When we think of black boxes, we usually think of data loggers mainly used in aircraft. However, the AI black box is a completely different concept.
The AI black box is not a physical device. The AI Black Box is a virtual entity. They exist only in algorithms, data, and computational systems.
AI black box is a concept that refers to autonomous decision making in AI systems. Let’s take a detailed look at AI black boxes, how they work, and the concerns surrounding them.
What is an AI black box?
An AI black box is an independent system that can make decisions without explaining how these decisions are reached. That’s a simple definition of an AI black box.
However, this definition encapsulates the essence of artificial intelligence. AI systems are designed to learn, analyze data, and make decisions based on the patterns and correlations they learn. However, the definition also encapsulates the concerns surrounding AI.
We’ll put those concerns aside for a moment when we look at how AI black boxes work.
How does the AI black box work?
There are 3 main built-in components to create AI black box. These combine to create the framework that constitutes a black box:
Machine Learning Algorithms: Deep Learning algorithms work by allowing AI to learn from data, identify patterns, and make decisions or predictions based on those patterns.
Computing power: The AI black box needs significant computing power to process the large amount of data required.
Data: Huge troves of data, sometimes up to trillions of words, are required to support decision making.
The principle is that AI black boxes use these 3 factors to recognize patterns and make decisions based on them. AI black boxes can also be trained by fine-tuning algorithms and customizing data.
Systems are exposed to relevant datasets and example queries during training to optimize their performance. This can be focused on metrics like efficiency and accuracy.
After completing the training phase, the black boxes can be deployed to make independent decisions based on learned algorithms and patterns. However, the lack of transparency about how decisions are made is one of the main concerns surrounding AI black boxes.
