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The use of artificial intelligence (AI) in manufacturing has been increasing in recent years, and with good reason. AI can help manufacturers achieve greater efficiency, productivity, and profitability. However, there are also risks associated with the use of AI in manufacturing. This is where the  whitepaper “AI Risk and Resilience in Manufacturing” by Sam Castro, SAP comes in.

The whitepaper provides an overview of the potential risks of using AI in manufacturing and how to mitigate them. One of the key risks highlighted in the whitepaper is the potential for AI to create bias in decision-making about the shopfloor. For example, if AI algorithms are trained on data that is biased towards certain typical situational response, it can lead to discriminatory outcomes. To address this risk, the whitepaper recommends using diverse data sets and regularly monitoring and evaluating AI systems for bias.

Another risk highlighted in the whitepaper is the potential for cybersecurity threats. AI systems can be vulnerable to cyber attacks, and manufacturers need to take steps to protect against these threats. The whitepaper recommends implementing robust cybersecurity measures and regularly testing and updating them.

Overall, the whitepaper provides valuable insights into the risks and opportunities of using AI in manufacturing by an industry leader, Sam Castro of SAP. By following the recommendations outlined in the whitepaper, manufacturers can leverage the power of AI while minimizing the associated risks.