These frameworks articulate expectations. The expectations cannot be satisfied through policy language alone. They must be implemented through structural design.Today, , the Texas Responsible Artificial Intelligence Governance Act (TRAIGA) goes into effect
Owing to the proliferation of AI in high-risk areas, the pressure is mounting to design and govern AI to be accountable, fair and transparent. How can this be achieved and through which frameworks?Keywords: artificial intelligence; culture; ethics; governance; law; technology.
A really interesting example of this is Singapores Model Artificial Intelligence Governance Framework. It was released in January 2019 as a guide for organisations to create explainable, transparent, and fair AI technologies.
Overview of the AI RMF. Led by the Information Technology Laboratory (ITL) AI Program, and in collaboration with the private and public sectors, NIST has developed a framework to better manage risks to individuals, organizations, and society associated with artificial intelligence (AI).
The history of artificial intelligence governance is remarkably recent compared with the broader history of technological regulation. During the mid-twentieth century, early AI research remained largely theoretical and academic.
As we can see from the illustration, Artificial Intelligence Governance Framework Design has many fascinating aspects to explore.
Current artificial intelligence governance frameworks, designed for conventional computing systems, are ill-suited for neuroAI systems built on neuromorphic hardware.
[1] R. Kaur, Artificial intelligence for cybersecurity: Literature review (2023).
