to battle any final calculation. The marketing of new artificial intelligence (AI) learning technologies promises a spectacular increase in productivity, challenging the limiting factors of effort and time, but perhaps also with a cost to human creativity and innovation. News reports have again highlighted how AI is producing art by using algorithms to study, i.e., arguably copy to some legal analysts, the long-practiced techniques of thousands of artists in order to then generate art of its “own.” Fundamentally, AI is racing to process all of this individual creative work, and yet using this type of technology could also put it on a fast-track collision course with copyright infringement and intellectual property laws.
These large reams of data, whether it be the styles of different artists, the unique voices of writers, the complex nuances of computer code, or even the scientific reasoning of researchers, are being processed at a stunning rate to essentially achieve what could conceivably be termed synthesized productivity and ultimately one might argue synthesized creativity. No longer a wholly human construct but rather manufactured and then authenticated by a machine, or at least a fenced in or potentially undisciplined notion of what that means to the artificial intelligence. In short, synthesizing data to deliberately produce a result may someday altogether alter the definition of what is now understood to be authentic and previously uncharted human innovation.