ABSTRACT
Buttressing the “intelligent” aspect of AI, advances in technology have led to the development of machine learning to make predictions or decision choices without being explicitly programmed to accomplish a task. With machine learning, algorithms and statistical models permit systems to “learn” from data, and make decisions, relying on patterns and inference instead of specific instructions.
The biggest ethical challenge confronting global society can be shaped by better understanding six dominant ethical algorithmic pathways as applied to AI. To work within the global society, AI has to be aware of the nuances and particulars of specific societies as they relate to the six ethical positions. An AI system in a high surveillance country might differ from its equivalents in other parts of the world. Then, of course, there is ethical divide within societies.
The AI policy landscape is still in its infancy. Many policymakers see this moment as the beginning of an AI arms race in need of public funding and deregulation. Others are calling for comprehensive guidelines that address ethical algorithms, workforce retraining, public safety, antitrust, and transparency.
