Imagine a world where information and opportunities are not just a click away but are rather confined to certain demographics and regions. Sadly, such a world existed well before the late 20th century when the term 'digital divide' was coined. It served as a stark reminder of the gaping chasm that separated those who had the privilege of accessing modern information and communications technology from those who were left behind, either with no access or restricted access. Orig

With the advent of the data science practises, especially the likes of Artificial Intelligence (AI) or machine learning and their adaptation in sensitive areas, has drawn massive attention to this technology in the recent years. Whether it is cancer diagnosing system, Amazon’s AI recruiting tool or the US court’s profiling system Correctional Offender Management Profiling for Alternative Sanctions (COMPAS), we can always disagree to the decision made by the AI systems. In fac

Your organisation may be tilting at windmills, hiring a Don Quixote for a Chief Data & Analytics Officer if your data strategy is not driving profit. A profound crisis exists: trillions in data investment yield limited returns, marked by a pervasive “two-year curse” instability among data leaders and 50-80% project failure rates. This failure is primarily managerial, as roughly 70% of struggles stem from people and processes. Data leaders often fail to establish Continuous Va

Artificial Intelligence (AI), or more precisely Machine Learning (ML), has become an industry trend in the past 10 years. From a buzzword to a new way of automation and decision-making, ML has become mainstream. I have had conversations with multiple organisations keen to use ML, even without a real-world use case. Graduate schools are offering lightweight courses to the masses, consulting companies are providing services on adopting ML, and technology companies are building

Large Language Models (LLMs) represent a transformative technology in the realm of generative artificial intelligence (AI). These machine learning models are designed to understand and generate text that mirrors human language, learning from vast amounts of text through rigorous self- and semi-supervised training. LLMs have a broad range of applications, from generating text and automating workflows to sparking creative ideas and even writing software code. Some of the most p