Dr. Satyandra K. Gupta: Co-Founder, Chief Scientist, GrayMatter Robotics; Smith Int’l Professor & Dir. CAM USC; Fellow ASME, IEEE, SME, SMA. Read SK Gupta's full executive profile here.
AI will be a truly transformational technology. It shows value in a wide variety of applications, ranging from analyzing medical images to writing legal briefs. AI is already beginning to play an important role in defect detection, automated production, predictive maintenance, inventory control, supply chain management and worker training.
Most users in the manufacturing sector do not need to develop AI technology themselves. Most of them do not need to master coding skills or develop in-depth knowledge about the latest AI technologies. However, they need basic AI literacy to make sound decisions regarding the deployment of AI tools and effectively utilize them.How well the AI tool will perform will depend upon the data used to train the AI tool.
How can they do this? First, understand where data used in training came from. Second, conduct data quality assessments to identify any issues or anomalies in the dataset. And finally, identify irrelevant features that may not contribute to the system's performance.People working with AI tools need to have a basic understanding of how AI algorithms and models function. Grasping the logic behind popular algorithms can aid in a better understanding of their results.
People working with AI tools should be able to understand, identify and mitigate concerns that arise due to privacy concerns. If an AI tool is continuously collecting data about people and customers, then people should have adequate training to obtain informed consent for data collection and usage.Data stored in conjunction with AI tools always comes with risk. Unauthorized access to this data can lead to serious problems.
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