Nardo Manaloto
Nardo Manaloto is a healthcare and deep tech industry veteran with over 25 years of management experience in solving healthcare challenges using innovation, user centered design, data ecosystems, enterprise architecture, and new technologies. He is a strategic thought leader in ecosystem development, platform design, data life cycle, solution concepts, systems analysis, system transition, product architecture, hybrid value chains, and applied innovations to solve complex problems using current and emerging technologies. Nardo has worked with many healthcare stakeholders including health plans, providers, patients, and community points of view. He previously headed up Kaiser
Permanente’s Innovation, Solution Design, and System Transition groups and has applied full innovation life cycle to scale new solutions and sunset legacy systems on an enterprise level.
Artificial Intelligence (AI) has been making significant progress in recent years, transforming various industries and enhancing human lives. However, with this growth, the need for governance has become increasingly vital. The need for AI governance comes with several complexities, including the definition of AI and the scope it entails. AI governance requires a clear understanding of what needs to be governed.
The term AI encompasses a broad spectrum of technologies, including augmented
intelligence, cybernetics, artificial intelligence, AGI, bio/brain-inspired chips, and more. Hence, defining AI's scope is essential to determine what needs governance. Additionally, AI's effectiveness depends heavily on the quality of data, information, content, and feedback it receives. Therefore, governing these elements is vital to ensure AI's ethical and trustworthy use.
Creating a governance framework that covers the trustworthiness of AI is also essential. Trustworthy AI ensures that AI systems are transparent, explainable, and nondiscriminatory. It's crucial to ensure that AI systems work to benefit humanity while minimizing risks and maximizing benefits.
With the increasing power of quantum technologies, AI systems will become more
capable and complex. Therefore, there is a need to create governance frameworks that can handle exponential capabilities. The governance framework needs to be flexible and adaptable to accommodate these advancements.
AI systems comprise various subsystems, capabilities, features, functions, and processes, and this need governance. It's also necessary to have a governance framework that can evaluate the outcomes and impact of AI systems. The framework needs to assess whether the output and decisions of AI systems have a positive or negative impact and consequence.
Finally, AI and autonomy are two sides of the same coin, and there is a need to - more in the book.