Storyteller-ede

I do know, however, from my observations, that the tiny funny dog upstairs is called Gucio. I've passed him once or twice during his walk and heard his owners use the name - and, while both the dog and his owners are oblivious to our existence, Gucio became an apt topic of discussion in our house. you know, we hear barking, ha, that's Gucio, he must be home alone again! or there's a stick left by the building door, that must have been brought by Gucio and he was forced to abandon it before entering! a household name, really.

yesterday as I was leaving to go to the store, walking down the narrow staircase, there he is! tiny funny looking dog, slightly startled by me suddenly appearing on the floor he just reached on his tiny funny looking legs.

"good morning Gucio!" I say joyfully, the most natural thing in the world.

well. remember that Gucio doesn't really know me. so he looks at me in the most flabbergasted way a dog can look at a person. he is positively aghast. agog! not sure how aware dogs are of their own names but he seemed genuinely puzzled at the apparent stretch of social convention.

and as I try to contain my laughter, I see his owner standing on the stairs below. the woman is sort of awkwardly frozen, speechless, and she looks at me.

"you... know each other?" she asks.

it's become impossible to ignore the discourse around so-called 'AI'. but while the bulk of the discourse is saturated with nonsense such as, i wanted to pool some resources to get a good sense of what this technology actually is, its limitations and its broad consequences. 

what is 'AI'

the best essay to learn about what i mentioned above is On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? this essay cost two of its collaborators to be fired from Google. it frames what large-language models are, what they can and cannot do and the actual risks they entail: not some 'super-intelligence' that we keep hearing about but concrete dangers: from climate, the quality of the training data and biases - both from the training data and from us, the users. 

The problem with artificial intelligence? It’s neither artificial nor intelligent

How the machine ‘thinks’: Understanding opacity in machine learning algorithms

The Values Encoded in Machine Learning Research

Troubling Trends in Machine Learning Scholarship: Some ML papers suffer from flaws that could mislead the public and stymie future research

AI Now Institute 2023 Landscape report (discussions of the power imbalance in Big Tech)

ChatGPT Is a Blurry JPEG of the Web

Can we truly benefit from AI?

Inside the secret list of websites that make AI like ChatGPT sound smart

The Steep Cost of Capture

labor

'AI' champions the facade of non-human involvement. but the truth is that this is a myth that serves employers by underpaying the hidden workers, denying them labor rights and social benefits - as well as hyping-up their product. the effects on workers are not only economic but detrimental to their health - both mental and physical.

OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic

also from the Times: Inside Facebook's African Sweatshop

The platform as factory: Crowdwork and the hidden labour behind artificial intelligence

The humans behind Mechanical Turk’s artificial intelligence

The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

The real aim of big tech's layoffs: bringing workers to heel

The Exploited Labor Behind Artificial Intelligence

workers surveillance

5 ways Amazon monitors its employees, from AI cameras to hiring a spy agency

Computer monitoring software is helping companies spy on their employees to measure their productivity – often without their consent

theft of art and content

Artists say AI image generators are copying their style to make thousands of new images — and it's completely out of their control  (what gives me most hope about regulators dealing with theft is Getty images' lawsuit - unfortunately individuals simply don't have the same power as the corporation)

Copyright won't solve creators' Generative AI problem

The real aim of big tech's layoffs: bringing workers to heel

The Exploited Labor Behind Artificial Intelligence

AI is already taking video game illustrators’ jobs in China

Microsoft lays off team that taught employees how to make AI tools responsibly/As the company accelerates its push into AI products, the ethics and society team is gone

150 African Workers for ChatGPT, TikTok and Facebook Vote to Unionize at Landmark Nairobi Meeting

Inside the AI Factory: the Humans that Make Tech Seem Human

Refugees help power machine learning advances at Microsoft, Facebook, and Amazon

Amazon’s AI Cameras Are Punishing Drivers for Mistakes They Didn’t Make

China’s AI boom depends on an army of exploited student interns

political, social, ethical consequences

Afraid of AI? The startups selling it want you to be

An Indigenous Perspective on Generative AI

“Computers enable fantasies” – On the continued relevance of Weizenbaum’s warnings

‘Utopia for Whom?’: Timnit Gebru on the dangers of Artificial General Intelligence

Machine Bias

HUMAN_FALLBACK

AI Ethics Are in Danger. Funding Independent Research Could Help

AI Is Tearing Wikipedia Apart  

AI machines aren’t ‘hallucinating’. But their makers are

The Great A.I. Hallucination (podcast)

“Sorry in Advance!” Rapid Rush to Deploy Generative A.I. Risks a Wide Array of Automated Harms

The promise and peril of generative AI

ChatGPT Users Report Being Able to See Random People's Chat Histories

Benedetta Brevini on the AI sublime bubble – and how to pop it   

Eating Disorder Helpline Disables Chatbot for 'Harmful' Responses After Firing Human Staff

AI moderation is no match for hate speech in Ethiopian languages

Amazon, Google, Microsoft, and other tech companies are in a 'frenzy' to help ICE build its own data-mining tool for targeting unauthorized workers

Crime Prediction Software Promised to Be Free of Biases. New Data Shows It Perpetuates Them

The EU AI Act is full of Significance for Insurers

Proxy Discrimination in the Age of Artificial Intelligence and Big Data

Welfare surveillance system violates human rights, Dutch court rules

Federal use of A.I. in visa applications could breach human rights, report says

Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI

Generative AI Is Making Companies Even More Thirsty for Your Data

environment

The Generative AI Race Has a Dirty Secret

Black boxes, not green: Mythologizing artificial intelligence and omitting the environment

Energy and Policy Considerations for Deep Learning in NLP

AINOW: Climate Justice & Labor Rights

militarism

The Growing Global Spyware Industry Must Be Reined In

AI: the key battleground for Cold War 2.0?

‘Machines set loose to slaughter’: the dangerous rise of military AI

AI: The New Frontier of the EU's Border Extranalisation Strategy

The A.I. Surveillance Tool DHS Uses to Detect ‘Sentiment and Emotion’

organizations

AI now

DAIR

podcast episodes

Pretty Heady Stuff: Dru Oja Jay & James Steinhoff guide us through the hype & hysteria around AI

Tech Won't Save Us: Why We Must Resist AI w/ Dan McQuillan, Why AI is a Threat to Artists w/ Molly Crabapple, ChatGPT is Not Intelligent w/ Emily M. Bender

SRSLY WRONG: Artificial Intelligence part 1, part 2

The Dig: AI Hype Machine w/ Meredith Whittaker, Ed Ongweso, and Sarah West

Download all your sources or print them so you can turn off your wifi

Give your phone to someone

Just. WRITE. Writing is analysing, you’ll get more ideas as you write. It doesn’t need to be perfect, for now you can just blurt out words and ideas randomly. You can fix it later.

Create a skeleton/structure before writing.

Stop before you get exhausted. It’s best to stop writing when you still have some energy and inspiration left, this will also motivate you to get started again next time.

Make a to do list

Work in bite sizes. Even if it’s not much, as long as you put some ideas on paper or do some editing.

Simple language =/= boring language, simple language = clear language.

Own your words. If they are not your words, state this clearly in the text, not just in the footnotes.