Machine learning (ML) is generating new opportunities for innovative research in areas apparently unrelated such as, economics, business or/and finance. Specifically, it has also been widely used in applications related to the economic and financial analysis, such as economic recessions prediction, labor market trends, risk management, prices analysis among others. However, it is important to note the differences between classical statistics/econometrics and machine learning.

The International Journal of Interactive Multimedia and Artificial Intelligence - IJIMAI - provides a space in which scientists and professionals can report about new advances in Artificial Intelligence (AI). On this occasion, for the last edition of the year, I am pleased to present a regular issue including different investigations covering aspects and problems in AI and its use in various fields such as medicine, education, image analysis, protection of data, among others.

Research on the relationship between computing and the meaning of human life flourishes proportionally to the increasing digitalization of our world. More and more, reflections on ethics and politics, spiritual values and religious experiences, beliefs, and practices make use of digital media in order to spread their content or express themselves. If we still consider that there is truth in the well-known dictum that “the medium is the message”, then it is worth asking how the content of these reflections and practices are changing today.

In today’s world, we have witnessed an onset of multimedia content being uploaded/downloaded and shared through a multitude of platforms both online and offline. In support of this trend, multimedia processing and analyzing has become very popular in all kinds of information extraction and attracts research interest from both academia and industry. This is to be expected as the multimedia digital world is worth trillions of dollars worldwide. However, multimedia information is hard to encode, interpret and recognize because it is combined with many complex components.