Major threats to the continued adoption of Artificial Intelligence in today's hyperconnected world

From the golden era of science fiction which dates to the late 1930s, scientific and technological advances in artificial intelligence (AI), along with one of its key subsets, machine learning (ML) have been growing significantly, especially in recent years. In 2021 alone, notable feats included an AI program capable of creating images from seen or previously unseen textual captions, an AI model that effectively integrates computer vision and natural language processing, and a novel AI framework for diagnosing dementia in 24 hours with real-world feasibility underway amongst a host of other fascinating breakthroughs. This paper briefly delves into AI/ML and recaps some key essentials, covering AI and ML subfields, ML methods, industries where AI/ML finds relevance, key stages and the common technical challenges in ML development. Importantly, the paper shifts attention from the latter to underscore the duo of transparency and ethics in AI, highlighting specifically what these are and why they are important, subsequently positing a PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework for AI design, build and implementation. It is anticipated that the upshot of this would be the facilitation of continuous adoption and long-term sustainability of AI/ML.