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By Iretiolu Akinrinade & Joan Mukogosi | Despite the prevalence of strategic ignorance inside social media and gaming companies, today’s teen tech users have developed a number of creative and often hilarious strategies to make sure that they are seen, heard, and valued online.

By Katherine Miller | A Stanford researcher advocates for clarity about the different types of interpretability and the contexts in which it is useful.

From Daniel Leufer and AI Myths team (Mozilla Fellowshop Project) | With every genuine advance in the field of ‘artificial intelligence,’ we see a parallel increase in hype, myths, misconceptions and inaccuracies. These misunderstandings contribute to the opacity of AI systems, rendering them magical, inscrutable and inaccessible in the eyes of the public.

By Nathalie Heynderickx and Leonard Hoon, PhD | A call to action to start conversations on AI governance, this manifesto highlights three questions for starting this dialogue.

Kate Crawford, who holds positions at USC and Microsoft, says in a new book that even experts working on the technology misunderstand AI.

On April 21, 2021, the European Commission published its Proposal for a Regulation on Artificial Intelligence. The European Commission’s…

From Reaktor's Everyday AI Insight | How can AI become better at helping us discover what we want at any given time when our moods and expectations of an answer change all the time?

by Josh Lovejoy | Jan, 2021 | UX Collective

Be user centric, stay focused, maintain a healthy give-and-take relationship. Get data.

By Elaine Lee | You may not know it, but as a product designer, you most likely have been designing for products that use some form of artificial intelligence.

Op-ed: Many methods have been developed to promote fairness, transparency and accountability in the predictions made by artificial intelligence and machine learning systems. A technical approach is often the focal point of these methodologies, however, to develop truly ethical machine learning systems that can be trusted by their users, it's important to supplement this with a human-centred approach.

Thryn Shapira discusses balancing user control and automation in AI-powered reminiscing features.

Human intelligence emerges from our combination of senses and language abilities. Maybe the same is true for artificial intelligence.

Understand what AI is, and the jobs & aspects of work most likely to be automated by AI, so you know how to position yourself for the…

Heuristics and applied use cases to drive AI-powered experiences

By Daphne Milner via It's Nice That | Mainstream conversations around artificial intelligence, while sometimes characterised by a rhetoric of scientific progress, often deal with anxieties related to the tech. Critiquing its shortcomings is not enough, however. Art can help shape the future of artificial intelligence by exposing its limitations and tendencies to further systemic inequalities.

By fph | What if human data is de-humanized? What if technology restricts human agency? This speculative design work and reflection explores the digital culture that might emerge, while serving as a reminder of the necessity for human-machine collaboration.

by Kursat Ozenc via Ritual Design Lab | 6 Reflections on Stanford’s Culturally Relevant AI Summit

By Ben Syverson, IDEO | What happens when you invite GPT-3 to a virtual brainstorm session? A designer/developer at IDEO ran an experiment and wrote about it here!

By Stanford HAI | The AI Index Report tracks, collates, distills, and visualizes data relating to artificial intelligence to develop a deeper understanding of the complex field.

By ai-explanations (an ad-hoc feminist collective of digital rights researchers, design thinkers, artists, journalists and social media specialists) | "HOW is AI and digital technology shaping our realities, rights, justice, equality ? What are the harms? How can we counter these harms as individuals, communities, governments? What are we hopeful for and how can we fix or overthrow these systems together?"

AI outputs are fascinating, but lack empathy, creativity, and context. Because of this designers have the responsibility to design ethical…

By Rebecca Feibrink | A paper aiming to provide foundation for the research and practice of machine learning education for creative practitioners.