IEEE Technology and Society Magazine - September 2020 - 24

to brea k out of the r ut a nd
-question implicit assumptions is
to solicit advice from unlikely
sources who may see the problem differently.
2)	 Conduct premortems [11]. Often
students of the social impacts of
new technologies on society find
themselves lamenting, with hindsight, negative social impacts of
a particular technology. The idea
of a premortem is to imagine
that a proposed technology has
negative impacts, to identify
what those would be, and then
deduce backwards to understand the reasons why. This
approach helps to correct against
a very natural bias humans
have to assume that actions will
have only intended consequen--
ces. It forces one to become the
devil's advocate: If we have to
assume - for the sake of argument - that our lovely technology is actually a social disaster
waiting to happen, what might
account for that?
People are not just one thing. Neither is any given technology. We
know full well now that when we intro-

24

-predict-what-viewers-will-like [Accessed
Mar. 1, 2020].
[4] J. Pitt, and A. Diaconescu, "Structure
and governance of communities for
the digital society," in Proc. 2015 IEEE
Int. Conf. Autonomic Computing, pp. 279284, 2015. https://ieeexplore.ieee.org/
document/7266980 [Accessed Apr. 2, 2020].
[5] J. Pitt, D. Busquets, A. Diaconescu, A.
Nowak, A. Rychwalska, and M. Roszczynska-Kurasinska, "Algorithmic self-governance
and the design of socio-technical systems,"
in CEUR Workshop Proc., vol. 1283, pp. 262-
273, Jan. 2014. http://ceur-ws.org/Vol-1283/
paper_33.pdf [Accessed March 15, 2020].
[6] BBC, "Computer AI passes Turing test
in 'world first'," June 9, 2014. https://
www.bbc.com/news/technology-27762088
[Accessed April 5, 2020].
[7] National Science Foundation, "Perspectives on broader impacts," Jan. 1, 2015.
https://www.nsf.gov/od/oia/publications/
Broader_Impacts.pdf [Accessed Feb. 20,
2020].
[8] https://www.nsf.gov/funding/aboutfunding
.jsp [Accessed Feb. 20, 2020].
[9] M. Johnson, J. M. Bradshaw, and P. J.
Feltovich, "Tomorrow's human-machine
design tools: From levels of automation
to interdependencies," J. Cognitive Engineering and Decision Making, vol. 12, no.
1, pp. 77-82, 2018.
[10] E. Stayton and J. Stilgoe, "It's time to
rethink levels of automation for self-driving
vehicles," IEEE Technology and Society
Mag., this issue.
[11] G. Klein, "Performing a project premortem," IEEE Engineering Management Rev., vol. 36, no. 2, pp. 103-104, May
30, 2008. https://ieeexplore.ieee.org/
document/4534313 [Accessed Apr. 1, 2020].


duce new technologies, we are altering
our societies and our own lives within
them. We may be creating something
that both bullies and defends us. It
should not be done without thoughtful examination from as many angles
as possible - positive and negative.
That, of course, calls upon the very
same ethical diversity that is under
threat in this Age of Algorithms.

Author Information
Todd L. Pittinsky is a Professor of
Technology and Society in the College of Engineering and Applied Sciences at Stony Brook University
(SUNY). He is the editor, most re--
cently, of Science, Technology, and
Society: New Perspectives and Directions (Cambridge University Press).

References
[1] "Moral Machine," M.I.T.; http://moralmachine
.mit.edu [Accessed June 30, 2020].
[2] S.D. Hunt and J.M. Hansen, "Understanding ethical diversity in organizations,"
Organizational Dynamics, vol. 36, no. 2,
pp. 202-216, 2007; http://sdh.ba.ttu.edu/
OrgDyn07%20Ethics.pdf [Accessed Mar. 1,
2020].
[3] L. Plummer, "This is how Netflix's topsecret recommendation system works,"
Wired UK, Sept. 22, 2017. https://www
.wired.co.uk/ar ticle/how -do-netf lixs
-algorithms-work-machine-learning-helps-to

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https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like https://ieeexplore.ieee.org/document/7266980 https://ieeexplore.ieee.org/document/7266980 http://www.ceur-ws.org/Vol-1283/paper_33.pdf http://www.ceur-ws.org/Vol-1283/paper_33.pdf https://www.bbc.com/news/technology-27762088 https://www.bbc.com/news/technology-27762088 https://www.nsf.gov/od/oia/publications/Broader_Impacts.pdf https://www.nsf.gov/od/oia/publications/Broader_Impacts.pdf https://www.nsf.gov/funding/aboutfunding.jsp https://www.nsf.gov/funding/aboutfunding.jsp http://moralmachine.mit.edu http://moralmachine.mit.edu http://sdh.ba.ttu.edu/OrgDyn07%20Ethics.pdf http://sdh.ba.ttu.edu/OrgDyn07%20Ethics.pdf https://ieeexplore.ieee.org/document/4534313 https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like https://ieeexplore.ieee.org/document/4534313 https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like https://www.wired.co.uk/article/how-do-netflixs-algorithms-work-machine-learning-helps-to-predict-what-viewers-will-like

IEEE Technology and Society Magazine - September 2020

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