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.
Insights curated by Experientia, the international UX consultancy
Insights curated by Experientia, the international UX consultancy
Category AI
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.
[Book] Possibilities and challenges of AI for work and society
Artificial Intelligence is permeating a wide range of areas and it is bound to transform work and society. This dossier asks what needs to be done politically in order to shape this transformation for the sake of the common good.
You are not your data but your data is still you
New worlds need new language. TOne of those things to name is what is happening to ourselves and our data proxies. Expanding our language from privacy to personhood enables us to have conversations that enable us to see that our data is us, our data is valuable, and our data is being collected automatically.
[Book] AI and UX: Why Artificial Intelligence Needs User Experience
The book explores the future of artificial intelligence (AI) through interviews with AI experts and explores AI history, product examples and failures, and proposes a UX framework to help make AI successful.
Why computing belongs within the social sciences
This article argues [that] the well-publicized social ills of computing will not go away simply by integrating ethics instruction or codes of conduct into computing curricula. The remedy to these ills instead lies less in philosophy and more in fields…
The ethnographer and the algorithm: beyond the black box
Angèle Christin argues that we can
explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of algorithmic systems - including their opacity. She delineates three mesolevel strategies for algorithmic ethnography.
[Book] Metrics at Work: Journalism and the Contested Meaning of Algorithms
The starkly different ways that American and French online news companies respond to audience analytics and what this means for the future of news.
[Book] New Laws of Robotics
AI is poised to disrupt our work and our lives. We can harness these technologies rather than fall captive to them - but only through wise regulation.
AI’s social sciences deficit
To create less harmful technologies and ignite positive social change, AI engineers need to enlist ideas and expertise from a broad range of social science disciplines, including those embracing qualitative methods, say Mona Sloane and Emanuel Moss in a comment…
The anthropologist of Artificial Intelligence
The algorithms that underlie much of the modern world have grown so complex that we always can’t predict what they’ll do. Iyad Rahwan, who directs the Center for Humans and Machines at the Max Planck Institute for Human Development, proposes…
Ten arguments against algorithmic decision making
Against the Dehumanisation of Decision-Making – Algorithmic Decisions at the Crossroads of Intellectual Property, Data Protection, and Freedom of Information by Dr Guido Noto La Diega, Senior Lecturer in Law at the Northumbria University Law School Published in JIPITEC (Journal…
Why data is never raw
“Except in divine revelation, data is never simply given, nor should it be accepted on faith,” writes Nick Barrowman in The New Atlantis. “How data are construed, recorded, and collected is the result of human decisions – decisions about what…
What are Europe’s rules for democratic artificial intelligence?
Vincenzo Tiani has written an excellent summary in Wired Italia of the recently published “Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations“, by AI4People, a task force of European experts. With the help of DeepL (also…
[Book] Uberland: How Algorithms Are Rewriting The Rules Of Work
Uberland: How Algorithms Are Rewriting The Rules Of Work by Alex Rosenblat University of California Press October 2018, 296 pages Silicon Valley technology is transforming the way we work, and Uber is leading the charge. An American startup that promised…
Nissan digging deep into human behavior for autonomy
Just about every automaker in the world is enlisting experts from a variety of fields outside engineering and design to help them develop autonomous vehicles. One of the best known is Nissan’s Melissa Cefkin. Her official title is principal researcher-Human…