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clarify ownership and licensing rights for the AI-generated content and consider whether and how to register any new intellectual property created by the AI system .
Data privacy and security
Generative AI often requires vast amounts of data to train models effectively . Manufacturers need to be aware of the data privacy and security implications associated with collecting , storing , and processing such data , implement appropriate security measures to protect the data from unauthorized access or breaches , and have an action plan should a data breach occur . The standard practice of conducting “ tabletop ” exercises to stress test data breach response plans may be an alien concept for manufacturers .
Liability and accountability
When using generative AI in manufacturing processes , questions may arise regarding liability and accountability . If AI-generated designs or models result in defects , malfunctions , or harm to consumers , it can raise legal issues . Manufacturers should clarify
the responsibility and potential liability for any issues arising from the AI system ’ s outputs . This may involve considering product liability laws , ensuring appropriate disclaimers , or establishing contracts with clear terms and limitations .
Compliance with regulations
Manufacturers must ensure that their use of generative AI complies with applicable regulations and industry standards . Depending on the sector and the products involved , specific regulations may apply , such as safety regulations , industry-specific standards , or labeling requirements . Moreover , the data necessary to fuel generative AI models may require compliance with regulations , such as the European General
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