OUR INHERENT HUMAN tendency of favoring one thing
or opinion over another is reflected in every aspect
of our lives, creating both latent and overt biases
toward everything we see, hear, and do. Any remedy
for bias must start with awareness that bias exists; for
example, most mature societies raise awareness of
social bias through affirmative-action programs, and,
while awareness alone does not completely alleviate
the problem, it helps guide us toward a solution. Bias
on the Web reflects both societal and internal biases
within ourselves, emerging in subtler ways. This
article aims to increase awareness of the potential
effects imposed on us all through bias present in Web
use and content. We must thus consider and account
for it in the design of Web systems that truly address
Bias has been intrinsically embedded in culture and
history since the beginning of time. However, due to
the rise of digital data, it can now
spread faster than ever and reach
many more people. This has caused
bias in big data to become a trending
and controversial topic in recent years.
Minorities, especially, have felt the
harmful effects of data bias when pur-
suing life goals, with outcomes gov-
erned primarily by algorithms, from
mortgage loans to advertising person-
alization. 24 While the obstacles they
face remain an important roadblock,
bias affects us all, though much of the
time we are unaware it exists or how it
might (negatively) influence our judg-
ment and behavior.
The Web is today’s most prominent
communication channel, as well as
a place where our biases converge. As
social media are increasingly central to
daily life, they expose us to influencers
we might not have encountered previously. This makes understanding and
recognizing bias on the Web more essential than ever. My main goal here is
thus to raise the awareness level for all
Web biases. Bias awareness would help
us design better Web-based systems, as
well as software systems in general.
The first challenge in addressing bias
is how to define and measure it. From
a statistical point of view, bias is a systemic deviation caused by an inaccurate estimation or sampling process.
As a result, the distribution of a variable could be biased with respect to the
original, possibly unknown, distribution. In addition, cultural biases can be
found in our inclinations to our shared
personal beliefs, while cognitive biases
affect our behavior and the ways we
Figure 1 shows how bias influences
Bias in Web data and use taints the
algorithms behind Web-based applications,
delivering equally biased results.
BY RICARDO BAEZA-YATES
˽ Any remedy for bias starts with
awareness of its existence.
˽ Bias on the Web reflects biases within
ourselves, manifested in subtler ways.
˽ We must consider and account for bias
in the design of Web-based systems that
truly address the needs of users.