@DocDrei
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Still Dré...still here. Award-winning author: https://nitter.cf/t.co/5R34Y7ciE2. BlackTwitter: https://nitter.cf/t.co/24rae5GPrJ. CTDA: https://nitter.cf/t.co/ImiL7H30kg.
Atlanta, GA
Joined March 2008
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I am SO honored to included in this dope-ass project!!
criticalminded.org/ presents:
“Liner Notes: A Critic’s Notebook”
led by Shamira Ibrahim and available for download here: criticalminded.org/downloads…
Wanna see a STACKED roster of culture writers (i don’t count LOL) ???
thot leedurr retweeted
Instead of clear eyed, fact based opinions like this one, politicians like Bernie Sanders are taking their cues from literal dooms day eugenicist cults, and so many on the 'left' are taking their cues from him.
Listen to this instead 👇👇👇
Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure.
1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity.
2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same.
As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed."
3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: ftc.gov/news-events/news/pre…).
Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead.
4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible.
this.weekinsecurity.com/doze…
ftc.gov/news-events/news/pre…
5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.
thot leedurr retweeted
Replying to @linamkhan
and let’s not forget about this:
“if the FTC finds that a company trained an LLM on improperly obtained data, then it will have to delete all the information along with the products developed from the ill-gotten data.”
👀 @timnitGebru
cyberscoop.com/ftc-algorithm…
thot leedurr retweeted
Law enforcers already have authority to charge companies and their CEOs for creating and releasing dangerous, unvetted, or defective products. We shouldn’t let discussions about new legal regimes distract from the fact that there’s no AI exemption from laws already on the books — a point @FTC emphasized repeatedly during my tenure.
1. There is an extensive set of laws that govern dangerous and defective products. For example, releasing unvetted AI models or agents can violate consumer protection laws. Shipping flawed AI tools without implementing adequate measures to detect and stop rogue or defective AI agents can be an “unfair or deceptive” act or practice under the FTC Act (and analogous state laws). And some state AGs are already exploring holding AI firms and their CEOs criminally liable when their models participate in criminal activity.
2. Existing laws also prohibit “unfair methods of competition.” This covers instances where AI firms appropriate the competitively sensitive information of their customers, including through tracking their use of various tools. It can also cover instances where firms pursue dangerous behavior, aware that doing so may compel rivals to do the same.
As the Supreme Court has noted: “A method of competition which casts upon one's competitors the burden of the loss of business unless they will descend to a practice which they are under a powerful moral compulsion not to adopt, even though it is not criminal, was thought to involve the kind of unfairness at which the [unfair methods of competition] statute was aimed."
3. The highly concentrated and interconnected structure of these markets could be creating major risks and conflicts of interest. We had started investigating these partnerships and cross-investments across the stack (and released a preliminarily overview of some findings: ftc.gov/news-events/news/pre…).
Both federal and state enforcers should be scrutinizing these opaque relationships and inter-dependencies. We are already seeing how these relationships could undermine accountability. For example, OpenAI could face liability given the Hugging Face incident, but Hugging Face being bought up by Nvidia means that we’re unlikely to see it file a lawsuit over this — given Nvidia’s strong incentive to see OpenAI continue full speed ahead.
4. As AI tools dramatically change the landscape of cybersecurity risks and hacks, all businesses should be doubling down on having core security protections in place. Firms that fail to invest in adequate data security measures or fix known vulnerabilities can also be breaking the law. A recent analysis showed that around 1/3 of Fortune 100 companies do not even have a way to notify them about security issues. During my @FTC tenure, we sued firms for poor data security practices and held CEOs liable when they were personally responsible.
this.weekinsecurity.com/doze…
ftc.gov/news-events/news/pre…
5. As policymakers consider new legal regimes, we should be looking to lessons from prior efforts to govern major sectors, such as banking and other networks, platforms, and utilities. Tools like structural separations, nondiscrimination, and supervision could be key, and there’s a rich history of what works and what doesn’t. But we can and must pursue any new efforts alongside enforcing existing laws.
“Failed to organize”
Fam…they deliberately ignore everything I’ve said or written about AI while excluding me from conversations and seminars held on campus
I’ve given a keynote at ACM FAccT and GT acts like I don’t know wtf I’m talking about.
Replying to @Tyler_A_Harper
Of the many reasons I have doubts that higher ed can be saved, the biggest is that it couldn’t even be mustered to its own defense when confronted with the gravest threat in its history. Faculty failed to organize against AI on campus and admins can’t welcome it fast enough. 4/
This is bars, honestly
thot leedurr retweeted
🚨Live leak of Black man leaving court after saying 🗣️🎙️“the white bitch guilty”‼️🤣🤣🤣🤣
thot leedurr retweeted
'Black Twitter served as a significant means to clawback some of the negative narratives that mainstream media has always propagated about the Black community. Dr. Meredith D. Clark, conducts an ethnographic investigation of Black Twitter through news media analysis and in-depth interviews to put forth a theory of Black Digital Resistance.'
youtube.com/watch?v=GUvSEX1a… | @LeftOfBlack
thot leedurr retweeted
the work done by people like @veenadubal and Katie Wells is some of the best not just articulating outrage but trying to point towards a different political and moral economy. we are building a monstrous future and it escapes our notice because it is built experiment by experiment on those of us who are the most vulnerable to this sort of predation—that is, before it's eventually turned on the rest of us! dissentmagazine.org/article/…
thot leedurr retweeted
Woke up with the nice news that my @cambUP_History book The Gift: How Objects of Prestige Shaped the Atlantic Slave Trade and Colonialism (2024) is one a joint runner-up of the @ASAUK_News Book Prize. Congratulations to winner Tosin Gbogi and co runner-up Nana Osei Quarshie!
thot leedurr retweeted
Nearly 30 incarcerated men sent $4,000 to a Kansas school district to pay off their school lunch debt.
This will read like a "feel good" story to some, but it is actually the greatest damnation of the capitalist state's ability to meet anyone's needs.
actionnews5.com/2026/09/04/p…
thot leedurr retweeted
thot leedurr retweeted
🦔An NYU mathematician says OpenAI used his own progress against him to beat him to one of the biggest unsolved problems in mathematics. Tristan Buckmaster had been working toward a Millennium Prize proof using OpenAI's Codex when information about his progress reached OpenAI.
Days later, OpenAI published a full proof of the same problem using the same uncommon approach, after burning $22.5 million in compute to get there. When Buckmaster confronted them, exec Sébastien Bubeck allegedly said "Why would you ruin your career?" and "If you don't want me to be nice, then I don't have to be nice."
My Take
OpenAI spent $22.5 million to solve a problem with a $1 million prize. They didn't do this for the bounty. They needed a headline that says "our AI solved one of the hardest problems in mathematics" and they needed it before someone else got credit. They started days after they heard about Buckmaster's progress and took the same uncommon approach he'd pursued for months. That's hard to explain as coincidence.
Buckmaster did his work inside Codex. OpenAI reserves the right to train on Codex data. They admit they can't rule out that his usage helped improve their models. So a customer used their product, potentially handed them the roadmap, and then OpenAI outran him with $22.5 million in compute he could never match. I don't know if any of this was intentional. But if you're a researcher and you just watched this happen, I don't think you'd keep your best ideas inside someone else's product.
Hedgie🤗
techcrunch.com/2026/09/08/op…
thot leedurr retweeted
3. The ironic thing with him mentioning climate change is that Open AI + Anthropic + friends's narratives is that data centers actually killing the planet are a distraction from the dangers of the magical "civilization building" models they're building.
theatlantic.com/ideas/2026/0…
thot leedurr retweeted
1. Read a blow by blow of what actually happened if you want to learn the facts. If you still want to believe in fantastical fairytales after that, then well I can't help.
mail.cyberneticforests.com/m…