Human-Level Intelligence or Animal-Like Abilities?

The recent success of neural networks in applications such as speech recognition, vision and autonomous navigation has led to great excitement by members of the artificial intelligence (AI) community and the general public at large. Over a relatively short period, by the science clock, we managed to automate some tasks that have defied us for decades and using one of the more classical techniques coming out of artificial intelligence research. The triumph over these achievements has led some to describe the automation of these tasks as having reached human level intelligence. This perception, originally hinted at in academic circles, has been gaining momentum more broadly and is leading to some implications. For example, a trend is emerging in which machine learning research is being streamlined into neural network research, under its newly acquired label “deep learning.” This perception has also caused some to question the wisdom of continuing to invest in other machine learning approaches, or even mainstream areas of artificial intelligence, such as knowledge representation, symbolic reasoning and planning. Some coverage of AI in public arenas, particularly comments made by some visible figures, has led to mixing this excitement with fear of what AI may be bringing us in the future (i.e., doomsday scenarios).2 This turn of events in the history of AI has created a dilemma for researchers in the broader AI community. On the one hand, one cannot but be impressed with, and enjoy, what we have been able to accomplish with neural networks. On the other hand, mainstream scientific intuition stands in the way of accepting that a method, which does not require any explicit modeling or sophisticated reasoning, can be sufficient for reproducing human level