The countdown has begun for The PublicSpaces Conference: For a Collective Internet, set to take place on June 27 and 28. Emma Yedema, editor and producer at PublicSpaces, sat down with Abdo Hassan for an interview.

To further the understanding of training data, the Knowing Machines Project developed SeeSet, an investigative tool for examining the training datasets for AI. Here you will find nine essays from individual members of our team. Each one uses SeeSet to explore a key AI dataset and its role in the construction of 'ground truth.'

This anthology was curated from stories of living with data and AI in/from the majority world, narrated at a storytelling workshop in October 2021 organized by Data & Society Research Institute.

Symbolic language can help us grasp the nature and power of what is coming

How many humans does it take to make tech seem human? Millions.

🔬 Research Summary by Elizabeth Seger, PhD, a researcher at the Centre for the Governance of AI (GovAI) in Oxford, UK, investigating beneficial AI model-sharing norms and practices.

Collected data and analysis from a large survey of machine learning researchers.

The machines that nudge us can be nudged back: Here are some ideas on how to steer them.

How AI misrepresents culture through a facial expression. "For the diversity of human expression to survive algorithmic hegemony."

Her new organization, DAIR, will raise the alarm about how AI is being deployed today and use AI to speak truth to power.

Workers’ fear of new artificial intelligence technology makes sense: that technology has the potential to eliminate their jobs. But if we didn’t live under capitalism, AI could be used to liberate us from drudgery rather than hurl us into poverty.

It has only been a little under four months since ChatGPT came out, and yet I already feel super behind in publishing this story. I guess…

Machine Bias explore the unconscious bias built into AI systems and map potential strategies for a more inclusive tech landscape.

With this write-up, I want to outline my current thinking around large language models like OpenAI's chatGPT.

OpenAI’s chatbot offers paraphrases, whereas Google offers quotes. Which do we prefer?

Stephen Wolfram explores the broader picture of what's going on inside ChatGPT and why it produces meaningful text. Discusses models, training neural nets, embeddings, tokens, transformers, language syntax.

A visual history of artificial neural networks from 1943 to 2020

Proving you're a human on a web flooded with generative AI content

Nora N. Khan assembles a cast of luminaries to consider the far-reaching implications of AI and computational culture. –$40

Every dataset communicates a different perspective. When you shift your perspective, your conclusions can shift, too.

Demanding inclusive and radically diverse digital futures

I was on a panel tonight discussing Ethics in Design Research. I’m on a lot of panels about design and ethics because I’ve worked in AI…