Knowledge-Centric Technology vs Artificial Intelligence: Part I

Author: Donald Thompson
Knowledge-Centric Technology vs Artificial Intelligence: Part I

Dave Bowman: Optimize my supply chain, HAL.
HAL: I’m sorry Dave, I’m afraid I can’t do that.

Is this the scene that plays out in your mind when you think of AI solving your complex business problems?  Wikipedia defines AI as “intelligence exhibited by machines,” which is further elaborated to “a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.”  Is this the future we want to create, where we simply give autonomy to supposedly intelligent machines to decide how to maximize profitability (often the measure of success)?

At Maana, we believe that humans are far from being replaceable.  In fact, we see it as our mission to empower people, to enable them to make better decisions more quickly.  Everything we do is designed to make this true, from the way we approach business optimization use cases, the assistive self-service technologies and experiences we build, ease of integration and operationalization, and, indeed, the central concept of accruing knowledge (in the form of conceptual/data and computational models in your very own Enterprise Knowledge Graph) not only for each business problem within each business unit, but ultimately across the entire enterprise — we recognize and embrace the fact that businesses are highly interconnected and interdependent, not silos with only local KPIs to measure.

We advocate a sort of symbiosis – a deep collaboration between humans and machines – that we term: user-guided / machine-assisted.  Demands of complexity, volume, and efficiency require the capabilities best suited to machines and algorithms.  But the direction of machine actions and interpretation of algorithmic results is still best managed by humans, whether business leaders and owners, subject matter experts, or data scientists.  This is an entirely pragmatic choice, not a fanciful one.

From an AI perspective, several of the core ingredients are Knowledge Representation and Reasoning, Learning, and Decision-making.  We will examine each of these in-depth in the subsequent parts of this small blog series and provide real-world examples and highlight how Maana incorporates essential elements of AI as a component of our overall Knowledge-Centric Technology approach, which is more comprehensive (and practical) than the AI program of science fiction.



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