Why This Book?
James Luke, David Porter, Padmanabhan Santhanam · 2022
Hundreds of papers on artificial intelligence (AI) algorithms are published in journals and conferences every day. Not a day goes by without something exciting in the media, good or bad, about AI! Big internet companies use the latest machine learning techniques to perform various consumer facing tasks, such as, answer simple questions, recognize images, recommend products, etc. However, the adoption of AI in a typical business enterprise (e.g. retail, banking, insurance, manufacturing, etc.) has been slow due to specific practical challenges: the lack of training data in sufficient quantity and quality, more complex analysis tasks, and the risk in unexpected AI behavior during deployment. In addition, considerable expertise is required to understand the data, relevant business context and the appropriate AI algorithms to support the business-critical tasks. Books currently on the market either describe detailed algorithms and implementation frameworks targeting engineers or provide high-level explanation of AI for broad guidance. In real AI projects, technology capabilities and the business impact are very much intertwined, due to the extreme reliance of data, decision on domain applicability and the expected trust objectives. Our book targets all stakeholders of an AI project and helps to enable successful application of AI to create real business value, irrespective of the underlying AI technology.