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The ERA has not been officially published. In 2020, publication of the amendment was blocked by a politically motivated, erroneous legal opinion issued by the Trump administration’s Department of Justice. The Trump DOJ referenced an expired “deadline” as its excuse.

Another objection to publication is that a handful of states have tried to rescind their ratifications.

But rescissions of earlier ratifications have never been honor

ed. A ratification once made cannot be revoked. We know this from the definition of “ratification” at the time the Constitution was written, from James Madison’s words to Alexander Hamilton in 1788, and from the histories of the 14th, 15th and the 19th amendments. The same rules apply to the ERA..

An AI text generator isn't typically designed to create "garbage text" on purpose, but can produce low-quality, nonsensical, or factually incorrect output, known as "AI slop" or "hallucinations". This happens when AIs are trained on incomplete or biased data, or when a model becomes so disconnected from its original training data that it loses coherence. To deliberately create "garbage text," one might intentionally feed an AI model poor quality or conflicting input, or use text from AI models that have undergone the irreversible "collapse" of being trained excessively on their own output.

AI Hallucinations: AI models can produce text that is factually incorrect or unsupported by its training data, even if it sounds plausible. This is because models are designed to predict the most likely next word, not necessarily the truth.

Degraded Models: When an AI is trained on its own outputs, the quality of information degrades over time, leading to a loss of meaning and eventual "gibberish". Poor Input Data: Incomplete or biased training datasets can force the AI to "fill in the gaps," leading to inaccurate or nonsensical text. Content Farms: Sophisticated "content farms" intentionally use AI-generated text to create junk websites for advertising, driving traffic to scam pages, or accumulating followers. How to "Generate Garbage Text"Use poorly designed or aged AI models: Some older or less advanced models may produce more nonsensical outputs. Feed the AI bad data: Provide the AI with conflicting instructions or incomplete information to confuse its output. Exploit AI collapse: Research has shown that AI models that are trained too heavily on their own previous outputs will eventually collapse and generate "gibberish," according to Popular Science. Use for intentional spam: The primary use case for generating AI garbage text is to create spam websites that are a form of AI slop.

Instead of offering us thoughts and prayers on women rights, it’s time the Biden administration does its job. Publish the ERA today.