AGENT-BASED MODELING OF THE ROLE OF SELECTIVE EXPERT OPINION IN THE DISSEMINATION OF
SCIENTIFIC IDEAS UNDER UNCERTAINTY
Emily Wilkins and David Courard-Hauri, Environmental Science and Policy Program, Drake University
Abstract
We live in a period where large amounts of data are too complex to be easily
understood by many interested individuals, who therefore must rely on expert
interpretation in order to expand their information about the world. However, in
several fields where scientific results are seen to have political implications (for
example, climate change, evolution, subjective well-being), oftentimes individuals
either seek out or are presented with experts who are preselected for the type of
data they are willing to provide. We have developed an agent-based model of
interacting individuals seeking to understand a quantitative question in the face of
“noisy” data. We use the simulation package NetLogo to study the communication
of environmentally relevant scientific information in a heterogeneous society. We
investigate the roles of uncertainty, expert interpretation, and intentional
information selection in the maintenance of false beliefs even when the agent has a
personal incentive to hold beliefs that correspond to exogenous reality, as well as
the relative importance and power of these influences in the emergence of stable or
complex dynamic networks of false belief systems.
Introduction
Each agent is then able to see only 5 points, and from those points each agent tries
to determine whether they are looking at a sine or a cosine wave. Agents also have
a randomly generated bias, predisposing them to expect one or the other. To
simulate social interactions, the agent will then interact with its neighbors, find out
what they believe, and make decisions according to the makeup of the group and
the extremism concept. The core data used to model extremism of the agents in
our simulation is based upon the observed voting patterns of appointed judges.4
Researchers observed that when people of like minds gather together, they are
more likely to reach more extreme conclusions than any individual. This will alter
the agent’s bias in belief. The agent also choses an expert to confer with, which
allows them to see the points the expert sees. The agents can chose which expert to
listen to and how much that changes their belief. For this study, agents always
chose the expert in the 6th percentile leaning towards what they already believed.
From interactions and expert opinion, the agent will then reevaluate their opinion
about whether they see sine or cosine.
Results
 As expert opinion becomes more important, there is a greater chance the
population will not reach consensus.
More people will be incorrect when expert opinion increases in importance
because of selective biases. Being able to choose which expert to listen to
strengthens divergence of opinions.
 As experts are able to see more data, it generally increases the likelihood the
group will come to a consensus.
Typical pre-run mix of opinions:
We were interested in how expert opinion affects the propagation of incorrect
beliefs within a population, where individuals have access to partial, imperfect data
about external reality. The study was inspired by observations that opinions about
global climate change among the lay public have become increasingly divergent,
while expert opinion on the topic has converged quite dramatically.1 We developed
a simple model to look into this topic and investigate the specific factors that lead
people to develop a decision. This model incorporates both interactions between
individuals and interactions with selected experts. We used evidence from studies
on individual choice within groups to model behavior that people exhibit when
forming decisions in groups.2 By looking into factors such as extremism, neighbor
radius, and a bias factor, it is possible to observe unique emergent behavior.
Our specific interest is in how the presence of experts change overall public
perception when other variables such as neighbor interactions are present, but held
constant. Experts generally have access to more information and can better
interpret conflicting results. The presence of experts ought to increase movement
toward consensus, but we hypothesize that the ability to choose which experts to
pay attention to may strengthen divergence of opinions. Media rarely inform people
of expert consensus, instead presenting one argument for an issue, so it is easy for
an individual to be selective when choosing an expert.3
Methods
In our model, we assume that
individuals are trying to
determine whether observed
external reality corresponds to a
sine or cosine wave. They have
made measurements, but the
measurements are imprecise and
so are normally distributed about
the actual wave.
Figure 1. The effects of the number of points experts see and the fraction of expert
opinion agents accept on the proportion of the population that is correct.
Once the program begins, people become more
extreme and clustering is observed (red is correct):
Future Directions
We have only begun to investigate the interaction of public communication
variables (such as extremism) and expert variables, and more work here is
necessary to identify key points of control.
Additionally, in this study people always chose to look at an expert that agreed
with them, in the top 6th percentile. Altering the model to have variation in this
would better factor in experts’ ability to change perceptions and allow for further
discussions on how the portrayal of expert opinion influences public consensus.
References
1. Doran, P. T. & Zimmerman, M. K. (2009). Examining the Scientific Consensus on Climate Change. EOS, Transactions of the
American Geophysical Union, 90, 22-23.
2. Sunstein, C.R. (2009). Goring to Extremes, How Like Minds Unite and Divide, Oxford University Press.
3. Shapiro, J. M. (2014). Special Interests and the Media: Theory and an Application to Climate Change. National Bureau of
economic research, 2-33.
4. Sustein, C.R., Schkade, D., Ellman, L.M., & Sawicki, A. (2006). Are Judges Political? An Empirical Analysis of the Federal
Judiciary, Brookings Institution Press