Texas Enacts Comprehensive AI Governance Law With Specific Requirements for Health Care Service Providers
6 minute readJuly 11, 2025
By Shawn Tuma, Christine Chasse
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Texas Governor Greg Abbott recently signed the _Texas Responsible Artificial Intelligence Governance Act (TRAIGA)_ into law, marking a significant milestone in artificial intelligence (AI) regulation. Effective Jan. 1, 2026, TRAIGA establishes a comprehensive framework for the ethical development, deployment, and use of AI systems in Texas.
Introduction to the Impact of Climate Change on Global Agriculture
Climate change is one of the most pressing issues facing global agriculture today. The increasing frequency and intensity of extreme weather events, coupled with rising temperatures, are significantly impacting crop yields, water availability, and soil health.
Key Statistics on Climate Change and Agriculture
- By 2050, climate change could reduce global crop yields by up to 30%.
- The number of heatwaves in the United States has increased from an average of 14 per year in the 1960s to over 20 today.
Impact on Crop Yields
Higher temperatures and more frequent heatwaves are leading to reduced crop yields. For example, wheat production in India has decreased by 10% since the early 2000s due to increased temperatures.
Water Availability
Climate change is also affecting water availability, which is critical for agriculture. In the western United States, snowpack has declined by 25% over the past few decades, leading to reduced water supply for irrigation.
Soil Health
Soil health is another area significantly impacted by climate change. Increased rainfall intensity and erosion are leading to a loss of topsoil, which can take centuries to regenerate.
Mitigation Strategies for Climate Change in Agriculture
- Implementing conservation tillage practices to reduce soil erosion and improve carbon sequestration.
- Developing drought-resistant crop varieties through genetic modification and traditional breeding methods.
Conclusion
In conclusion, the impact of climate change on global agriculture is profound and multifaceted. Addressing these challenges requires a comprehensive approach that includes both mitigation strategies and adaptation measures.
A “true lifecycle approach” for governing healthcare AI
AI is rapidly transforming healthcare, but for that transformation to be for the good we must ensure it is safe and ethical. One way to ensure this is with a new model of governance called the True Lifecycle Approach, writes Dr. Barry Solaiman.
From hospital wards to wellness apps, AI is rapidly transforming how healthcare is delivered. The speed of AI’s proliferation is quite breathtaking—think Cedars Sinai and its wellness app on the Apple Vision Pro, or the plethora of applications developed by Siemens in precision medicine, predictive analytics, and beyond.
As the technologies continue to evolve, the frameworks that govern their use remain fragmented. Law, as usual, is slow to catch up to technological innovation. This raises a serious question: how do we ensure that AI in healthcare is safe, ethical, and worthy of patients’ trust?
Why is the TLA Necessary?
Readers might pause and argue that there are already governance frameworks for AI, such as those developed and updated by the Food and Drug Administration (FDA) in the U.S. and the European Medicines Agency in the EU. These approaches focus narrowly on approving AI medical devices to market. Devices that pose greater risks to the public must undergo more checks and approvals before seeking approval.
The problem is that these frameworks have not been designed with the full complexity of healthcare AI in mind. They overlook important issues like informed consent, malpractice liability, and other patient rights.
These frameworks also regard AI as a technical tool, not as something that deeply impacts human lives. By contrast, the TLA is grounded in healthcare law and ethics, emphasizing the importance of the standard of care in medicine, patient confidentiality, matters of consent, and respect for cultural and religious differences.
These values are particularly relevant among Gulf Cooperation Council (GCC) countries, which are home to diverse expat populations.
The TLA has three core phases of governance, starting with research and development (R&D). This phase sets the foundation for legal and ethical AI in healthcare from the very beginning of its conception. In Qatar, for example, HBKU worked in partnership with the Ministry of Public Health (MOPH) to create the [“Research Guidelines for Healthcare AI Development.”](https://www.researchgate.net/publication/390763866_Research_Guidelines_for_Healthcare_AI_Development?channel=doi&linkId=67fd4491bd3f1930dd5e1657&showFulltext=true)
These encourage developers to follow detailed processes and document the purpose, scope, and intended use of AI systems. Importantly, researchers should consider ethics and law from the outset, such as compliance with data protection law as it pertains to medical data.
The second phase considers systems approval. While not all healthcare AI tools require regulatory approval, regulators should nevertheless have broader powers to ensure that healthcare AI meets robust safety standards.
While regulators around the world currently lack such powers, Saudi Arabia has made progress in the GCC region with its regulatory framework. Through its published guidance [MDS–G010 for AI-based medical devices](https://www.sfda.gov.sa/sites/default/files/2023-01/MDS-G010ML.pdf), the Saudi Food and Drug Authority’s standards go beyond other regulators, incorporating ethical standards and provisions on adaptive algorithms, transparency, and post-market monitoring.
Again, this does not cover all healthcare AI devices, but indicates where governance can evolve further.
The TLA’s final phase focuses on AI once it is used in practice. Rules should govern not only researchers and developers, but also healthcare providers, insurers, and any other entity using AI downstream.
To this end, Abu Dhabi and Dubai have introduced AI policies with binding elements that go beyond mere recommendations to require audits, validation of AI, and patient feedback mechanisms.
An Unexpected Case Study
GCC countries are prioritizing AI investment, including healthcare AI governance. Regional governments are making strides in different phases of the AI governance lifecycle. Yet, conceptualized collectively, their efforts represent a True Lifecycle Approach (TLA) that covers the whole spectrum of AI governance.
Indeed, the GCC is uniquely positioned to pioneer this approach as a global model. Member states have centralized governance structures and diverse populations which need technologies that account for cultural sensitivities concerning language, religion, and other factors. The result can be a governance ecosystem that respects global norms and local needs—an approach that could help inform global best practices in the years to come.
Developers and deployers of AI in healthcare settings must remember that AI is not just a technological project but a human one. While policymakers and lawmakers decide how to regulate the technology, the TLA provides a principled roadmap that encourages discussions on how best to govern the technology, putting patients at the center.