Should the "I" in "Artificial Intelligence (AI)" need a reboot?

So, if Machine Learning is the way AI is powered to meet only the last point of acquiring knowledge and storing it for use later, then will this not be "incomplete intelligence"? At the risk of sounding like a non-conformist, Pearl argues that Artificial Intelligence is handicapped by an incomplete understanding of what intelligence really is. AI applications, as of today, can solve problems that are predictive and diagnostic in nature, without attempting to find the cause of the problem. Never denying the transformative and disruptive, complex, and non-trivial power of AI, Pearl has shared his genuine critique on the achievements of Machine Learning and Deep Learning given the relentless focus on correlation leading to pattern matching, finding anomalies, and often culminating in the function of "curve"-fitting. The significance of the "ladder of causation" i.e., progressing from association to intervention and concluding with counter factuality has been the contribution of immense consequence from Pearl. Pearl has been one of the driving forces who expects that the correlation-based reasoning should not subsume the causal reasoning and the development of causal based algorithmic tools.