Artificial Intelligence (AI) is becoming increasingly adept at making decisions, but its inability to explain its reasoning is a significant hurdle. This lack of transparency, known as the ‘black box’ problem, is a major issue for the adoption of AI in fields like medicine and law, where explanations are crucial. The Defense Advanced Research Projects Agency (DARPA) in the United States is addressing this issue with a programme called ‘Explainable AI’ (XAI), aimed at developing AI systems that can translate their complex processes into something humans can understand.
The XAI programme is tackling this issue by breaking down AI’s decision-making process into steps that are comprehensible to humans. This involves creating models that can explain their reasoning, a task that is proving to be a significant challenge. The programme is also exploring the idea of ‘psychological transparency’, where AI explains its decisions in a way that aligns with how humans think.
The ability of AI to explain itself will be critical in building trust and understanding between humans and machines. It will also be essential for the legal and ethical implications of AI’s decisions. Despite the challenges, the XAI programme’s efforts represent a significant step towards a future where AI can be both powerful and understandable.
Go to source article: https://www.nytimes.com/2017/11/21/magazine/can-ai-be-taught-to-explain-itself.html