Expert Systems: Leveraging AI for Decision Making

Making Intelligence Scalable

As artificial intelligence and machine learning advance rapidly, businesses are finding more opportunities to leverage AI to augment and improve human decision-making. One approach that has been used for decades is the expert system. 

An expert system is a computer system that emulates the decision-making ability of a human expert. It uses knowledge about a specific domain, as well as inference algorithms, to solve complex problems that normally require human expertise.

An expert system consists of two main components:

A knowledge base - This contains the facts and rules about a particular subject domain. For example, for a medical expert system, the knowledge base would contain information about the symptoms and treatment of diseases.

An inference engine - This applies logic and reasoning to the facts in the knowledge base in order to deduce solutions or provide advice. The inference engine asks the user questions, processes the responses, and provides suitable solutions.

Examples :

Expert systems have been used in many areas like medical diagnosis, vehicle troubleshooting, and financial investment advice. For example, a medical expert system can help diagnose a patient's symptoms by asking relevant questions.

Based on the patient's responses, it can determine possible diagnosis and recommend next steps for treatment. The expert system has been pre-programmed with knowledge from medical experts to understand symptoms, diseases, and effective diagnosis/treatment processes.

Another example is an expert system that helps customer service agents troubleshoot and resolve technical issues with a company's products.

The agent interacts with the customer to understand the issue, and the expert system recommends possible solutions, as well as follow-up questions, to efficiently resolve the customer's issue. This helps less experienced agents solve problems faster and with higher consistency.

Expert systems are a useful way to capture knowledge from talented professionals and make it accessible to a wider group of people in an organization. They reduce dependency on scarce experts and increase the overall problem-solving capacity. However, expert systems have limitations - they cannot match human creativity, intuition or common sense reasoning. They are best at optimizing well-defined and repeatable decision flows. Expert systems will continue to be a valuable tool for enhancing business productivity, accelerating innovation, and improving the customer experience. When combined with human input and oversight, they provide the best of both artificial and human intelligence.