[Colloquium] Thursday 4/11 | Abdullah Almaatouq at the Computational Social Science Workshop

[Nora Nickels]

THE COMPUTATIONAL SOCIAL SCIENCE WORKSHOP PRESENTSABDULLAH
ALMAATOUQPH.D. STUDENT
IN COMPUTATIONAL SCIENCE & ENGINEERING, RESEARCH ASSISTANT AT THE HUMAN
DYNAMICS GROUPMASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT)



The Computational Social Science Workshop
<https://macss.uchicago.edu/content/computation-workshop>at the University
of Chicago cordially invites you to attend this week’s talk:


THE WISDOM OF THE NETWORK
<https://github.com/uchicago-computation-workshop/abdullah_almaatouq/blob/master/WON-draft.pdf>


Summary: Collective decision systems such as teams, markets, polls, and
votes are central to the way society organizes and allocates resources. The
use of these and related modern mechanisms is on the rise, finding
applications in areas as diverse as problem-solving, technological and
economic forecasting, crowdsourcing, product rating, public policy design,
and mapping natural disasters. Hence, providing a sound understanding of
and useful design guidelines for these systems is of paramount importance.
Although scientists have generated a tremendous number of studies on this
topic, they have been much less successful at reconciling some of the
inconsistencies and contradictions amongst them. For instance, studies have
shown that social interaction (i.e., via communication networks) can either
promote the “wisdom of the crowd” or, conversely, lead to the “madness of
the mob” by inducing social bias, herding, and group-think. Different
theories have disagreed on which communication structural attributes are
most relevant, and empirical studies offered an overwhelming lack of
consistent evidence. However, many of the studies on this topic only
consider, explicitly or implicitly, static communication network structures
and stable environments, offering at best a partial view of human
collective decision making. Here we address this question using a series of
human experiments and supporting simulations. Our results show that the
optimal communication structure depends on the “environment,” and that
groups provided with high-quality feedback and connected by dynamic
communication structures, as opposed to static ones, can adapt to biased
and non-stationary information environments, significantly improving both
individual and collective judgments. Furthermore, we find that the
collective performance of these groups can substantially surpass that of
their best individual and that even the best individual’s judgment is
substantially benefited from group engagement. Our findings help reconcile
some previously conflicting claims from the collective intelligence
literature and motivate a future research program to more systematically
identify stable principles of collective performance.


THURSDAY, 4/11/201911:00AM-12:20PMKENT 120


A light lunch will be provided by Noodles, Etc.



Abdullah Almaatouq is Research Assistant at the Human Dynamics group and
pursuing a PhD in Computational Science & Engineering at the Massachusetts
Institute of Technology (MIT). He did dual masters’ at MIT in Computation
for Design & Optimization (CDO) and Media, Arts & Sciences (MAS), and
before that he received his bachelor degree from the School of Electronics
and Computer Science at Southampton University, UK. Abdullah’s current
research interests lie in the area where computational and social sciences
meet. In particular, his work includes conducting theoretical and empirical
research on human behavior using innovative approaches and tools ranging
from complex systems theory and agent-based modeling, to network analysis,
econometric techniques, and behavioral and experimental methods.




The 2018-2019 Computational Social Science Workshop
<https://macss.uchicago.edu/content/computation-workshop>meets Thursdays
from 11 a.m. to 12:20 p.m. in Kent 120. All interested faculty and graduate
students are welcome.

Students in the Masters of Computational Social Science program are
expected to attend and join the discussion by posting a comment on the issues
page
<https://github.com/uchicago-computation-workshop/abdullah_almaatouq/issues>of
the workshop’s public repository on GitHub.
<https://github.com/uchicago-computation-workshop/abdullah_almaatouq> Further
instructions are documented in the Computational Social Science
Workshop’s README
on Github. <https://github.com/uchicago-computation-workshop/README>
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