Inside the Black Box: When AI Knows More Than Its Creators
Artificial intelligence is influencing not only the process of loaning people money but also the process of diagnosing patients with various illnesses, but in most cases, these systems are not fully understood by their authors either. It is a black box phenomenon of AI whereby complex models are used to provide results without transparent reasoning routes. On the one hand, it has been better in terms of accuracy, but on the other hand, transparency has not been able to keep pace, which itself casts serious doubts on the issues of trust and accountability.
The more the AI systems become autonomous, the more the black box is relied upon in AI. Deep learning models can process millions of data points, whose logic is usually non-obvious. This is dangerous when matters of human lives are involved, like recruitment, law enforcement or health care, whereby prejudice or fallacy may remain unconscious.
Why the Black Box Problem Is Becoming Harder to Ignore
Regulators, researchers and businesses are currently driving to explainable AI structures that achieve average performance and transparency. In the absence of a better understanding, the black box in AI poses a challenge to undermine human control and moral governance. Finding the balance between strong and comprehensible AI systems is the struggle to be made, before the control falls further out of reach of humans.
