IEEE Technology and Society Magazine - September 2022 - 7

Editorial
The Unbelievable
Pointlessness of Impact
Jeremy Pitt
Imperial College London, London SW7 2BX, U.K.
 All the deep philosophical questions, starts
the joke, were asked by the classical Greeks, and
everything since then has been footnotes and comments
in the margins, finishes the punchline-
although Graeber [1] might have argued that it was
the military-coinage-slavery complex that fostered a
flowering of philosophical thought in three regions
(the Mediterranean, India, and China) contemporaneously,
and all else has been footnotes.
Certainly, as documented in [2], the Greeks were
as concerned with artificial life as they were with a
pantheon of deities, producing myths such as those of
the bronze warrior Talos and the statue brought-to-life
Galatea. Thus, a concern for artificial life and artificial
consciousness seems to have been at the forefront of
human thought from at least 600 BC to the present day,
when (at the time of writing) Google engineer Blake
Lemoine claimed that his artificial intelligence (AI)
program was conscious, and its biggest concern was
being switched off, a claim that seemed to cause considerable
concern to his employers. While it is arguable
whether or not the claim involves significant elements
of remarkable self-deception, projection, confirmation
bias, and what has been called the media equation
(people's tendency to ascribe human characteristics to
media computers [3] and interact with them as if they
were another person), the advancement of the " knowledge
frontier " that enabled the creation of this program
goes back some way.
Digital Object Identifier 10.1109/MTS.2022.3197120
Date of current version: 16 September 2022.
September 2022
Tales from the knowledge frontier
While the question of computer consciousness was
brought to prominence by Turing's [4] original paper
on machine intelligence, the first " big wave " of AI in
the 1970s and early 1980s saw a number of attempts to
build machine learning systems based on artificial neural
networks. This included the neocognitron of Fukushima
et al. [5] (whose ideas of multilayer networks
gradually integrate local features at lower layers which
are classified at higher-layer prefigured convolutional
neural networks) and the perceptrons of Minsky and
Papert [6]. Minsky and Papert's conclusions on the limitation
of perceptrons also included the idea that learning
how to do a complex task would require multiple
neuronal layers and might, therefore, be untrainable.
This was the cause of some controversy: some related
to misinterpretation of their results and some related
to that misinterpretation's contribution to the so-called
" AI winter " of the late 1980s.
Nevertheless, the first pattern recognition system
based on neural learning, WISARD, was built by Aleksander
et al. [7] at Imperial College in 1984-despite
grant proposals being frequently rejected on the
grounds that Minsky and Papert had shown that
(allegedly) " neural networks don't work. " WISARD
worked because it pared down the messy and hardto-compute
neural functions proposed by Minsky
and Papert (with which they and everyone else were
struggling) into a random access memory that could
be implemented in hardware or simulated in software.
An industrial system based on WISARD was
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