The future of urban AI
10 conversations by Urban AI, a Paris based think tank, with worldwide experts to explore the future of urban artificial intelligence
Insights curated by Experientia, the international UX consultancy
Insights curated by Experientia, the international UX consultancy
Category AI
[Book] Imagining AI
The book sheds new light on some of the most important themes in AI ethics, from the differences between Chinese and American visions of AI, to digital neo-colonialism. It is an essential work for anyone wishing to understand how different cultural contexts interplay with the most significant technology of our time.
Toward best practices for human-centered machine learning
A new area called "human-centered machine learning" (HCML) promises to balance technological possibilities with human needs and values. However, there are no unifying guidelines on what "human-centered" means, nor how HCML research and practice should be conducted.
This article by Stevie Chancellor in Communications of the ACM draws on the interdisciplinary history of human-centered thinking, HCI, AI, and science and technology studies to propose best practices for HCML.
Ericsson on AI ethics
This report by the IndustryLab of Ericsson, the Swedish multinational, aims to introduce the ethics of AI and explore how this fast-growing technology needs to align with humans’ moral and ethical principles if it is to be embraced by society at large.
Design for AI: What should people who design AI know?
Hal Wuertz, Adam Cutler and Milena Pribic of IBM Design defined a unique set of five skills for “AI Design.”
2022 HAI Fall Conference on AI in the Loop: Humans in Charge
At the "AI in the Loop: Humans in Charge" conference, which took place Nov. 15 at Stanford University, panelists proposed a new definition of human-centered AI – one that emphasizes the need for systems that improve human life and challenges problematic incentives that currently drive the creation of AI tools.
Special issue on machine anthropology
Bringing together a motley crew of social scientists and data scientists, the aim of this special theme issue of Big Data & Society is to explore what an integration or even fusion between anthropology and data science might look like.
Qualitative humanities research is crucial to AI
“All research is qualitative; some is also quantitative”
Harvard Social Scientist and Statistician Gary King
[Book] Expand: Stretching the Future By Design
From transforming the ways we do business and reimagining health care, to creating planet-restoring housing and humanizing our digital lives in an age of AI, Expand explores how expansive thinking across six key areas—time, proximity, value, life, dimensions, and sectors—can provide radical, useful solutions to a whole host of current problems around the globe.
[Book] Human-Centered Data Science: An Introduction
Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.
Three interviews on UX research and anthropology
The Response-ability Summit, formerly known as the Anthropology + Technology Conference, is a unique two-day event that brings social scientists and technologists together to foster interdisciplinary conversations on the important topic of socially-responsible tech.
[Book] Human-Centered AI
In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives.
Videos online of “Humanizing technology through design” conference
Curated by Experientia partner Jan-Christoph Zoels and Sara Fortunati, director of the Torino Circle of Design, the conference dealt with the best international practices about the humanization of technology. It was structured into six different thematic sessions: ethics, public services, healthcare, AI, mobility and learning. All videos are now available, with English subtitles.
AI still sucks at moderating hate speech
But scientists are getting better at measuring where each system fails.
The human error of Artificial Intelligence
Rather than trying to fix the biases of AI systems and their human error, we need to find ways to coexist with it. Anthropology can help us a lot here.
Social science perspectives on artificial intelligence. A special issue.
This special issue collects six articles tackling artificial intelligence (AI) from a social science perspective.
Google Health’s human-centred observational study on AI’s real-world problems
The gulf between the technical brilliance claimed for Google's deep learning model and its real-world application points to a common problem that has hindered the use of AI in medical settings.
How an AI tool for fighting hospital deaths actually worked in the real world
It wasn't just technical work but also significant social and emotional labor that turned Sepsis Watch, a Duke University deep-learning model, into a success story.
Rethinking human-AI interaction
This essay by AI specialist Jessy Lin explores some of the possibilities to rethink how humans and "intelligent" machines interact today.
Anthropology and technology conference
The Anthropology + Technology conference brings together pioneering technologists and social scientists from across the globe. Its aim is to facilitate dialogue on emerging technology projects in order to help businesses benefit from more socially-responsible AI.