How low-code machine learning can power responsible AI

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. The rapid technical progress and widespread adoption of artificial intelligence (AI)-based products and workflows are influencing many aspects of human and business activities across banking, healthcare, advertising and many more industries. Although the accuracy of AI models is undoubtedly the most important factor to consider while deploying AI-based products, there is an urgent need to understand how AI can be designed to operate responsibly. Responsible AI is a framework that any organization developing software needs to adopt to build customer trust in the transparency, accountability, fairness and security of any deployed AI solutions. At the same time, a key aspect to make AI responsible is to have a development pipeline that can promote the reproducibility of results and manage the lineage of data and ML models.