Transcript Highlights:

• court system.
• You would tell the computer how to follow these steps, and that's how computing was done.
• So instead of telling the computer exactly what it needs to do, ...instead of telling the computer exactly
• But it's also helping us build better defenses for computers and find weaknesses in our systems.
• The system.

Summary: The committee held its first meeting on artificial intelligence and data centers, established a quorum, and heard introductory remarks from Majority Leader Hogue and the chair about the committee’s charge. Members said the goal was to build a factual foundation on AI, hear from experts and stakeholders, and develop practical North Dakota-focused recommendations rather than simply produce a large volume of bills. Legislative Council also reviewed interim committee rules and procedures before the informational presentations began. Staff and NCSL presenters then gave overviews of AI concepts and the state and federal policy landscape. The background memo and presentations covered AI categories and terms, state laws in areas such as consumer protection, algorithmic discrimination, deepfakes, chatbots, children’s safety, health, education, and government use, as well as data center siting and economic impacts. NCSL described a growing number of AI bills introduced and enacted across the states, with comprehensive laws in places like Utah, Colorado, Texas, California, and Illinois, and noted recurring issues around transparency, privacy, liability, and protections for minors. A major focus of the discussion was federal preemption and the tension between state regulation and national AI policy. NCSL said a recent White House executive order and related federal framework seek a light-touch, innovation-friendly national standard, with possible challenges to state laws and possible funding conditions tied to compliance, though no broad federal preemption has yet been enacted. Members asked about Commerce Clause concerns, industry pushback, oversight models, and whether AI policy is bipartisan; presenters said the issue cuts across party lines, with broad agreement on child safety and deepfake restrictions but more disagreement on broader regulatory approaches. No votes or formal actions were taken at the meeting, and the committee recessed briefly for technical issues during the second presentation.

Transcript Highlights:

• and transfer, and looking at things like new licensing systems, new computers that we've actually purchased
• and transfer, and looking at things like new licensing systems, new computers that we've actually purchased
• &gt;&gt; And<00:36:52.240><c> what</c><00:36:52.400><c> computer</c><00:36:52.800><c> systems</c><00:
• system. ...computer system as far as delays are concerned, or was there procurement too?
• :00:47.760><c> implemented,</c> computer system once it's implemented, computer system once it's implemented

Committee: Joint Appropriations

Transcript Highlights:

• In June, the North Dakota court system issued a public notice regarding the use of AI in the court system
• You would tell the computer how to follow these steps, and that's how computing was done.
• But it’s also helping us build better defenses for computers and find weaknesses in our systems.
• heavily test the systems, making sure that they don’t... ...heavily test the systems and make sure that
• The system.

Committee: Joint Artificial Intelligence and Data Center Committee

Summary: The committee held its first meeting on artificial intelligence and data centers, establishing its purpose as a study and policy-development body rather than one aimed at producing many bills. Majority Leader Hogue urged members to move quickly, focus on federal and other states’ AI laws, consider possible federal preemption, child protections, and the siting and economic impacts of data centers. Committee leadership echoed that the goal is practical, balanced governance that protects North Dakota while allowing innovation to continue. Legislative Council staff provided a background memo and NCSL presented a detailed overview of AI concepts and the current state legislative landscape. The presentations distinguished narrow AI, generative AI, agentic AI, and theoretical AGI/ASI, and summarized major state policy themes: comprehensive AI laws in states such as Utah, Colorado, Texas, California, and Illinois; targeted laws on deepfakes, chatbots, health, education, notifications, and digital likeness; and growing use of appropriations and agency inventories. Members asked about Colorado’s repeal and reenactment, Texas’s sandbox and training provisions, oversight structures, and whether AI regulation is bipartisan; presenters said most issues cut across party lines, with broad agreement on child safety and deepfakes but more division on broader regulatory approaches. The federal update focused on executive orders, preemption, and congressional activity. NCSL described a White House framework favoring a single federal standard, a DOJ litigation task force, Commerce Department review of state laws, and possible funding conditions tied to state AI policy, though no formal state-law challenge had yet occurred. The presentation also covered a recent executive order creating a voluntary federal vetting process for advanced frontier models after safety concerns, and congressional proposals including a failed 10-year state moratorium, Senator Blackburn’s child-safety bills, the Kids Online Safety Act, a House-passed children’s digital safety package, a Senate data center moratorium proposal, and a House ratepayer/data-center bill. The committee took no formal action beyond receiving testimony and asking questions.

Transcript Highlights:

• AI systems learn from historical data.
• AI systems, uh, but this can reflect systemic biases that's in that data set right now.
• ><c> advanced,</c><00:04:50.320><c> lack</c> systems, no matter how advanced, lack systems, no matter
• AI systems learn from inequalities. AI systems learn from historical<00:05:06.000><c> data.
• AI systems the uh but this can<00:05:14.960><c> reflect</c><00:05:15.360><c> systemic</c><00:05:15.919

Transcript Highlights:

• AND IT ENDED UP IN WEATHER AND THE COMPUTER WOULD NOT HAVE LANDED INSTRUMENTALLY.
• TO TRULY UNDERSTAND THINKING YOU HAVE TO UNDERSTAND THE COMPUTATIONS BEHIND IT.
• SYSTEMS.
• THESE SYSTEMS ARE VERY EXPENSIVE.
• I MEAN, THERE ARE COMPUTER SCIENCE GEEKS LIKE MYSELF.

Bills: SB2969 , SB3263 , SB2602 , SB3229 , SB3199 , SB2550 , SB2877 , SB3325 , SB2024 , SB2614 , SB2613 , SB3063 , SB2319 , SB2800 , SB2892 , SB2321 , SB2407 , SB2805 , SB2153 , SB2595 , SB2781 , SB3233 , SB2360 , SB1432 , SB2543 , SB2599 , SB3053 , SB2001 , SB2041 , SB3247 , SB3253 , SB2401 , SB2673 , SB3067 , SB411 , SB2934 , SB3219 , SB2919 , SB2239 , SB2532 , SB2601 , SB1032 , SB2446 , SB2152 , SB2721 , SB3076 , SB3140 , SB2671 , SB2338 , SB2268 , SB99 , SB2930 , SB3069 , SB3096 , SB3097 , SB3090 , SB2060 , SB3028 , SB2544 , SB2069 , SB2552 , SB3218 , SB3022 , SB148 , SB2259 , SB2578 , SB2928 , SB2816 , SB2580

Committee: House Finance

Keywords: SB2969, Maui wildfire, Maui wildfires, wildfire exposure, Maui Health Registry, University of Hawaii, public health, biomonitoring, medical screening, mental health services, trauma recovery, disaster recovery, first responders, kupuna, children's health, medically vulnerable, environmental exposure, toxic exposure, respiratory illness, community health

Transcript Highlights:

• So QCAMP stands for the Quantum Computing, Math, and Physics.
• Quantum computing with doing digital twins, model-based systems engineering, when you work with government
• Which could also be addressed with some of these quantum systems.
• Systems like you would see in AI and data centers.
• , advanced energy technologies, and aerospace and defense systems.

Committee: House Science, Technology & Telecommunications Committee

Transcript Highlights:

• But quantum computers are a billion times a billion faster than your classic computer.
• When I say change the world of computing, I'm referring to the fact that quantum computers require orders
• While not replacing them, quantum computers can add new computing capabilities.
• While not replacing them, quantum computers can add new computing capabilities that do more with less
• and cooling computers.

Summary: The Assembly Economic Development, Growth, and Household Impact Committee met in person and established quorum after beginning briefly as a subcommittee. The committee adopted its rules and then heard several bills focused on economic recovery, housing, technology, retail theft, and utility infrastructure. AB 265 (Caloza) would create a $100 million state-funded small business and nonprofit recovery program for organizations affected by declared emergencies; it drew broad support from small business, nonprofit, chamber, city, and community groups, with no opposition voiced. AB 797 (Harabedian) proposed a zero-cost state financing structure using CRA-backed securities to help community nonprofits buy wildfire-damaged properties at fair market value and prevent predatory investor purchases; it was presented as a community stabilization tool and received support from the California Community Foundation, with no opposition. AB 940 (Wicks/Ellis) would establish quantum innovation zones to strengthen California’s quantum computing economy, and AB 949 (Shiavo) would create a retail theft grant program for small businesses to fund security improvements and theft prevention measures; both bills were supported by business and university witnesses, though one member said they would not vote for AB 949 due to concerns about broader crime policy. AB 1347 (Carrillo) proposed a pilot program to speed utility interconnections in priority growth regions, including allowing developers to trade expedited connections for upfront infrastructure cost recovery and use microgrids in some cases; it had no opposition in the hearing. Committee members generally expressed support for the bills, especially those aimed at disaster recovery and small business resilience. Questions on AB 940 focused on where quantum innovation zones might be located and how local governments and universities would coordinate; the author and witnesses said the zones should be open statewide and could build on existing research centers such as Berkeley, Stanford, Caltech, UCSB, UCLA, and UCSC. On AB 797, members discussed the need to protect homeowners from below-market offers after wildfires. On AB 949, the author emphasized that modest grants could help small businesses make security upgrades and prevent repeated theft losses. The committee voted to send AB 265, AB 797, AB 940, AB 949, and AB 1347 forward, generally on party-line or near-unanimous votes, with the bills reported out of committee and placed on call as needed. The consent calendar, including AB 254, AB 415, AB 655, AB 1232, AB 1254, AB 1477, and HR 27, was also approved. The hearing adjourned at 10:33 a.m.

Transcript Highlights:

• , and they can be both automated decision systems and frontier systems.
• And they can be both automated decision systems and front-tier systems working together.
• And so what does it mean to build the cockpit for a big flying system like an AI system?
• or systems cards.
• It was a bad system, and it still is a bad system.

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.

Transcript Highlights:

• of computing.
• than traditional computers in less time with less energy.
• When I say change the world of computing, I'm referring to the fact that quantum computers require orders
• While not replacing them, quantum computers can add new computing capabilities that do more with less
• and cooling computers.

Committee: House Economic Development, Growth, and Household Impact

Transcript Highlights:

• So we do have some concerns about the administrative and fiscal impact of a bifurcated system where some
• And I struggle to sit in front of a computer for four hours to take a test.
• The amount of the surcharge that an advanced computing business or an affiliated group owes is capped
• The amount of the surcharge that an advanced computing business or an affiliated group owes is capped
• This bill is about aligning our financial aid system with today's economic realities.

Bills: HB2286 , HB2324 , HB2363 , HB2098

Committee: House Postsecondary Education & Workforce

Keywords: social work, licensure, alternative routes, education requirements, professional regulation, tuition waivers, veterans, education, children of veterans, higher education, military families, music therapy, temporary exemptions, healthcare, therapy practice, funding, tuition, financial aid, state budget

Transcript Highlights:

• Senator for the school system, for SARB, that's not the answer.
• , as a young boy, we talk about the school system.
• We mentioned the IEP system, the SAR.
• The current staffing level of the Computer Crimes Investigation...
• Whether it's a phone or a computer or some other storage device.

Transcript Highlights:

• </c> computing and that is to say computation computing and that is to say computation that's<00:26:56.640
• </c> to store and some capacity for compute to store and some capacity for compute but<00:27:19.279><
• Compute will take more electricity.
• </c> cooling their systems. cooling their systems. um<00:43:43.359><c> evaporative</c><00:43:44.000><
• Medicaid system. And so, we're extremely Medicaid system.

Summary: The Intelligence Task Force met with a quorum present and approved the minutes from the August 14 meeting. The first presentation was from the National Retail Federation on artificial intelligence in the retail sector. NRF described AI use cases in three areas: consumer-facing tools such as chatbots, product descriptions, and marketing; employee-facing tools such as company-specific apps trained on employee manuals; and internal uses such as supply chain forecasting, inventory planning, fraud detection, cybersecurity, and coding support. The presenters said retail has been among the top deployers of AI and emphasized that the goal is to improve both customer and employee experience. NRF also outlined its principles for responsible AI use, organized around governance and risk management, customer engagement and trust, workforce applications, and business partner accountability. The group said retailers should maintain strong internal oversight, be transparent with customers, ensure compliance with existing laws, closely review workforce-related uses because they can be high-risk, and clearly define responsibilities between retailers and third-party developers. In policy discussion, NRF urged a tiered approach focused first on high-risk uses such as hiring, health care, financial, mortgage, and rental decisions, warned against fragmented rules that could favor only the largest firms, and encouraged voluntary standards and worker upskilling incentives. In response to a question about dynamic pricing, NRF said its members do not target consumers based on pricing and offered to follow up with more information. The committee then moved to a follow-up discussion on energy policy and data centers, hearing from Bartley Cleland of NetChoice. He explained that AI runs largely in data centers and that cloud computing shifts processing and storage away from individual devices, which he argued improves efficiency and can reduce costs. He said electricity demand has been rising over time and that AI will increase compute-related electricity use, but framed electricity as a normal input to economic growth. No votes or formal actions were taken after these presentations.

Transcript Highlights:

• This is a technology that is going to significant orders of magnitude faster computing. the computing
• I know a lot about quantum computing. I appreciate you coming.
• And with the modern quantum computer. the power consumption.
• We're witnessing revolution in computing.
• One of the big problems with quantum computing is people say quantum computer and there are multiple

Bills: HB3146 , HB3719 , HB3895 , HB3923 , HB4748 , HB4751 , HB4936 , HB4952 , HB4990 , HB4991 , HB5061 , HB5196 , HB5238 , HB5246 , HB5487

Committee: House Delivery of Government Efficiency

Keywords: State Office of Administrative Hearings, SOAH, administrative hearings, contested case, contested case hearing, administrative law judge, ALJ, final decision, proposed decision, agency hearing, hearing continuance, rescheduling, Texas administrative law, Government Code Chapter 2001, workers' compensation, Department of Human Resources, Texas Labor Code, Transportation Code, Agriculture Code, Insurance Code

Transcript Highlights:

• I also want to note that we continue to have Cal Compute in this bill, which is an exciting new public
• cloud that will help democratize and expand access To compute for folks who maybe can't afford compute
• And we are creating Cal Compute, which I think will enhance innovation because compute has become so
• So models that make it easier to shut down the banking system or the electric grid.
• And we are creating Cal Compute, which I think will enhance innovation because compute has become so

Summary: The Assembly Privacy and Consumer Protection Committee heard SB 53 by Senator Wiener after the bill was substantially amended on the floor and referred back under Assembly Rule 77.2. The author explained that the bill, focused on AI safety and frontier models, now applies its main requirements to models trained above 10^26 FLOPs, includes broader whistleblower protections, sets different disclosure obligations based on company revenue, removes Attorney General rulemaking authority in favor of an annual Department of Technology report, and keeps a $1 million-per-violation penalty. He also highlighted CalCompute, a proposed public cloud intended to expand access to compute and support innovation. Supporters, including Encode AI and Economic Security California Action, argued the bill would hold AI developers accountable to their public safety commitments, improve transparency, protect whistleblowers, and help democratize access to AI infrastructure. They said the measure reflects extensive negotiation with the administration and stakeholders and aligns with recommendations from the governor’s frontier-model working group. Opponents, including CalChamber, TechNet, CCIA, and Chamber of Progress, remained opposed unless amended, saying they appreciated the author’s work but still had concerns outlined in their letters. Committee members questioned whether the bill could stifle innovation, how it would address worst-case AI harms, and whether it could reach actors outside California. The author responded that the bill is intended as a light-touch transparency measure, that it applies to entities doing business in California, and that California can still lead in the absence of federal action. Members also emphasized the importance of whistleblower protections and CalCompute. The committee voted 12-1 to pass the bill, with DeMaio voting no and Patterson not voting, and the bill was sent back to the floor.

Transcript Highlights:

• You know, send them through the school system, for SARB, that's not the answer.
• We mentioned the IEP system, the SARB to your parents.
• It is their system, and we can do a diversion before... ...system, and we can do a diversion before it
• So I think it bears a little explanation on how the system is set up.
• Whether it's a phone or a computer or some other storage device.

Summary: The Assembly Budget Subcommittee on Public Safety heard several items focused on youth safety and law enforcement resources. The committee first took up tribal youth diversion programs, with the Legislative Analyst’s Office describing the Tribal Youth Diversion Grant Program and its two cohorts of grantees funded through the Board of State and Community Corrections. Tribal representatives from the Yurok Tribe and San Pasqual Band of Indians testified that diversion, tribal courts, school partnerships, mentoring, and culturally grounded services helped reduce truancy and justice-system involvement, but that short-term funding interruptions and limited capacity prevented them from serving all youth in need. Committee members discussed the importance of early intervention, tribal-state court collaboration, and possible misidentification of Native youth in the justice system. The committee then heard the California Highway Patrol’s overview of surge operations supporting local crime suppression, including organized retail theft. CHP reported that its surge teams have been used in response to mutual aid requests and cited arrests, stolen vehicle recoveries, and firearm seizures in Oakland, Bakersfield, and San Bernardino. Members asked about demand for these operations and whether CHP could meet requests without affecting other duties; CHP said requests have increased and are accepted when resources allow. The committee also heard CHP’s request for a $5 million General Fund augmentation and 12 positions for its Computer Crimes Investigation Unit to make child sexual abuse material and human trafficking investigations a higher priority. CHP cited rising cybertip volumes, a case involving AI-generated CSAM, and the need for more investigators and forensic capacity. A larger portion of the hearing focused on the Internet Crimes Against Children task forces and a separate $5 million ongoing General Fund proposal for Cal OES to continue the program. Task force commanders from Sacramento, San Diego, Silicon Valley, and Fresno described rapidly growing cybertip volumes, heavy caseloads, forensic backlogs, and the need for training and equipment for affiliate agencies statewide. They emphasized that the ICAC model relies on local partnerships, deconfliction, and subject-matter expertise to identify victims, execute warrants, and rescue children, and they gave examples of cases that led to arrests and child rescues. Members generally supported the work but raised questions about overlap between CHP and ICAC efforts, the need for broader statewide collaboration, and whether more resources should be directed to task forces and victim services. A public commenter also urged expansion of homeless youth exploitation services and the California Youth Crisis Line.

Transcript Highlights:

• Representative, Web EOC is our system of systems for tracking mission requests, and each county has access
• So we try to modify the systems.
• What is interesting, the system is scalable, so... What is interesting, the system is scalable.
• But with the increase in data and some of these big computing systems, have you seen a need to upgrade
• be is that we build small systems For our experimental work, and then when real computing power is needed

Summary: The Natural Resources and Disaster Subcommittee met to discuss the use of artificial intelligence in emergency management and related public-safety applications. The panel included the Florida Division of Emergency Management, the University of Florida, and Florida International University. FDEM described current uses of AI for invoice anomaly detection, automated situation report drafting, and data synthesis in WebEOC, emphasizing that AI is used to speed analysis and improve efficiency but not to replace human decision-making. The agency also said counties retain access through backup communications such as Starlink and generators, and that WebEOC provides shared visibility, archived documentation, and a common operating picture across all 67 counties. University of Florida representatives highlighted Beacon, an AI-enabled public safety audio service developed with FDEM and public media partners to distribute official alerts across multiple platforms, including mobile devices and digital streams. UF IFAS described a geospatial AI “Gaia bot” that turns satellite data into natural-language answers and maps for crop damage assessment and flood-risk mapping, with a focus on making complex Earth-observation data more accessible to growers and policymakers. FIU presented AI models that predict water levels and flood mitigation settings much faster than traditional simulation tools, with comparable or better accuracy, and said the work includes explainability features and broader research on compound flooding. Members asked extensive questions about storm surge, hallucinations, whether generative AI or large language models were being used, data vetting, and hardware needs. The witnesses repeatedly stressed that their systems are not autonomous, that human review remains central, and that the models used are primarily data-driven predictive tools rather than chatbot-style generative AI. The meeting ended with thanks to the panelists and an announcement that the committee’s policy chief was leaving for another position. Representative Mooney then moved that the committee rise, and the meeting adjourned.

Transcript Highlights:

• Minnesota is 48th in access to computer science education in our K-12 system.
• </c><01:31:26.239><c> Citizens</c> computer science education. Citizens computer science education.
• our K12 computer science education in our K12 system.<01:31:39.040><c> But</c><01:31:39.120><c> we</
• </c> system. But we are making progress. system. But we are making progress.
• c> to</c><01:32:36.159><c> solve</c> computer using computer science to solve computer using computer

Committee: Senate Education Finance

Transcript Highlights:

• With our center, the county is looking at upgrading our computer systems.
• And number two, it seems like there need to be funds in order to upgrade the computer system.
• And also Apache County told you... ...how their computers didn't work well with the system.
• didn't work for us and also Apache County told you how their computers didn't work well with the system
• inappropriate computer system.

Committee: Joint Joint Legislative Audit Committee

Summary: The committee began with opening remarks about moving to a monthly, two-hour schedule for more timely and focused oversight of Auditor General findings. Members also recognized Melanie Chesney for 32 years of service to the Office of the Auditor General, with several speakers praising her work and her role in strengthening the relationship between the Auditor General’s office and J-LAC. The main agenda item was the Auditor General’s December 2025 special audit on the school safety interoperability fund and interoperable communication systems. Staff reported that about $26 million had been allocated to 14 law enforcement agencies for systems intended to improve real-time communication between schools and first responders. The audit found that all 14 agencies used the money for interoperable systems, but four agencies allowed private or tribal schools to participate contrary to statute, and several agencies failed to submit required annual expenditure reports. It also found that none of the three systems reviewed met every statutory requirement as written, in part because some requirements were vague or interpreted differently by vendors and agencies. The audit recommended that agencies recover and report any improper benefit to non-public schools, avoid using fund money for ongoing costs tied to non-public school participation, submit missing reports, and improve cost planning and contract monitoring; it also recommended that the legislature clarify eligibility for private and tribal schools and revisit unclear system requirements. The audit further found procurement and contracting problems at nine of 14 agencies, including weak or missing sole-source justifications, contracts that lacked accountability and termination provisions, and poor documentation of pricing and deliverables. Several agencies had not planned for ongoing annual costs, which the audit estimated could range from about $16,000 to $382,000 per rural county depending on the system. In the discussion, members expressed frustration with sole-source contracting and lack of documentation, and some said they would oppose future vendor bills without competitive bidding and stronger payment controls. The auditor also described mixed system performance: some agencies reported useful features such as panic alerts, camera access, and map sharing, but other systems were not fully functional or had never been implemented. The committee then heard from the Arizona Sheriffs’ Association, whose president said sheriffs support the goal of improving school safety, described county implementation challenges, and defended the use of local staff to manage the projects, while acknowledging that smaller counties face staffing and connectivity limits.

Transcript Highlights:

• , or computing.
• , or computing.
• , or computing.
• He said work involving electronics, digital systems, and computing has recognized professional engineering
• licensure in disciplines such as electrical, computer, software, and systems engineering in situations

Committee: Senate Executive Departments and Administration