Extension of Endogenous Growth Theory : Artificial Intelligence as a Self-Learning Entity

The Artificial Intelligence (AI) evolution is a broad set of methods, algorithms, and technologies making software human-like intelligent that is encroaching our contemporary workplace. Thinking like humans but acting rational is the primary goal of AI innovations. The current market disruption with AI lies at the core of the IT-enhanced economic growth driven by algorithms – for instance enabled via the sharing economies and big data information gains, self-check outs, online purchases and bookings, medical services social care, law, retail, logistics and finance to name a few domains in which AI leads to productivity enhancement. While we have ample account of AI entering our everyday lives, we hardly have any information about economic growth driven by AI. Preliminary studies found a negative relation between digitalization and economic growth, indicating that we lack a proper growth theory capturing the economic value imbued in AI. We also have information that indicates AI-led growth based on ICT technologies may widen an inequality-rising skilled versus unskilled labor wage gap. This paper makes the theoretical case of AI as a self-learning entity to be integrated into endogenous growth theory, which gives credit to learning and knowledge transformation as vital economic productivity ingredients. Future research may empirically validate the claim that AI as a self-learning entity is a driver of endogenous growth. All these endeavors may prepare for research on how to enhance human welfare with AI-induced growth based on inclusive AI-human compatibility and mutual exchange between machines and human beings