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Daimler AG Adopts Principles for Dealing With AI

Auto News - Published on Wed, 11 Sep 2019

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Daimler AG is the first automotive manufacturer to have its own principles for artificial intelligence. Responsible use, explainability, protection of privacy as well as safety and reliability as guiding principles according to which the company develops and uses AI. Renata Jungo Brungger Member of the Board of Management of Daimler AG for Integrity and Legal Affairs said that "Our four principles for dealing with artificial intelligence create a clearly defined scope for action. We thus make it clear that the human being will remain the pacemaker of technical progress."

An inter-disciplinary team that included experts from Development, IT and Legal Affairs developed the four principles for dealing with artificial intelligence at Daimler, so as to take into account technical, legal and social aspects.

Behind the principle of "Responsible use" is the maxim that the opportunities and effects of AI must be carefully weighed up. The use of AI at Daimler is therefore preceded by a transparent assessment process: Will products, services and processes actually become faster and more efficient with AI? What are the benefits for different target groups? These questions are examined during a risk-based technology impact assessment. Responsible use of AI also means creating a high-quality, representative database. This means that the data used must take the factors relevant to the application into account. This fosters fairness and inclusion.

The principle of "Explainability" creates the transparency necessary to have trust in new technologies. Customers and employees of Daimler AG must be able to recognise when they come into contact with AI – eg by information in the General Terms & Conditions, or by direct messages in the system. The principle also stands for comprehensibility: it must be clear which parameters are included in data analyses. This makes it easier to evaluate the results of AI-based calculations, and avoid unwanted bias.

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Posted By : Mohan Sharma on Wed, 11 Sep 2019
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