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AI technology (or artificial intelligence technology) is the new big thing in the tech world and is expected to penetrate into different sectors in time to come and as AI continues to advance. The primary reason behind why AI technology may be used extensively in the future is because it would help in making smarter decisions that would align well with business and operational goals, and help achieve faster, more accurate results.

There are scientists at the famous Columbia and Lehigh Universities who have been working on developing on AI technology for many years and have finally created a unique process through that would in error-correcting artificial intelligence based deep learning networks. It has primarily helped the scientists to understand how the artificial intelligence works and how the computer comes to a conclusion when making a decision. The scientists have, therefore, reverse engineered the AI. It has created a roadmap to answer the long-standing “black box” problem well-known in the world of artificial intelligence.

The ‘black box’ problem persisted for long mainly because of the deep learning AI systems having a complicated process of decision-making and conducting large sets of calculations to process millions of data sets at the same time, and ultimately find the answers. It is often beyond the comprehension of the human mind as to why and how the AI chose one solution over the other.

To understand the process as to how the deep learning AI system makes decisions, DeepXplore was created that tricked the system into making mistakes, which helped in identifying the flaws in the advanced AI systems and its decision-making process. The black box method of decision making used by the AI system has been a mystery for researchers so far, and thus, a process is used these days by the scientists as to how deep learning AI systems come up with a solution. The researchers only feed a problem into the AI system that it cannot solve and study the efforts it goes through, which is what helps identify the milestones in its decision-making process.

Error-checking in the deep learning AI system is essential. This allows us to use it widely in many different areas without doubting the standard practices that it operates with. The co-developed of DeepXplore, Kexin Pei of the famous Columbia University said that they aim to improve DeepXplore going forward. He believes that once the decision-making process of the AI system is validated and transparent enough to be trusted, it can be applied without worry in different sectors.

It would also help in ensuring that the outcomes of the AI systems would become more accurate with the help of rigorous error-checking processes. Areas like healthcare, defense, security, transportation, and others can significantly benefit once the decision making logic of the AI system is known and is deemed trustworthy. As of now, artificial intelligence technology is studied with a grain of salt, as there is a sense of mistrust as to what the results can be, and whether it would be biased or not due to some of the effects of AI decision-making process having been surprisingl negative.