Understanding the Transformational Nature of AI

AI is expected to be a truly transformational technology. It is showing value in a wide variety of applications, ranging from analyzing medical images to writing legal briefs.

The Role of AI in Manufacturing

In the manufacturing sector, AI is already beginning to play an important role in defect detection, automated production using robots, predictive maintenance, inventory control, supply chain management, and worker training to boost human productivity and improve the efficiency of manufacturing operations.

Identifying Risks Associated with AI

However, AI is not a technology without deficiencies. Therefore, deployment of AI may pose several risks that need to be carefully managed. Unfortunately, most people in the current workforce had no exposure to AI technology when they attended school. This makes it challenging for them to identify, manage, and mitigate risks associated with AI.

A Framework for Managing AI Risks

This article provides a high-level framework for thinking about these risks and what factors need to be considered to make sound decisions regarding the deployment of AI tools and effectively utilize them.

Auditing of Training Data to Understand Vulnerabilities

Recent advances in AI are fueled by data-driven approaches. Basically, an AI system ingests a vast amount of data and learns patterns in the ingested data—and uses this information to perform classification or prediction or generate new content. How well an AI tool—for instance, a defect detection system—performs depends upon the quality of the data used to train it.

Frequently Asked Questions

Q: What are the main risks of deploying AI?
A: The main risks include data quality issues, lack of workforce training, and potential biases in AI decision-making.

Q: How can organizations mitigate these risks?
A: Organizations can mitigate risks by ensuring high-quality training data, providing AI education for employees, and implementing robust auditing processes.

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