IEEE Technology and Society Magazine - June 2021 - 12

Editorial
persons...who understand the mental processes
and social patterns of the masses. It is they who
pull the wires which control the public mind.
In short, it actually doesn't matter if we as academics
in whichever ivory towers we inhabit tell people
that they shouldn't see computers that way. In fact,
this could almost certainly be extended to other
machines-cars, for example. Automation bias will
see to it that they will tend to see things like this anyway,
but it will be reinforced by this conscious and
intelligent manipulation of their opinions. It almost
certainly doesn't matter if we tell people not to trust
technology, they already do. This is part of the problem.
Because " AI " as speech act is used, that trust
is misdirected and abused, with obviously negative
consequences. This isn't about trustworthy " AI " ; it's
about untrustworthy people.
At the end of Artificial Unintelligence Broussard
[19] says that " Turning real life into math is a marvellous
magic trick, but too often the inconveniently
human part of the question gets pushed to the side.
Humans are not now, nor have they ever been,
inconvenient. Humans are the point. Humans are the
beings all this technology is supposed to serve. " We
cannot but agree, and we would add this: humans
are also the ones tricking the rest of us into believing
otherwise. However, we would add a cautionary
note: this is true for " AI " as speech act. It need not be
true for AI as synthetic mind. Maybe we will find out.
Where is this taking us? We observe that trustworthy
" AI " is used as a tool to deflect responsibility,
or even to be a proxy for trustworthy developers
and engineers. The result is based on abnegation of
responsibility and willful ignorance. We should be
doing better. For one thing, it is important to note
the distinction between " AI " (as power speech act
or marketing speak), which we see around us extensively,
and AI (or synthetic minds), which we could
perhaps have already constructed either on purpose
or by accident, but which we should be careful to
acknowledge as " different. " This last point is important:
AI as a synthetic mind is not a binary " thing " ;
just as there are different kinds of intelligence, there
are almost certainly different kinds (and levels) of
synthetic minds. Some of these seem futuristic, while
others, we contend, are already here or may be
" out there. " And if we cannot ask ourselves how we
should be treating that which is not " us, " we deserve
everything we have coming.
12
We suggest that a democratization of both " AI "
and AI is necessary in order to better inform the
people who are affected by this deceit. It is not satisfactory
to blame the computer-indeed it never has
been, yet since we've had them, we've tried to do
exactly that-what is needed is the means to explain:
What the system is doing;
Why it does what it does;
How it does this thing;
Why it does it this way;
In ways that the people affected by it understand.
This should not be the responsibility of the machine,
since we do not (yet) have AI capable of bearing
responsibility for its behavior and operation. Let's
consider a more pressing question instead: who is
responsible for " AI " ?
This acTually should not be too much to ask. 
 References
[1] P. Walker, " Call centre staff to be monitored via
webcam for home-working 'infractions' , " The Guardian.
Accessed: Mar. 26, 2021. [Online]. Available: https://
www.theguardian.com/business/2021/mar/26/
teleperformance-call-centre-staff-monitored-viawebcam-home-working-infractions
[2]
S. West, M. Whittaker and K. Crawford. (2019).
Discriminating Systems: Gender, Race and Power
in AI. AI Now Institute. [Online]. Available: https://
ainowinstitute.org/discriminatingsystems.html
[3] A. Turing, " Computing machinery and intelligence,''
Mind, vol. 49, pp. 433-460, Oct. 1950.
[4] J. Haugeland, Artificial Intelligence: The Very Idea.
Cambridge, MA, USA: MIT Press, 1985.
[5] K. Milanovic and J. Pitt, " Misattribution of error
origination: The impact of preconceived expectations
in co-operative online games,'' in Proc. Designing
Interact. Syst. (DIS), 2021.
[6] A. Mayor, Gods and Robots. Princeton, NJ, USA:
Princeton Univ. Press, 2018.
[7] E. Rich and K. Knight, Artificial Intelligence. New York,
NY, USA: McGraw-Hill, 1990.
[8] D. Graeber, The Utopia of Rules: On Technology,
Stupidity, and the Secret Joys of Bureaucracy.
Brooklyn, NY, USA: Melville House, 2015.
[9] D. Graeber, Bullshit Jobs: A Theory. New York, NY,
USA: Simon & Schuster, 2018.
[10] M. Boden, AI: Its Nature and Future. Oxford, U.K.:
Oxford Univ. Press, 2016.
[11] J. Bryson. (2018). AI & Global Governance: No One
Should Trust AI. United Nations University, Centre for
IEEE Technology and Society Magazine

https://www.theguardian.com/business/2021/mar/26/teleperformance-call-centre-staff-monitored-via-webcam-home-working-infractions https://www.theguardian.com/business/2021/mar/26/teleperformance-call-centre-staff-monitored-via-webcam-home-working-infractions https://www.theguardian.com/business/2021/mar/26/teleperformance-call-centre-staff-monitored-via-webcam-home-working-infractions https://www.theguardian.com/business/2021/mar/26/teleperformance-call-centre-staff-monitored-via-webcam-home-working-infractions https://www.ainowinstitute.org/discriminatingsystems.html https://www.ainowinstitute.org/discriminatingsystems.html

IEEE Technology and Society Magazine - June 2021

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