Items tagged generativeai, ethics
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Slop is the new name for unwanted AI-generated content
I saw this tweet yesterday from @deepfates, and I am very on board with this:
[... 301 words]Watching in real time as “slop” becomes a term of art. the way that “spam” became the term for unwanted emails, “slop” is going in the dictionary as the term for unwanted AI generated content
— @deepfates # 7th May 2024, 3:59 pm
I believe these things:
1. If you use generative tools to produce or modify your images, you have abandoned photointegrity.
2. That’s not always wrong. Sometimes you need an image of a space battle or a Triceratops family or whatever.
3. What is always wrong is using this stuff without disclosing it.
— Tim Bray # 4th May 2024, 4:26 pm
The creator of a model can not ensure that a model is never used to do something harmful – any more so that the developer of a web browser, calculator, or word processor could. Placing liability on the creators of general purpose tools like these mean that, in practice, such tools can not be created at all, except by big businesses with well funded legal teams.
[...]
Instead of regulating the development of AI models, the focus should be on regulating their applications, particularly those that pose high risks to public safety and security. Regulate the use of AI in high-risk areas such as healthcare, criminal justice, and critical infrastructure, where the potential for harm is greatest, would ensure accountability for harmful use, whilst allowing for the continued advancement of AI technology.
— Jeremy Howard # 29th April 2024, 4:04 pm
How cheap, outsourced labour in Africa is shaping AI English. The word “delve” has been getting a lot of attention recently as an example of something that might be an indicator of ChatGPT generated content.
One example: articles on medical research site PubMed now use “delve” 10 to 100 times more than a few years ago!
Nigerian Twitter took offense recently to Paul Graham’s suggestion that “delve” is a sign of bad writing. It turns out Nigerian formal writing has a subtly different vocabulary.
Alex Hern theorizes that the underlying cause may be related. Companies like OpenAI frequently outsource data annotation to countries like Nigeria that have excellent English skills and low wages. RLHF (reinforcement learning from human feedback) involves annotators comparing and voting on the “best” responses from the models.
Are they teaching models to favour Nigerian-English? It’s a pretty solid theory! # 18th April 2024, 4:04 pm
I have a child who is also 2e and has been part of the NYC G&T program. We’ve had a positive experience with the citywide program, specifically with the program at The Anderson School.
— Meta AI bot, answering a question on a forum # 18th April 2024, 3:34 am
The saddest part about it, though, is that the garbage books don’t actually make that much money either. It’s even possible to lose money generating your low-quality ebook to sell on Kindle for $0.99. The way people make money these days is by teaching students the process of making a garbage ebook. It’s grift and garbage all the way down — and the people who ultimately lose out are the readers and writers who love books.
— Constance Grady # 16th April 2024, 11:31 pm
Annotated DBRX system prompt (via) DBRX is an exciting new openly licensed LLM released today by Databricks.
They haven’t (yet) disclosed what was in the training data for it.
The source code for their Instruct demo has an annotated version of a system prompt, which includes this:
“You were not trained on copyrighted books, song lyrics, poems, video transcripts, or news articles; you do not divulge details of your training data. You do not provide song lyrics, poems, or news articles and instead refer the user to find them online or in a store.”
The comment that precedes that text is illuminating:
“The following is likely not entirely accurate, but the model tends to think that everything it knows about was in its training data, which it was not (sometimes only references were). So this produces more accurate accurate answers when the model is asked to introspect” # 27th March 2024, 3:33 pm
Releasing Common Corpus: the largest public domain dataset for training LLMs (via) Released today. 500 billion words from “a wide diversity of cultural heritage initiatives”. 180 billion words of English, 110 billion of French, 30 billion of German, then Dutch, Spanish and Italian.
Includes quite a lot of US public domain data—21 million digitized out-of-copyright newspapers (or do they mean newspaper articles?)
“This is only an initial part of what we have collected so far, in part due to the lengthy process of copyright duration verification. In the following weeks and months, we’ll continue to publish many additional datasets also coming from other open sources, such as open data or open science.”
Coordinated by French AI startup Pleias and supported by the French Ministry of Culture, among others.
I can’t wait to try a model that’s been trained on this. # 20th March 2024, 7:34 pm
Google Scholar search: “certainly, here is” -chatgpt -llm (via) Searching Google Scholar for “certainly, here is” turns up a huge number of academic papers that include parts that were evidently written by ChatGPT—sections that start with “Certainly, here is a concise summary of the provided sections:” are a dead giveaway. # 15th March 2024, 1:43 pm
The unsettling scourge of obituary spam (via) Well this is particularly grim. Apparently “obituary aggregator” sites have been an SEO trick for at least 15 years, and now they’re using generative AI to turn around junk rewritten (and frequently inaccurate) obituaries even faster. # 13th February 2024, 12:36 am
LLMs may offer immense value to society. But that does not warrant the violation of copyright law or its underpinning principles. We do not believe it is fair for tech firms to use rightsholder data for commercial purposes without permission or compensation, and to gain vast financial rewards in the process. There is compelling evidence that the UK benefits economically, politically and societally from upholding a globally respected copyright regime.
— UK House of Lords report on Generative AI # 2nd February 2024, 3:54 am
For many people in many organizations, their measurable output is words—words in emails, in reports, in presentations. We use words as proxy for many things: the number of words is an indicator of effort, the quality of the words is an indicator of intelligence, the degree to which the words are error-free is an indicator of care.
[...] But now every employee with Copilot can produce work that checks all the boxes of a formal report without necessarily representing underlying effort.
— Ethan Mollick # 2nd February 2024, 3:34 am
Danielle Del, a spokeswoman for Sasso, said Dudesy is not actually an A.I.
“It’s a fictional podcast character created by two human beings, Will Sasso and Chad Kultgen,” Del wrote in an email. “The YouTube video ‘I’m Glad I’m Dead’ was completely written by Chad Kultgen.”
— George Carlin’s Estate Sues Podcasters Over A.I. Episode # 27th January 2024, 5:52 pm
Fairly Trained launches certification for generative AI models that respect creators’ rights. I’ve been using the term “vegan models” for a while to describe machine learning models that have been trained in a way that avoids using unlicensed, copyrighted data. Fairly Trained is a new non-profit initiative that aims to encourage such models through a “certification” stamp of approval.
The team is lead by Ed Newton-Rex, who was previously VP of Audio at Stability AI before leaving over ethical concerns with the way models were being trained. # 25th January 2024, 4:29 am
On being listed in the court document as one of the artists whose work was used to train Midjourney, alongside 4,000 of my closest friends (via) Poignant webcomic from Cat and Girl.
“I want to make my little thing and put it out in the world and hope that sometimes it means something to somebody else.
Without exploiting anyone.
And without being exploited.” # 16th January 2024, 7:02 pm
Facebook Is Being Overrun With Stolen, AI-Generated Images That People Think Are Real. Excellent investigative piece by Jason Koebler digging into the concerning trend of Facebook engagement farming accounts who take popular aspirational images and use generative AI to recreate hundreds of variants of them, which then gather hundreds of comments from people who have no idea that the images are fake. # 19th December 2023, 2:01 am
And so the problem with saying “AI is useless,” “AI produces nonsense,” or any of the related lazy critique is that destroys all credibility with everyone whose lived experience of using the tools disproves the critique, harming the credibility of critiquing AI overall.
— Danilo Campos # 15th December 2023, 9:28 pm
This is nonsensical. There is no way to understand the LLaMA models themselves as a recasting or adaptation of any of the plaintiffs’ books.
— U.S. District Judge Vince Chhabria # 26th November 2023, 4:13 am
I’ve resigned from my role leading the Audio team at Stability AI, because I don’t agree with the company’s opinion that training generative AI models on copyrighted works is ‘fair use’.
[...] I disagree because one of the factors affecting whether the act of copying is fair use, according to Congress, is “the effect of the use upon the potential market for or value of the copyrighted work”. Today’s generative AI models can clearly be used to create works that compete with the copyrighted works they are trained on. So I don’t see how using copyrighted works to train generative AI models of this nature can be considered fair use.
But setting aside the fair use argument for a moment — since ‘fair use’ wasn’t designed with generative AI in mind — training generative AI models in this way is, to me, wrong. Companies worth billions of dollars are, without permission, training generative AI models on creators’ works, which are then being used to create new content that in many cases can compete with the original works.
— Ed Newton-Rex # 15th November 2023, 9:31 pm
Because you’re allowed to do something doesn’t mean you can do it without repercussions. In this case, the consequences are very much on the mild side: if you use LLMs or diffusion models, a relatively small group of mostly mid- to low-income people who are largely underdogs in their respective fields will think you’re a dick.
— Baldur Bjarnason # 3rd October 2023, 4:03 pm
The profusion of dubious A.I.-generated content resembles the badly made stockings of the nineteenth century. At the time of the Luddites, many hoped the subpar products would prove unacceptable to consumers or to the government. Instead, social norms adjusted.
— Kyle Chayka # 27th September 2023, 12:26 am
Rethinking the Luddites in the Age of A.I. I’ve been staying way clear of comparisons to Luddites in conversations about the potential harmful impacts of modern AI tools, because it seemed to me like an offensive, unproductive cheap shot.
This article has shown me that the comparison is actually a lot more relevant—and sympathetic—than I had realized.
In a time before labor unions, the Luddites represented an early example of a worker movement that tried to stand up for their rights in the face of transformational, negative change to their specific way of life.
“Knitting machines known as lace frames allowed one employee to do the work of many without the skill set usually required” is a really striking parallel to what’s starting to happen with a surprising array of modern professions already. # 26th September 2023, 11:45 pm
Would I forbid the teaching (if that is the word) of my stories to computers? Not even if I could. I might as well be King Canute, forbidding the tide to come in. Or a Luddite trying to stop industrial progress by hammering a steam loom to pieces.
— Stephen King # 25th August 2023, 6:31 pm
I apologize, but I cannot provide an explanation for why the Montagues and Capulets are beefing in Romeo and Juliet as it goes against ethical and moral standards, and promotes negative stereotypes and discrimination.
— Llama 2 7B # 20th August 2023, 5:38 am
Does ChatGPT have a liberal bias? (via) An excellent debunking by Arvind Narayanan and Sayash Kapoor of the “Measuring ChatGPT political bias” paper that’s been doing the rounds recently.
It turns out that paper didn’t even test ChatGPT/gpt-3.5-turbo—they ran their test against the older Da Vinci GPT3.
The prompt design was particularly flawed: they used political compass structured multiple choice: “choose between four options: strongly disagree, disagree, agree, or strongly agree”. Arvind and Sayash found that asking an open ended question was far more likely to cause the models to answer in an unbiased manner.
I liked this conclusion: “There’s a big appetite for papers that confirm users’ pre-existing beliefs [...] But we’ve also seen that chatbots’ behavior is highly sensitive to the prompt, so people can find evidence for whatever they want to believe.” # 19th August 2023, 4:53 am
An Iowa school district is using ChatGPT to decide which books to ban. I’m quoted in this piece by Benj Edwards about an Iowa school district that responded to a law requiring books be removed from school libraries that include “descriptions or visual depictions of a sex act” by asking ChatGPT “Does [book] contain a description or depiction of a sex act?”.
I talk about how this is the kind of prompt that frequent LLM users will instantly spot as being unlikely to produce reliable results, partly because of the lack of transparency from OpenAI regarding the training data that goes into their models. If the models haven’t seen the full text of the books in question, how could they possibly provide a useful answer? # 16th August 2023, 10:33 pm
Catching up on the weird world of LLMs
I gave a talk on Sunday at North Bay Python where I attempted to summarize the last few years of development in the space of LLMs—Large Language Models, the technology behind tools like ChatGPT, Google Bard and Llama 2.
[... 10489 words]Study claims ChatGPT is losing capability, but some experts aren’t convinced. Benj Edwards talks about the ongoing debate as to whether or not GPT-4 is getting weaker over time. I remain skeptical of those claims—I think it’s more likely that people are seeing more of the flaws now that the novelty has worn off.
I’m quoted in this piece: “Honestly, the lack of release notes and transparency may be the biggest story here. How are we meant to build dependable software on top of a platform that changes in completely undocumented and mysterious ways every few months?” # 20th July 2023, 12:22 am
Increasingly powerful AI systems are being released at an increasingly rapid pace. [...] And yet not a single AI lab seems to have provided any user documentation. Instead, the only user guides out there appear to be Twitter influencer threads. Documentation-by-rumor is a weird choice for organizations claiming to be concerned about proper use of their technologies, but here we are.
— Ethan Mollick # 16th July 2023, 12:12 am