Participating and designing around algorithmic socio-technical systems

Eslamimehdiabadi, Motahhare

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https://hdl.handle.net/2142/106253 Copy

Description

Title

Participating and designing around algorithmic socio-technical systems

Author(s)

Eslamimehdiabadi, Motahhare

Issue Date

2019-12-05

Director of Research (if dissertation) or Advisor (if thesis)

Karahalios, Karrie

Doctoral Committee Chair(s)

Karahalios, Karrie

Committee Member(s)

• Bailey, Brian
• Hamilton, Kevin
• Sundaram, Hari
• Sandvig, Christian

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Algorithms
• Algorithmic Opacity, Algorithmic Transparency
• Socio-Technical Systems
• Design

Abstract

Our daily digital life is full of algorithmically selected content such as social media feeds, recommendations and personalized search results. These algorithms curate everyday online content by prioritizing, classifying, associating, and filtering information. However, while these algorithms have great power to shape users’ experiences, users are often unaware of their operation, or even presence. While this opacity partly stems from protecting intellectual property and preventing malicious users from gaming the system, it is also designed to provide users with seamless, effortless system interactions. However, this opacity can result in misinformed behavior among users, particularly when there is no clear feedback mechanism for users to understand the effects of their own actions on an algorithmic system. The increasing prevalence and power of these opaque algorithms coupled with their sometimes biased and discriminatory decisions raises questions about how knowledgeable users are and should be about the existence, operation and possible impacts of these algorithms. This dissertation draws on human-computer interaction, social computing and data mining techniques to investigate users’ behavior around opaque algorithmic systems and create new designs that communicate opaque algorithmic processes to users and provide them with a more informed, satisfying, and engaging interaction. In doing so, I add new angles to the old idea of understanding the interaction between users and automation by investigating and designing around algorithm sensemaking and algorithm transparency. Specifically, this dissertation makes three contributions. First, it investigates how users currently interact with opaque algorithmic socio-technical systems and what is missing in this interaction. I show that when an algorithmic system is opaque, users try to add “seams,” visible hints disclosing aspects of automation operations, into the system manually to increase the visibility of the algorithm and its potential impacts on other users (such as bias). In doing so, users also take stances (defending or questioning) towards an algorithm’s existence, opacity in existence, operation, and opacity in operation. These findings lead to the next part of this dissertation in which I present two seamful designs, ReVeal (on Yelp) and FeedVis (on Facebook), to demonstrate how we can redesign current opaque algorithmic systems by adding transparency into the existence of algorithms. I report on the extensive lack of awareness about the presence of opaque algorithms in algorithmic socio-technical systems. I then illustrate that a seamful design can help users to have a more informed and engaging interaction with the system by developing theories about how an algorithm might work. Finally, I take a step further and expose users to the operation of opaque algorithms. I show that users do not need full transparency in ad curation process in order to have a satisfactory experience. For example, in the case of opaque behavioral advertising algorithms, what users need is an interpretable, non-creepy explanation with a link to their identity. I then evaluate the impacts of different levels of transparency on users’ perception of algorithmic decisions and show that while increasing transparency about how an algorithm (here a review filtering algorithm) makes a decision can improve users’ understandability of the decision, it cannot change users’ agreement or disagreement with the decision. The findings of this dissertation present a future for algorithmic socio-technical systems in which adding a right level of transparency into algorithmic processes provide a more informed, satisfying, and adaptive interaction between users and the system.

Graduation Semester

2019-12

Type of Resource

text

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http://hdl.handle.net/2142/106253

Copyright and License Information

Copyright 2019 Motahhare Eslamimehdiabadi

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