“instituting a “duty of care” for AI developers to “prevent and mitigate foreseeable harm to users” (per Blackburn’s summary of the bill). This duty would be enforced by the Federal Trade Commission (FTC).
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“It’s basically just an invitation for lawyers to sue any time anything bad happens and someone involved in the bad thing that happened somehow used an AI tool at some point.
And then you have to go through a big expensive legal process to explain “no, this thing was not because of AI” or whatever. It’s just a massive invitation to sue everyone, meaning that in the end you have just a few giant companies providing AI because they’ll be the only ones who can afford the lawsuits.”
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Section 11 of Blackburn’s bill is promoted as combating “the consistent pattern of bias against conservative figures demonstrated by Big Tech and AI systems.” But, in practice, it could require AI systems to have a pro-conservative slant—at least as long as President Donald Trump or other Republicans are in power.
The bill would set up “audits of high-risk AI systems to undergo regular bias evaluations to prevent discrimination based on protected characteristics, including political affiliation.”
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“Right now, 230 lets platforms get frivolous lawsuits dismissed quickly at the motion to dismiss stage. This change would force every platform to go through lengthy, expensive litigation to prove they weren’t “facilitating” (an incredibly vague term) or “soliciting” third-party content that violates federal criminal law.
That’s gutting the main reason Section 230 exists. Instead of quick dismissals, you get discovery, depositions, and trials, all while someone argues that because your algorithm showed someone a post, you were “facilitating” whatever criminal content they claim to find.””
Chip restrictions on China appear to work because China is obsessed with asking US administrations to lift the restrictions, and because the Chinese companies say the restrictions slow their progress.
“The first giant leap backward has been a dangerous weakening of public data, the raw material required to train AI models. The federal government collects troves of data that families and businesses use every day — traffic patterns and census information, nutritional assessments and air quality reports, soil data and economic measures.
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the administration has spent months ordering agency after agency to delete or hide data that’s politically inconvenient, and indiscriminately firing employees including those who manage valuable datasets.
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Initial research shows the eye-popping potential for AI weather forecasts that could be precise down to a city block or accurate as far ahead as a month. But that’s only possible with the sensor data that the National Oceanic and Atmospheric Administration (NOAA) collects and curates from weather stations, ships, balloons, aircraft, satellites and buoys. The Trump administration has reduced weather balloon launches and removed hundreds of agency staff. It plans to cut back on NOAA satellites and shutter more than a dozen facilities that gather and curate data.
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The Trump administration has also disrupted the collection of important health data. One example is data the Centers for Disease Control and Prevention gathered for nearly four decades from a representative sample of volunteers to understand risks in pregnancy. That valuable data now remains scattered and hard to access, because the CDC first shuttered the database to avoid collecting data on race and ethnicity in line with the administration’s executive order against “DEI,” and then placed the staff on administrative leave. That makes it harder to learn why Black maternal mortality is more than twice the national average, or how to protect all mothers and newborns. Data on vaccine safety, farm labor, hunger, greenhouse gas reporting and international development have also been deleted or degraded.
For AI to be effective against these immensely complex challenges, the smarter move would have been to expand data collection and support the agency staff who make sure datasets are robust and accessible.
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With steady support from Congress over successive administrations, eight decades of federal research funding made it possible to start new industries, prevent and cure diseases, deter potential adversaries, understand and start to manage environmental risks and expand the boundaries of human knowledge. This research base is where AI itself came from, and to harness AI for the next generation of advances, federal support is essential.
Instead, the Trump administration has frozen grants, attacked leading research universities, curtailed high-talent immigration, ousted thousands of research agency staff and proposed a $44 billion reduction in federally funded research and development — the largest single-year cut in history.
While some take solace in the administration’s cuts sparing specific budget lines for AI research and the new executive order for Energy Department research using AI, that’s like buying more tractors while you kill off your crops. AI is a tool, not the goal itself. The federal government needs to fund not just AI researchers, but researchers in the full range of promising fields that need AI to advance”
Trump’s Saudi Arabia deal may be a lie. Multiple countries have promised to invest big money in the U.S. in deals with Trump, and many have not materialized. Is this a real deal, or a misleading press release?
Even if they were real people, it would be misleading to cherry pick certain people out of the many losing benefits and present this like it is representative of who is losing benefits. 2/2
‘47,000 gun deaths occurred in the United States last year, 7 times more than that of all Europe combined. Five trans people participated in women’s sports.’
“Almost all of the AI models showed a preference to escalate aggressively, use firepower indiscriminately and turn crises into shooting wars — even to the point of launching nuclear weapons. “The AI is always playing Curtis LeMay,” says Schneider, referring to the notoriously nuke-happy Air Force general of the Cold War. “It’s almost like the AI understands escalation, but not de-escalation. We don’t really know why that is.””