This post was originally published on this site

We live in a dynamic age, especially with the increasing awareness and popularity of Artificial Intelligence (AI) systems being explored by users and organizations alike. I was recently quizzed by a junior researcher on how AI systems came about and realized I could not answer that query immediately. I had a rough idea of what led to the current generative and large language models. Still, I had a very fuzzy understanding of what transpired before them, besides being confident that neural networks were involved. Unsatisfied with the lack of appreciation of how AI systems evolved, I decided to explore how AI systems were conceptualized and developed to the current state, sharing what I learnt in this diary. However, knowing only how to use them but being unable to ensure their trustworthiness (especially if organizations want to use these systems for increasingly critical business activities) could expose organizations to a much higher risk than what senior leadership could accept. As such, I will also suggest some approaches (technical, governance, and philosophical) to ensure the trustworthiness of these AI systems.