IEEE Technology and Society Magazine - March 2018 - 89
Table 5. effects of self-reported ideology on support under different experimentally varied conditions
as estimated by subsample correlations and regression coefficients computed under different conditions.
2014
2015
Corr
%Var
B
%Var
Corr
%Var
B
%Var
Economic
-0.09
0.86%
-0.14
0.08%
0.12
1.44%
0.18
0.08%
Security
-0.02
0.05%
-0.04
0.00%
0.29*
8.18%
0.48*
0.55%
Environment
-0.27**
7.02%
-0.35*
0.48%
-0.32*
10.43%
-0.35
0.26%
Economic
-0.09
0.77%
-0.14
0.08%
0.15
2.37%
0.25
0.16%
Security
0.24*
5.71%
0.40*
0.64%
-0.00
0.00%
-0.00
0.00%
Environment
-0.18
3.28%
-0.29
0.25%
0.11
1.25%
0.15
0.05%
Government use for...
Business use for...
2
+p<0.10, *p<0.05, **p<0.01, ***p<0.001. These follow-ups were justified by a significant four-way interaction (R -change=0.006, F-change(2,853) = 3.09,
p = 0.046) indicating that the strength of the ideology-support relationship varied by end-user, purpose, and year of the survey. Corr=Pearson correlation.
%var for corr indicates the total variance shared by self-reported ideology and support. %Var for B indicates the independent variance accounted for based on
regression results.
Discussion and Recommendations
As stated by [30], "it is important to note that on one
hand a new technology may bring about radical changes
in society, while on the other hand the fate of that technology rests with the society in which it is being applied"
[30, p. 783]. The present work investigating U.S. public
responses to UAV technologies is important, as it confirms and extends prior findings, thereby advancing
understanding of U.S. public resistance to and support
of UAVs, while also suggesting recommendations for UAV
developers, end users, and policy makers.
For example, terminology had no effect on public support, consistent with previous findings [9]. This may suggest UAV developers, policy makers, and users should
not waste energy fighting for specific terminology.
Instead they should focus on the factors more important
to the public, such as how, why, and by whom the UAVs
will be used. It appears from these findings that members of the public translate between "drone" and other
similar, but much less familiar, terms without a measureable change in attitude.
Second, the finding that prevention framing enhances support suggests that members of the public are
more moved by appeals related to reducing threats than
enhancing benefits. This strategy could emphasize how
UAVs can be used to prevent or decrease risks rather
than increasing convenience. For example, if designing
UAVs for prescribed fires, more public support may be
garnered by emphasizing how use of the UAVs protects
workers and the public from dangerous situations, rather than emphasizing efficiency or even safety gains.
However, the weakness of the effect suggests framing
may not be a very powerful strategy for impacting public support.
march 2018
∕
Instead, focusing on valued purposes may be more
powerful. Consistent with prior findings, support for
UAVs varied significantly by purpose. In our samples,
the greatest support was found for UAVs used for environmental purposes and the least support was found for
use for security purposes. Because we used a convenience sample, this specific pattern may or may not generalize to the U.S. as a whole. Nonetheless, the results
indicate that various U.S. publics are likely paying much
more attention to UAV purpose - rather than to factors
like terminology or framing-when deciding how much
they support UAVs.
The public is also attending to who is using the UAVs
and how much they trust them. Trustworthiness variables
accounted for the second largest amount of variance after
UAV purposes. Of the trustworthiness variables, positive
trustworthiness perception was the strongest predictor of
support, followed by perceived competence, and then
perceived distrustworthiness (see Table 4). This indicates
a relatively positive public context for UAVs (i.e., support is
driven by reasons to trust users rather than by reasons to
distrust) and could allow broader support for trusted entities, such as fire rescue personnel, to use UAVs. It also
suggests that efforts to impact factors increasing perceived end-user trustworthiness, such as training and
licensing, may result in greater support for their UAV uses.
Regulatory or punitive responses aimed at reducing distrust in end users may be less effective.
It is worth highlighting that drone autonomy was
mostly unrelated to public support in our two samples.
Furthermore, the direction of one observed marginal
effect indicated a preference for autonomy. This finding
contrasts with the evidence of public concern when it
comes to autonomous cars [31] or autonomous military
IEEE Technology and Society Magazine
89
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