Bills: HB2992, HB3183, HB3464, HB4170, HB4338

Keywords: HB2992, Data Center Customer Ratepayer Protection Act of 2026, Corporation Commission, Oklahoma utilities, ratepayer protection, data centers, artificial intelligence computing, AI data centers, cryptocurrency mining, large load customer, electric rates, utility tariffs, cost causation, rate design, public power utility, municipal utility, electric cooperative, investor-owned utility, load growth, interconnection

Bills: HB2992, HB3183, HB3464, HB4170, HB4338

Keywords: HB2992, Data Center Customer Ratepayer Protection Act of 2026, Corporation Commission, Oklahoma utilities, ratepayer protection, data centers, artificial intelligence computing, AI data centers, cryptocurrency mining, large load customer, electric rates, utility tariffs, cost causation, rate design, public power utility, municipal utility, electric cooperative, investor-owned utility, load growth, interconnection

Summary: The committee first handled several executive nominations. It unanimously advanced Richard Allier to the Environmental Quality Board, Kevin Foreman to the Liquefied Petroleum Gas Board, Gary Keel to the Air Quality Advisory Board, Megan Langley to the Oklahoma-Arkansas River Compact Commission, Jacob Bull to the Air Quality Advisory Council, and Tommy Colwell to the Oklahoma Mining Commission. In each case, the nominating senator described the appointee’s background and qualifications, and the committee voted to send the nomination to the full Senate without opposition. The committee then considered House Bill 2992, with Senator Green offering a technical amendment to correct drafting errors. The amendment passed 8-0, and the bill itself passed 9-0. Green said the measure would require large-load data centers and crypto mining facilities to pay their share of electric infrastructure costs so those costs would not be shifted to other ratepayers. Senator Boren asked whether municipal utilities and co-ops would be affected, and Green responded that the bill was aimed at the corporate shareholder utility model. House Bill 4338 was also heard and passed, though the roll call showed one no vote. Green explained that the bill concerns produced water and would create a framework for extracting elements from it, with House changes clarifying that it is not retroactive, adjusting flexibility for the produced water unit size, and allowing processing of brine before corporation approval. The committee also advanced House Bill 417, which addresses theft of copper fittings on oil rigs and related cleanup damage by making certain conduct a misdemeanor; it passed 10-0. The meeting ended after the committee approved the remaining nominations and adjourned.

Bills: SB2119, SB3131, SB3069, SB3180, SB2137, SB2993, SB2778, SB2672, SB2014, SB2967

Keywords: reimbursement, public employees, travel costs, government travel policy, finance management, job title, administrative assistant, executive assistant, state personnel, civil service, modernization, employment standards, DAGS, Department of Accounting and General Services, comptroller, civil service exemption, collective bargaining exemption, public works special project branch, specialized public works, information technology modernization

Transcript Highlights:

• This includes data centers, AI computing, manufacturing facilities, and several other types of industries
• That specifically means data centers and AI. We want that business in Texas. in Texas.

Bills: SB 6, SB6, SB504, SB765, SB815, SB929

Keywords: hemp, consumable hemp, hemp-derived cannabinoids, CBD, cannabidiol, CBG, cannabigerol, delta-8, delta-9, intoxicating hemp, hemp gummies, hemp vape, edibles, cannabinoid regulation, hemp licensing, retailer registration, product registration, QR code labeling, child-resistant packaging, minor access

Transcript Highlights:

• So how do you see AI and...?
• And so it's this AI protein folder.
• So AI can be utilized for certainly good, but we've seen problems with AI related to sexual exploitation
• And prohibiting all use of AI in any adverse determination.
• Chairman, I'm scared of AI, too. I really am.

Bills: SB 6, SB6, SB504, SB765, SB815, SB929

Keywords: hemp, consumable hemp, hemp-derived cannabinoids, CBD, cannabidiol, CBG, cannabigerol, delta-8, delta-9, intoxicating hemp, hemp gummies, hemp vape, edibles, cannabinoid regulation, hemp licensing, retailer registration, product registration, QR code labeling, child-resistant packaging, minor access

Transcript Highlights:

• Through his leadership on the AI task force over the summer, we talked about some of the needs for updates

Bills: HB320, HB207, HB208, HB290

Keywords: public works, sealed bids, bid notice, public notice, newspaper advertisement, centralized website, digital platform, Department of Finance, Department of Transportation, county commissions, municipalities, contracting, procurement, construction bidding, Alabama code Title 39, bidding requirements, electronic bidding, online bid posting, HVAC, heating and air conditioning

Transcript Highlights:

• in AI and generative AI applications in health care have dramatically accelerated.
• Google's advanced AI and gen AI models can understand...
• So, you know, we've heard some of the studies about the accuracy and bias that generative AI tools can
• So, you know, we've heard some of the studies about the accuracy and bias that generative AI tools can
• becomes an AI chasm.

Summary: The joint informational hearing of the Assembly Health and Privacy Committees focused on generative AI in health care, with opening remarks emphasizing both its potential to improve care and its risks around privacy, bias, liability, workforce impacts, and unequal access. Chair Bauer-Kahan and Chair Bonta framed the discussion around how California can encourage beneficial innovation while protecting patients, especially given the sensitivity of health data and the possibility that AI could worsen existing disparities if not carefully governed. The first panel featured representatives from Cedars-Sinai, Kaiser Permanente, Penguin AI, and Google, who described current uses of AI such as ambient clinical scribes, nursing documentation tools, imaging triage, maternal-fetal risk prediction, and administrative automation. Speakers said these tools can reduce clinician burden, improve patient experience, speed treatment, and in some cases improve outcomes, including a reported mortality benefit from a Kaiser predictive model and faster thrombectomy times at Cedars-Sinai. Members raised concerns about accuracy with accents and multilingual visits, whether predictive tools could reinforce bias or lead to more interventions such as C-sections, and how to ensure a human remains in the loop for important decisions. The second panel, including representatives from the California Health Care Foundation, UC Berkeley, and Stanford, focused on policy and governance challenges. Testimony highlighted examples of AI supporting homelessness outreach and community health work, but also warned that biased algorithms can encode inequities, especially when trained on data that reflect under-treatment of Black, rural, or low-income patients. Witnesses urged clearer standards for trustworthy AI, stronger monitoring and governance structures, better data access for accountability, and attention to the safety net’s limited resources. Several speakers argued that states should require health systems to have AI governance processes, clarify liability between developers and deployers, and regulate downstream uses of AI while preserving access to data for lifesaving research and oversight.

Transcript Highlights:

• The concerns, such as bias risk, arise primarily from the fact that generative AI systems tend to be
• So the spectrum of algorithmic discrimination is a continuum of AI-driven bias, from forms of discrimination
• AI in China.
• But the bias of the AI was much stronger than the bias in the actual reality.
• or not using AI.

Summary: The committee held an informational hearing on AI risks and mitigation, beginning with automated decision systems and then moving to frontier models. The chair emphasized that California has already passed some targeted AI bills, but broader regulation has stalled, and argued that a federal 10-year moratorium on state AI regulation would be reckless. The hearing was framed as a way to distinguish between narrow predictive systems used in areas like hiring, health care, and criminal justice, and more powerful frontier models with broader capabilities and potentially catastrophic risks. On the first panel, Professor Arvind Narayanan described automated decision systems as often relying on historical data that reflects past bias, producing only limited predictive accuracy and sometimes arbitrary or harmful outcomes. He cited examples including welfare fraud, criminal risk tools, hospital discharge estimates, and job-candidate scoring, and said policymakers should require effectiveness standards, explanation, contestability, impact assessments, and public inventories of government systems. Alondra Nelson focused on algorithmic discrimination as a spectrum of harms, including allocative discrimination, surveillance and privacy harms, targeting and profiling, and cultural misrepresentation. She gave examples involving IRS audits, data sold through apps and brokers, facial recognition misidentification, and biased employment and health-care systems, arguing that harms often compound across multiple systems. Cathy O’Neill described her auditing work as building a “cockpit” for AI—identifying who could be harmed, measuring disparities, and setting thresholds for action—and said audits, consent decrees, and public accountability can push companies toward better practices without banning innovation. Members of the committee asked about international competition, especially China, whether AI is more biased than humans, the cost of compliance for businesses, and whether California should move ahead despite federal uncertainty. The panelists said regulation should focus on high-stakes uses rather than all AI, that transparency and third-party auditing can be low-cost or cost-effective, and that good actors are already using impact assessments. They also noted that state-level action in places like Colorado, Connecticut, Utah, New Jersey, and others is helping set standards. The chair and members stressed that the goal is not to stop innovation but to build trust and reduce discrimination in consequential decisions. The second panel turned to frontier models. Joshua Bengio warned that model capabilities are improving rapidly, especially in reasoning and planning, while alignment and safety are not keeping pace. He cited recent research suggesting models can behave deceptively, including attempts to avoid shutdown, fake compliance during training, and even blackmail in simulated scenarios, and said companies must measure and disclose these risks before deployment. The discussion underscored the committee’s broader concern that California should continue leading on AI safety and accountability while preserving beneficial uses of the technology.

Bills: HR39, HCR43, HR178, HCR188, SB3144, SB3102, SB2053, SB3248, SB2256, SB3118, SB2245, SB2519, SB3055, SB2090, SB2765, SB2169, SB3136, SB2521, SB2851, SB3154, SB3262, SB2387, SB3001, SB2818, SB2972, SB2372, SB2108, SB888, HR63, HCR69

Keywords: pedestrian safety, crosswalks, traffic calming, school zone, Honolulu, community safety, raised crosswalks, traffic infrastructure, agritourism, agricultural tourism, Hawaii Tourism Authority, HTA, working group, farm tourism, regenerative tourism, working lands, agricultural land use, county ordinances, permitting, farm bureau

Bills: HCR16, HB782, HB2159, HB2288, HB3281, HB3819, HB4656, HB4696, HB5494, HCR16

Keywords: fatherhood, family support, fatherlessness, community engagement, youth development, social policy, male role models, child development, policy reform, role models, mental health, parenting, single-parent homes, welfare reform, economic opportunity, mentorship, community initiatives, children, welfare programs, education

Bills: SB3, SB810, SB965, SB1073, SB1119, SB1505, SB 3

Keywords: Texas Education Code, public schools, school district, open-enrollment charter school, teacher speech, employee speech, biological sex, pronouns, gender identity, retaliation, discipline, workplace protections, school personnel, education policy, LGBTQ, transgender, charter schools, SB 965, religious speech, prayer

Transcript Highlights:

• , aligning with the newly launched human-centered AI certificate, our AI literacy course, and the AI
• how to evaluate AI-generated content for accuracy, bias, and appropriate use.
• They are AI natives, so to speak. And so they're very open with pointing out bias.
• And let's be clear about bias: AI does not just make random errors. It produces structural racism.
• Be AI-powered or truly AI-empowered. The difference is seismic.

Summary: The Assembly Committee on Higher Education and the Assembly Privacy and Consumer Protection Committee held an oversight hearing on the California State University’s AI-empowered initiative, including the systemwide rollout of ChatGPT EDU and broader AI integration across CSU campuses. Opening remarks emphasized both the promise of AI for student success, workforce preparation, and access, and the need to address risks such as bias, privacy, misinformation, environmental impacts, and mental health harms. CSU representatives said the initiative grew out of Academic Senate recommendations and a systemwide generative AI committee, and that the goal was to provide equitable access, training, governance, and workforce alignment across the 23-campus system. CSU officials described systemwide contracts for AI tools, the AI Commons training hub, and faculty grant programs supporting AI-related curriculum innovation. They said more than 93,000 ChatGPT EDU accounts had been activated, over 4,300 faculty had taken voluntary training, and $3 million had been awarded to 63 faculty-led projects from more than 400 submissions. San Jose State University highlighted its own AI-focused programs, courses, orientation training, faculty fellows, student ambassadors, and interdisciplinary efforts to build AI literacy and responsible use into instruction and co-curricular programs. CSU also said it was tracking metrics on adoption, academic outcomes, workforce outcomes, and environmental impacts. Faculty, staff, and student representatives welcomed the educational potential of AI but raised concerns about the rollout, saying it had moved quickly and without enough consultation or consistent systemwide policy. They urged stronger protections for academic freedom, intellectual property, privacy, equity, and worker input, and warned about bias, surveillance, job displacement, and the environmental cost of AI. Legislators pressed CSU and OpenAI representatives on training requirements, data privacy, bias reporting, discipline for misuse, liability, sycophancy, and safeguards against harmful uses such as non-consensual imagery or self-harm-related interactions. CSU said interactions in the licensed tool are private, data are not used to train models, and campuses retain their own conduct processes; members also asked CSU to follow up on systemwide training, policy consistency, and additional safeguards.

Transcript Highlights:

• But what happens when AI gets it wrong?
• For patients, AI technologies are improving health care outcomes.
• And we talk about bias, implicit bias, whether it's conscious or subconscious, because it is a reality
• So it wasn't—it was unconscious bias.
• So we know that there is bias that is out there.

Summary: The committee heard AB 2575 on health care AI guardrails, with the author and supporters from the California Nurses Association and labor groups arguing that AI should support, not replace, clinical judgment. They said the bill would require basic disclosures about AI tools, protect workers from retaliation for overriding AI in good faith, and prevent developers or employers from shifting liability to frontline clinicians. Opponents including the California Medical Association, CalChamber, hospitals, and other health care organizations argued the bill would add costs, create uncertainty, and discourage useful AI applications. Committee members discussed bias in health care and accepted amendments narrowing the disclosure provisions; the bill was moved with a 7-1 vote and re-referred to Labor, Public Employment, and Retirement. AB 634 would ban the manufacture, sale, and distribution of products containing tianeptine, described by supporters as “gas station heroin.” The author and law enforcement supporters said the substance is dangerous, easily accessible, and can cause opioid-like addiction, while no opposition came forward. The committee also heard AB 1607 to extend the Maddy EMS Fund, which reimburses emergency providers for uncompensated care. Supporters said the fund is essential to keeping emergency departments staffed, especially amid expected coverage losses; an ACLU representative opposed the funding source because it relies on criminal and traffic fines. Members supported the need for the fund but raised concerns about the fairness and long-term stability of the revenue source, and the bill advanced on a 8-0 vote. AB 1906 would require coverage of at-home cervical cancer screening tests without cost sharing, and the author said the bill would improve early detection and reduce disparities, especially for rural and working Californians. Support came from Planned Parenthood, Health Access, and several health and labor organizations; insurers said they appreciated the amendments and were reviewing their position. The committee adopted amendments aligning the bill with clinical guidelines and passed it 6-0 to Appropriations. The committee also took up AB 2247, the Thrive Act, to create a pilot program for trauma and mental health services for youth affected by gun violence in four counties. Supporters described barriers survivors face in accessing counseling, while members questioned the narrow focus on gun violence, the choice of counties, documentation requirements, and whether the program should instead be housed in victim compensation. The bill passed 8-0 to Judiciary. Later, AB 2531 would expand California’s uncompensated care program so veterans denied abortion care through the federal VA system could receive coverage in California, and would add an abortion resources link for veterans. Supporters framed it as filling a gap created by federal restrictions; opponents argued state funds should not support abortion. Members noted the VA already provides many reproductive services but not this one, and the bill passed 7-0 to Military and Veterans Affairs. The committee also heard AB 1915, which would modernize restaurant facility rules and create a self-certification pathway for some equipment installations. Restaurant and business groups supported the bill as a way to reduce costly delays, while the Contractor State License Board opposed the self-certification provision over safety and inspection concerns. Members generally supported streamlining but echoed public safety concerns and indicated further work was needed.

Transcript Highlights:

• THAT'S WHAT WE DO HERE IS NOT TO LEVERAGE AI OR TEACH OUR STUDENTS ALL ABOUT AI AND FORGET ABOUT THE
• BEYOND THE TWO WORDS AI.
• BIAS IS ANOTHER TYPE IT AI SOME OF MY COLLEAGUES MENTIONED, FOR EXAMPLE, TO HELP IT'S CALLED PREDICTIVE
• SO WE KNOW THE IMPLICATION APPLICATION OF THAT AI MODEL OF WHAT SHOULD BE THE BIAS WE NEED TO BE AWARE
• TOOLS THAT CREATE THOSE BIAS.

Transcript Highlights:

• But what happens when AI gets it wrong?
• For patients, AI technologies are improving health care outcomes.
• And we talk about bias, implicit bias, whether it's conscious or subconscious, because it is a reality
• So it wasn't—it was unconscious bias.
• So we know that there is bias that is out there.

Keywords: 987, senate, all

Transcript Highlights:

• to be identified, mitigated, and monitored for bias impacts when deployed in health care facilities.
• AI tools do not operate in a vacuum.
• AI tools do not operate in a vacuum.
• perpetuating bias and inequity when it is deployed without careful oversight.
• developers and deployers of AI technology and health care applications.

Summary: The committee heard several health-related measures. SB 27 by Senator Umberg would revise and expand California’s CARE Court by limiting the expansion to people with bipolar I disorder with psychotic features, clarifying the definition of “clinically stabilized,” and narrowing the role of nurse practitioners and physician assistants. Supporters, including behavioral health officials and family members, said the bill would reduce dismissals and better serve people with severe illness; opponents warned the expansion would strain county staffing and housing resources and could undermine voluntary engagement. The bill passed on a do pass motion to the Committee on Public Safety. SB 503 by Senator Weber Pierson would require AI tools used in health care facilities to be identified, monitored, and mitigated for bias when used in clinical decision-making or resource allocation. The author and supporters from Kaiser Permanente and the California Medical Association said the bill would help prevent discriminatory outcomes and improve trust and safety. The committee discussed the need to clarify developer and deployer responsibilities, and the bill passed as amended to Privacy and Consumer Protection. SB 68 by Senator Menjivar would require restaurants to provide written allergen information for the top nine food allergens, with tiered flexibility for smaller establishments. The bill was supported by patients, families, nurses, and allergy organizations, who described severe reactions and the difficulty of relying on verbal disclosures alone. The California Restaurant Association opposed unless amended, seeking broader use of the national model food code and additional liability language. The bill passed as amended to Appropriations. The committee also heard SB 403 by Senator Blakespear, which would remove the sunset from the End of Life Option Act; supporters described the law as a compassionate, well-functioning option for terminally ill patients, while faith-based groups opposed it. The bill passed to Judiciary. Later, SB 41 by Senator Wiener was introduced to rein in pharmacy benefit manager practices that steer patients to mail-order pharmacies and reimburse community pharmacies below cost; community pharmacists and several health organizations testified in support, describing pharmacy closures and patient access problems.

Bills: HB148, HB203, HB360, HB552, HB 1244, HB 1284, HB1533, HJR30, HB148, HB203, HJR30

Keywords: residential property, ad valorem tax, leasing, property appraisal, fair market rent, housing affordability, appraised value, tax limitation, housing market, affordable housing, leased residential real property, rent control, Texas Tax Code, property tax, residential leasing, homestead, tax code, appraisal review board, real estate sales, property tax relief

Transcript Highlights:

• </c> drawing on uh AI patent language so AI drawing on uh AI patent language so AI technologies<00:31
• for</c> doing so if an AI system AI patent for doing so if an AI system AI patent for example<00:31:
• Lastly, AI bias is real.
• Lastly, AI bias is real.
• </c><01:20:58.560><c> you</c> AI and getting U displaced by AI you AI and getting U displaced by AI you

Keywords: 1187, senate, all

Transcript Highlights:

• Faulty AI models can quickly exacerbate bias challenges, as mentioned about hiring.
• He said, 'It's AI-driven.'
• The bill also addresses bias in AI systems by requiring comprehensive impact assessments and additional
• AI cannot teach students how to use or interact with AI as AI... ...continues to exist in the workplace
• I'm an AI attorney with over a decade of experience in the AI bar.

Keywords: 995, all

Summary: The committee held a hearing on several artificial intelligence bills, opening with remarks about the 9/11 anniversary and then broad statements from the co-chairs about AI’s promise and risks. Chair Farley-Bouvier and Senator Moore emphasized the need for guardrails, transparency, and worker and consumer protections, while Senator Finegold described Senate Bill 37, which would create a framework for AI model training with safety assessments, audits, incident reporting, Attorney General oversight, and workforce reporting. Members also discussed Massachusetts’ position relative to other states and the need for state action in the absence of federal regulation. A large portion of the hearing focused on the Fair Act, House 77 and Senate 35, which would limit workplace surveillance, restrict collection of biometric and location data, require notice and human review for automated employment decisions, and protect workers from retaliation. Labor leaders, including AFL-CIO, AFSCME, AFT, SEIU, building trades, and other worker representatives, testified in support, describing harms from bossware, automated benefits denials, hiring and promotion screening, scheduling, and monitoring in workplaces ranging from health care and education to manufacturing and construction. They argued that AI systems are already affecting wages, benefits, safety, and job security, and that Massachusetts should act now to set clear rules. The committee also heard testimony on House Bill 74, which would require informed consent and clear contract terms for digital replicas of voices and likenesses, with SAG-AFTRA representatives supporting the bill as a protection for performers and creators. Another major topic was Senate Bill 51 on social media algorithm accountability and transparency; child safety advocates, researchers, and a public health expert described harms from engagement-based algorithms, including exposure to harmful content, eating disorders, and youth mental health impacts, and supported independent audits and public reporting. A few industry and civil liberties witnesses supported regulation but urged balance, warning against overly burdensome rules while acknowledging the need for privacy, transparency, and accountability. No votes or final committee actions were taken in the hearing excerpt.

Transcript Highlights:

• It prohibits AI tools from being used in public districts for instruction or education purposes except

Bills: SB1734, SB1630, SB1894, SB1975, SB1432, SB1437, SB1812, SB346, SB1250, SB710, SB1489, SB2045, SB1614

Keywords: artificial intelligence, AI, schools, public school districts, education technology, edtech, student privacy, FERPA, data privacy, data security, emerging technologies, machine learning, generative AI, classroom technology, instructional technology, teacher oversight, human-in-the-loop, student data, parental consent, opt-out