In the last decades, many AI projects focused on model efficiency and performance. Results are documented in scientific articles, and the best-performing models are deployed in organizations. Now it is the time to put another important part into our AI systems; responsibility. The algorithms are here to stay and nowadays accessible for everyone with tools like chatGPT, co-pilot, and prompt engineering. Now comes the more challenging part which includes moral consultations, ensuring careful commissioning, and informing the stakeholders. Together, these practices contribute to a responsible and ethical AI landscape. In this blog post, I will describe what responsibility means in AI projects and how to include it in projects using 6 practical steps.
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