The 30-Year Cycle In The AI Debate
  In the last couple of years, the rise of Artificial Intelligence and the
successes of academic breakthroughs in the field have been inescapable. Vast
sums of money have been thrown at AI start-ups. Many existing tech companies --
including the giants like Google, Amazon, Facebook, and Microsoft -- have
opened new research labs. The rapid changes in these everyday work and
entertainment tools have fueled a rising interest in the underlying technology
itself; journalists write about AI tirelessly, and companies -- of tech nature
or not -- brand themselves with AI, Machine Learning or Deep Learning whenever
they get a chance. Confronting squarely this media coverage, several analysts
are starting to voice concerns about over-interpretation of AI's blazing
successes and the sometimes poor public reporting on the topic. This paper
reviews briefly the track-record in AI and Machine Learning and finds this
pattern of early dramatic successes, followed by philosophical critique and
unexpected difficulties, if not downright stagnation, returning almost to the
clock in 30-year cycles since 1958.
