In the field of autonomous driving, the decision as to whether an invention should be patented or kept undisclosed as a trade secret is increasingly becoming a key factor for future market success. The reason: the employees in this highly innovative, very dynamic and more converging segment of the automotive and digital industries are not only excellently trained in the field of algorithms and machine learning, but also sophisticated, mobile and interconnected.
In autonomous driving, employees and experts from external companies from different industries, technology fields and economic sectors have to collaborate. However, it is difficult to work together if no or too little information is passed on. It is therefore important for management to identify, categorize and evaluate all information. Only then can it decide what should be kept secret and what should be passed on. This is not only about technology, but also about platforms, solutions, customer experiences, organizational structures, segmentation, or value chains. In our projects, we therefore work with software tools that better categorize, evaluate and manage trade secrets.
Driverless cars are always an academic field with depth. Many experts in autonomous driving are academically interested and want to discuss their work results in events and forums or publish them in scientific journals. The risk that employees inadvertently disclose critical knowledge through their publications and statements is very high. Companies therefore need a process that allows employees to publish in scientific journals while reducing the risk of disclosure. Conversely, companies can quickly find themselves in a situation in which they have unintentionally incorporated the business secrets of another company into a project through the knowledge brought in by employees.
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