The purpose of this study is to offer a roadmap for work on the ethical and societal implications of algorithms and AI. Based on an analysis of the social, technical and…
The purpose of this study is to offer a roadmap for work on the ethical and societal implications of algorithms and AI. Based on an analysis of the social, technical and regulatory challenges posed by algorithmic systems in Korea, this work conducts socioecological evaluations of the governance of algorithmic transparency and accountability.
This paper analyzes algorithm design and development from critical socioecological angles: social, technological, cultural and industrial phenomena that represent the strategic interaction among people, technology and society, touching on sensitive issues of a legal, a cultural and an ethical nature.
Algorithm technologies are a part of a social ecosystem, and its development should be based on user interests and rights within a social and cultural milieu. An algorithm represents an interrelated, multilayered ecosystem of networks, protocols, applications, services, practices and users.
Value-sensitive algorithm design is proposed as a novel approach for designing algorithms. As algorithms have become a constitutive technology that shapes human life, it is essential to be aware of the value-ladenness of algorithm development. Human values and social issues can be reflected in an algorithm design.
The arguments in this study help ensure the legitimacy and effectiveness of algorithms. This study provides insight into the challenges and opportunities of algorithms through the lens of a socioecological analysis: political discourse, social dynamics and technological choices inherent in the development of algorithm-based ecology.
The main purpose of this study was to determine whether users of the online social network site, Facebook, actually look at the ads displayed (briefly, to test the existence of the phenomenon known as “banner blindness” in this website), thus ascertaining the effectiveness of paid advertising, and comparing it with the number of friends' recommendations seen.
In order to achieve this goal, an experiment using eye‐tracking technology was administered to a total of 20 participants from a major university in the USA, followed by a questionnaire.
Findings show that online ads attract less attention levels than friends' recommendations. A possible explanation for this phenomenon may be related to the fact that ads on Facebook are outside of the F‐shaped visual pattern range, causing a state of “banner blindness”. Results also show that statistically there is no difference in ads seen and clicked between women and men.
The sample type (undergraduate and graduate students) and the sample size (20 participants) inhibit the generalization of the findings to other populations.
The paper includes implications for the development of an effective online advertising campaign, as well as some proposed conceptualizations of the terms social network site and advertising, which can be used as platforms for discussion or as standards for future definitions.
This study fulfils some identified needs to study advertising effectiveness based on empirical data and to assess banner blindness in other contexts, representative of current internet users' habits.