Congressional gridlock and competing legislative priorities have kept comprehensive federal AI safety legislation from advancing beyond committee stages. Bipartisan proposals, including the Obernolte-Trahan framework introduced in July 2026 and measures advanced by the House Science Committee in June, address transparency, incident reporting, and frontier model evaluation but face opposition over preemption of state laws, regulatory scope, and timing constraints ahead of midterms. Recent targeted bills on AI agents and superintelligence remain early-stage with limited support. Traders price in a low likelihood of enactment before 2027 because historical patterns show narrow AI provisions passing more readily than broad safety mandates, and the remaining session offers few clear paths through both chambers.
Experimental AI-generated summary referencing Polymarket data. This is not trading advice and plays no role in how this market resolves. · Updated10% chance
$102,026 Vol.
$102,026 Vol.
Dec 31, 2026
10% chance
$102,026 Vol.
$102,026 Vol.
Dec 31, 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. Congressional gridlock and competing legislative priorities have kept comprehensive federal AI safety legislation from advancing beyond committee stages. Bipartisan proposals, including the Obernolte-Trahan framework introduced in July 2026 and measures advanced by the House Science Committee in June, address transparency, incident reporting, and frontier model evaluation but face opposition over preemption of state laws, regulatory scope, and timing constraints ahead of midterms. Recent targeted bills on AI agents and superintelligence remain early-stage with limited support. Traders price in a low likelihood of enactment before 2027 because historical patterns show narrow AI provisions passing more readily than broad safety mandates, and the remaining session offers few clear paths through both chambers.
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.
Market Opened: Nov 12, 2025, 5:08 PM ET
Volume
$102,026End Date
Jan 1, 2027Market Opened
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. Congressional gridlock and competing legislative priorities have kept comprehensive federal AI safety legislation from advancing beyond committee stages. Bipartisan proposals, including the Obernolte-Trahan framework introduced in July 2026 and measures advanced by the House Science Committee in June, address transparency, incident reporting, and frontier model evaluation but face opposition over preemption of state laws, regulatory scope, and timing constraints ahead of midterms. Recent targeted bills on AI agents and superintelligence remain early-stage with limited support. Traders price in a low likelihood of enactment before 2027 because historical patterns show narrow AI provisions passing more readily than broad safety mandates, and the remaining session offers few clear paths through both chambers.
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
$102,026End Date
Jan 1, 2027Market Opened
Nov 12, 2025, 5:08 PM ETResolver
0x65070BE91...Congressional gridlock and competing legislative priorities have kept comprehensive federal AI safety legislation from advancing beyond committee stages. Bipartisan proposals, including the Obernolte-Trahan framework introduced in July 2026 and measures advanced by the House Science Committee in June, address transparency, incident reporting, and frontier model evaluation but face opposition over preemption of state laws, regulatory scope, and timing constraints ahead of midterms. Recent targeted bills on AI agents and superintelligence remain early-stage with limited support. Traders price in a low likelihood of enactment before 2027 because historical patterns show narrow AI provisions passing more readily than broad safety mandates, and the remaining session offers few clear paths through both chambers.
Experimental AI-generated summary referencing Polymarket data. This is not trading advice and plays no role in how this market resolves. · Updated
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