Digging deeper, today’s artificial intelligence has three key ingredients: data, recipes and optimizations. The data is the foundation and the basis for learning. Just like we as humans learn from books, movies, teachers, etc. — all of which are sources of data — a computer needs data from which to learn in order to become intelligent. And with the proliferation of sensors —sensors attached to refrigerators, sensors attached to pipelines, sensors attached to production lines and even sensors attached to cows — there is more data than ever before. The volume and quality of data have a critical impact on the success of an artificial intelligence system.
The recipe of an AI system provides guidance on how the computer should discover patterns in data to produce outputs. The recipe helps the computer to create rules for classifications, segmentation and predictions based on the data it is learning from. According to AI Ethics report, AI technology also not only require a large of datasets and algorithms but also obtain a systematic approach to avoid bias and achieve core ethical value for relieving human well-being and happiness, as well as solving important issues, such as SDGs.