Emerging Technologies and Their Impact on Society
Introduction to AI in Healthcare
In the first half of 2025, 34 states introduced over 250 AI-related health bills. These bills generally fall into four categories: disclosure requirements, consumer protection, insurers’ use of AI, and clinicians’ use of AI. The introduction of these bills highlights the growing importance of artificial intelligence in the healthcare sector and the need for regulations to ensure its safe and fair use.
Categories of AI-Related Health Bills
The bills about transparency define requirements for information that AI system developers and organizations that deploy the systems disclose. Consumer protection bills aim to keep AI systems from unfairly discriminating against some people and ensure that users of the systems have a way to contest decisions made using the technology. Bills covering insurers provide oversight of the payers’ use of AI to make decisions about health care approvals and payments. And bills about clinical uses of AI regulate the use of the technology in diagnosing and treating patients.
Facial Recognition and Surveillance
In the US, a long-standing legal doctrine that applies to privacy protection issues, including facial surveillance, is to protect individual autonomy against interference from the government. In this context, facial recognition technologies pose significant privacy challenges as well as risks from potential biases. Facial recognition software, commonly used in predictive policing and national security, has exhibited biases against people of color and consequently is often considered a threat to civil liberties.
Bias in Facial Recognition Software
A pathbreaking study by computer scientists Joy Buolamwini and Timnit Gebru found that facial recognition software poses significant challenges for Black people and other historically disadvantaged minorities. Facial recognition software was less likely to correctly identify darker faces. Bias also creeps into the data used to train these algorithms, for example when the composition of teams that guide the development of such facial recognition software lack diversity.
State-Level Regulations
By the end of 2024, 15 states in the US had enacted laws to limit the potential harms from facial recognition. Some elements of state-level regulations are requirements on vendors to publish bias test reports and data management practices, as well as the need for human review in the use of these technologies. These regulations aim to mitigate the risks associated with facial recognition technologies and ensure their use is fair and transparent.
Conclusion
The use of emerging technologies such as AI in healthcare and facial recognition software raises important questions about privacy, fairness, and transparency. As these technologies continue to evolve and become more prevalent, it is crucial that we have regulations in place to ensure their safe and responsible use. By understanding the potential risks and benefits of these technologies, we can work towards creating a future where they enhance our lives without compromising our values.
Frequently Asked Questions
Q: What are the main categories of AI-related health bills?
A: The main categories of AI-related health bills are disclosure requirements, consumer protection, insurers’ use of AI, and clinicians’ use of AI.
Q: What is the issue with facial recognition software?
A: Facial recognition software has exhibited biases against people of color and poses significant privacy challenges.
Q: How many states have enacted laws to limit the potential harms from facial recognition?
A: By the end of 2024, 15 states in the US had enacted laws to limit the potential harms from facial recognition.
Q: What is the purpose of state-level regulations on facial recognition?
A: The purpose of state-level regulations on facial recognition is to mitigate the risks associated with these technologies and ensure their use is fair and transparent.
