AIR5: Five Pillars of Artificial Intelligence Research
In this paper, we provide an overview of what we consider to be some of the most pressing research questions currently facing the fields of artificial and computational intelligence (AI and CI). While AI spans a range of methods that enable machines to learn from data and operate autonomously, CI serves as a means to this end by finding its niche in algorithms that are inspired by complex natural phenomena (including the working of the brain). In this paper, we demarcate the key issues surrounding these fields using five unique Rs, namely, rationalizability, resilience, reproducibility, realism, and responsibility. Notably, just as air serves as the basic element of biological life, the term AIR5-cumulatively referring to the five aforementioned Rs-is introduced herein to mark some of the basic elements of artificial life, for sustainable AI and CI. A brief summary of each of the Rs is presented, highlighting their relevance as pillars of future research in this arena.
Data models , Training , Computational intelligence , Predictive models , Resilience , Artificial neural networks