**Bipartisan but limited House Science Committee action in June 2026 advanced narrower AI measures on research infrastructure, NIST safety evaluation centers, incident reporting, labeling, and workforce development, while a more ambitious Obernolte-Trahan framework for frontier-model transparency, independent audits, and deployment restrictions stalled amid disputes over state-law preemption.** With the legislative calendar shortened by the approaching midterms and must-pass funding measures, comprehensive safety legislation faces steep procedural and political barriers. Recent Senate activity has centered on narrower child-protection provisions rather than broad federal rules. Traders therefore assign an 88.5% implied probability that no comprehensive AI safety bill will clear both chambers and be enacted before 2027, reflecting the gap between targeted committee progress and the consensus requirements for major regulatory legislation.
Resumo experimental gerado por IA com dados do Polymarket. Isto não é aconselhamento de trading e não tem qualquer papel na resolução deste mercado. · AtualizadoSim
12% chance
$101,934 Vol.
$101,934 Vol.
31 dez 2026
Sim
12% chance
$101,934 Vol.
$101,934 Vol.
31 dez 2026
This market will resolve to "Yes" if a bill that includes at least one of the following provisions is signed into federal law in the United States by December 31, 2026, 11:59 PM ET.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used. **Bipartisan but limited House Science Committee action in June 2026 advanced narrower AI measures on research infrastructure, NIST safety evaluation centers, incident reporting, labeling, and workforce development, while a more ambitious Obernolte-Trahan framework for frontier-model transparency, independent audits, and deployment restrictions stalled amid disputes over state-law preemption.**
With the legislative calendar shortened by the approaching midterms and must-pass funding measures, comprehensive safety legislation faces steep procedural and political barriers. Recent Senate activity has centered on narrower child-protection provisions rather than broad federal rules. Traders therefore assign an 88.5% implied probability that no comprehensive AI safety bill will clear both chambers and be enacted before 2027, reflecting the gap between targeted committee progress and the consensus requirements for major regulatory legislation.
This market will resolve to "Yes" if a bill that includes at least one of the following provisions is signed into federal law in the United States by December 31, 2026, 11:59 PM ET.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used.
Mercado Aberto: Nov 12, 2025, 5:08 PM ET
Volume
$101,934Data de Término
1 jan 2027Mercado Aberto
Nov 12, 2025, 5:08 PM ETResolver
0x65070BE91...This market will resolve to "Yes" if a bill that includes at least one of the following provisions is signed into federal law in the United States by December 31, 2026, 11:59 PM ET.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used. **Bipartisan but limited House Science Committee action in June 2026 advanced narrower AI measures on research infrastructure, NIST safety evaluation centers, incident reporting, labeling, and workforce development, while a more ambitious Obernolte-Trahan framework for frontier-model transparency, independent audits, and deployment restrictions stalled amid disputes over state-law preemption.**
With the legislative calendar shortened by the approaching midterms and must-pass funding measures, comprehensive safety legislation faces steep procedural and political barriers. Recent Senate activity has centered on narrower child-protection provisions rather than broad federal rules. Traders therefore assign an 88.5% implied probability that no comprehensive AI safety bill will clear both chambers and be enacted before 2027, reflecting the gap between targeted committee progress and the consensus requirements for major regulatory legislation.
This market will resolve to "Yes" if a bill that includes at least one of the following provisions is signed into federal law in the United States by December 31, 2026, 11:59 PM ET.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used.
- Prohibition on Creation or Release: Forbids the creation or release of specific AI systems or models.
- Training Restrictions: Sets limits on how AI systems can be trained, such as restricting access to previously available training data or imposing a maximum limit on the number of parameters used for training.
- Usage Restrictions: Prevents AI systems from being used in certain applications, such as interacting with customers, interfacing with other applications, or performing actions on the web.
- Human-in-the-Loop Requirements: Requires AI systems to include mechanisms ensuring human oversight or involvement in their operation.
Otherwise this market will resolve to "No".
The resolution source will be official U.S. federal government (e.g., Congress.gov) however a consensus of credible reporting may also be used.
Volume
$101,934Data de Término
1 jan 2027Mercado Aberto
Nov 12, 2025, 5:08 PM ETResolver
0x65070BE91...**Bipartisan but limited House Science Committee action in June 2026 advanced narrower AI measures on research infrastructure, NIST safety evaluation centers, incident reporting, labeling, and workforce development, while a more ambitious Obernolte-Trahan framework for frontier-model transparency, independent audits, and deployment restrictions stalled amid disputes over state-law preemption.** With the legislative calendar shortened by the approaching midterms and must-pass funding measures, comprehensive safety legislation faces steep procedural and political barriers. Recent Senate activity has centered on narrower child-protection provisions rather than broad federal rules. Traders therefore assign an 88.5% implied probability that no comprehensive AI safety bill will clear both chambers and be enacted before 2027, reflecting the gap between targeted committee progress and the consensus requirements for major regulatory legislation.
Resumo experimental gerado por IA com dados do Polymarket. Isto não é aconselhamento de trading e não tem qualquer papel na resolução deste mercado. · Atualizado
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