Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Interrogating Algorithmic Bias: From Speculative Fiction to Liberatory Design
in
Algorithms
/ Artificial intelligence
/ Artists
/ Bias
/ Education
/ Educational Technology
/ Private Sector
/ Software development
/ Speculative fiction
2023
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Interrogating Algorithmic Bias: From Speculative Fiction to Liberatory Design
in
Algorithms
/ Artificial intelligence
/ Artists
/ Bias
/ Education
/ Educational Technology
/ Private Sector
/ Software development
/ Speculative fiction
2023
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Interrogating Algorithmic Bias: From Speculative Fiction to Liberatory Design
Journal Article
Interrogating Algorithmic Bias: From Speculative Fiction to Liberatory Design
2023
Request Book From Autostore
and Choose the Collection Method
Overview
This paper reviews algorithmic or artificial intelligence (AI) bias in education technology, especially through the lenses of speculative fiction, speculative and liberatory design. It discusses the causes of the bias and reviews literature on various ways that algorithmic/AI bias manifests in education and in communities that are underrepresented in EdTech software development. While other recent work has responded to mainstream or private sector technology development, this review looks elsewhere where practitioners, artists, and activists engage underrepresented communities in brainstorming processes to identify and solve tough challenges. Their creative work includes films, toolkits, applications, prototypes and other physical artifacts, and other future-facing ideas that can provide guideposts for private sector development. Acknowledging the gaps in what has been studied, this paper proposes a different approach that includes speculative and liberatory design thinking, which can help developers better understand the educational and personal contexts of underrepresented groups. Early efforts to advocate for fairness and equity in AI and EdTech by groups such as the Algorithmic Justice League, the EdTech Equity Project, and EdSAFE AI Alliance is also explored.
Publisher
Springer Nature B.V
Subject
This website uses cookies to ensure you get the best experience on our website.