IEEE Technology and Society Magazine - June 2021 - 7

is being packaged as something at the upper end of
the AI spectrum by willfully leveraging preconceptions
and misconceptions of AI competence through
the speech act of " AI. "
Therefore, people have been, and are being,
" encouraged " to think about artificial intelligence
wrongly [5]. The results of thinking about it wrong
are all around us, and not much of it is " good. " Just
as the " autonomous " in lethal autonomous weapons
allows the military to dissemble over responsibility
for their effects, there are civilian companies leveraging
" AI " to exert control without responsibility. And
there are tech giants and others who are happily taking
advantage of the gaps that this creates.
And so we arrive at " trustworthy AI " because, of
course, we are building systems that people should
trust and if they don't it's their fault, so how can we
make them do that, right? Or, we've built this amazing
" AI " system that can drive your car for you but
don't blame us when it crashes because you should
have been paying attention. Or, we built it, sure, but
then it learned stuff and it's not under our control
anymore-the world is a complex place.
The problem of " trustworthy AI " is one that has
great many different " sides. " On the one hand, there
are guidelines (for example, from the EU) that tell
us how AI should be built and/or behave in order to
be seen as " trustworthy " -presumably this means
that people are going to (should? must?) trust it.
On the other hand, the problem is seen as " We
shouldn't have to trust AI " because it is a " made
thing " and, since it is a human artifact, humans
should be held responsible (accountable) when it
does something wrong. As we've already noted, in
many cases, when they are using marketing speak,
those who claim " AI " can be seen as " trustworthy "
also claim that it is " beyond the control " of its creators
when it leaves the shop floor. Usually, it's the
creators who claim this, by the way. This is an unacceptable
attempt to evade responsibility by people
who would rather not be held accountable. There
are many, but the usual suspects would seem to be
prevalent-we can call them big tech, for the sake
of argument, but they need not be big or indeed
tech. As Mayor [6] notes " artificial devices " have
always been used by those who would seek power
over others (and of course, to the detriment of their
creators, in the end).
It's not just an evasion of responsibility; it is an
exercise in power and it is profoundly wrong.
June 2021
There's another hand (sure, we have two, but we
can borrow one). There are also those who believe
that there is a need to consider how we treat AI, and
think about it because doing so holds a mirror up to
our own humanity. Perhaps even more importantly,
it prepares us for a time when we may well need to
worry about how we used to treat it. To our shame,
we have plenty of examples through human history
of how we treated those that looked different from
us. These have never been shining examples of the
goodness of human nature. Unlike the powerful position
Columbus, Drake, and others were in during the
" discovery " of new lands and peoples, we may find
ourselves in a somewhat less powerful position with
respect to a synthetic mind should we one day all be
unequivocally satisfied that one has appeared.
That reference to " synthetic mind " was deliberately
chosen.
It is important to be clear here. Seeing a future
where such a thing may come to pass is emphatically
not the same as seeing a present where those
who create " trustworthy AI " should not be held
responsible for its actions. Of course, they should be.
However, unfortunately, it's also not quite that
simple. There can be a debate here about whether
we could or would ever produce something sufficiently
holistically mind-like to satisfy even the
strongest critics of AI. It is possible that we don't have
enough time left to find out. It is also rather easy to
point the " idealist " finger at those who (choose to)
believe that we may. And there is, as alluded to
earlier, a substantial difference between AI, in the
form of Turing's " imaginable digital computer that
would do well at the Imitation Game, " and AI as a
basic problem solver or classifier implemented at
a hackathon.
But there is a sense of a moving target here. In
one conception of AI, Rich and Knight [7] define
it as " the study of how to make computers perform
things that, at the moment, people do better. " This
definition serves as a metaphorical carrot or a
stick, to encourage us to make computers that can
do ever more mind-like things. It also goes some
way to explaining why, once we've figured out
how to do something mind-like perfectly well with
a machine, and it is so common as to no longer
be surprising, we are tempted to start claiming
that that machine is " not really AI. " As an aside, it
does not seem at all obvious to us that a hypothetical
future (synthetic or alien) mind would be in
7

IEEE Technology and Society Magazine - June 2021

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