https://arxiv.org/pdf/2504.01029
Bias Bytes #1
Welcome to the first edition of my bi-monthly newsletter aiming to keep you updated with all things bias-based to help us all feel more grounded when it comes to critical oversight. I'm pretty proud of my graphic headings so please humour me :) Let's start with.
View of Generative AI in Design Thinking Pedagogy: Enhancing Creativity, Critical Thinking, and Ethical Reasoning in Higher Education
My Ethical AI Principles
Sign posted in the common kitchen at the campground in Selfoss, Iceland, where this article was written I understand. Artificial Intelli...
On Ethical AI Principles
I have commented in my newsletter that what people have been describing as 'ethical AI principles' actually represents a specific po...
AI Ethics in the Content Areas
A collection of resources shared with conference attendees during the 24-25 school year.
Capabilities & Ethics of AI Found in Middle Grades Fiction
Novels that explore AI through stories grounded in real ethical and scientific questions spark discussions and critical thinking with students, says Kasey Short
Digital ethicswashing: a systematic review and a process-perception-outcome framework - AI and Ethics
The term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.”
Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia.
In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.
The term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.” Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia. In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.
AI Ethics, Ethics Washing, and the Need to Politicize Data Ethics
Many commercial actors in the tech sector publish ethics guidelines as a means to ‘wash away’ concerns raised about their policies. For some academics, this phenomenon is reason to replace ethics with other tools and methods in an attempt to make sure that the tech sector does not cross any moral Rubicons. Others warn against the tendency to reduce a criticism of ‘ethics washing’ into one of ethics simpliciter. In this essay, I argue firstly that the dominant focus on principles, dilemmas, and theory in conventional ethical theories and practices could be an explanation of it lacking resistance to abuse by dominant actors, and hence its rather disappointing capacity to stop, redirect, or at least slow down big tech’s course. Secondly, drawing from research on casuistry and political philosopher Raymond Geuss, this essay will make a case for a question, rather than theory or principle-based ethical data practice. The emphasis of this approach is placed on the acquisition of a thorough understanding of a social-political phenomenon like tech development. This approach should be replenished with one extra component to the picture of the repoliticized data ethics drawn so far: the importance of ‘exemplars,’ or stories. Precisely the fact that one should acquire an in-depth understanding of the problem in practice will also allow one to look in the past, present, or future for similar and comparable stories from which one can learn.
The Most Important Skills for the 4th Industrial Revolution? Try Ethics and
For those keeping count, the world is now entering the Fourth Industrial Revolution. That’s the term coined by Klaus Schwab, founder and executive ...