The AI Kaleidoscope in an Age of Regulations and Options
AI is everywhere. However, utilizing traditional system approaches to solutions risks repeating the same mistakes and fragmentation from the last 35 years. AI is not a “hammer” or a one-size-fits-all COTS design. It is an intelligent data delivery approach for the next generation of products, audit, legal, and regulatory compliance which requires continuous feedback from adaptive learning systems.
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Among experienced IT personnel, there is a saying, “When is a hammer not a hammer?” This circular phrase is based on the application of a cognitive bias termed the “Law of the Instrument” where a common (technology) tool is applied repeatedly to all situations.
As we are very aware, in 2023 artificial intelligence (AI) captured the imaginations of every executive and researcher across the world, and 2024 will likely extend its innovation iterations and dominance[1]. In fact, nary a 2024 go-to-market, legal, supply chain, application systems, audit compliance, customer service, or back-office strategy excludes AI as part of their infrastructure, operational processes, or sought after skills.
Today, we are witnessing bias taking place with the rapid advancements surrounding artificial intelligence solutions, software, chips, and skills. If there is a current or future problem, AI is the hammer that must be deployed.
However, what ideation, strategy, design, or implementation of AI are we talking about? In the end, the nuances, details, and context of implementation mean as much as the underlying technology advancements. AI in 2024 is about a “kaleidoscope” of options, designs, and solution sets. As illustrated in Figure 1, there is no longer a “one-size-fits-all” (e.g., hundreds of Gen AI solutions) as the number of variables and options require smaller “hammers”—greater precision.
To reinforce the exponential complexity, a quick AI query about AI returns dozens of forms including generative AI, general AI, machine learning, deep learning, natural language processing, expert systems, computer visioning and even robotics. Another AI query for AI designs yields unfamiliar terms of gradient boosting, random forest, decentralized learning, adaptive learning, checkpointing, and dozens more. Adding additional regulatory parameters (i.e., features), what AI solutions best fit to the EU AI Act, the (WH) AI Executive Order, passed and pending state oversight, and numerous foreign government proposals? When assembled across a landscape, an ecosystem of AI capabilities and choices, the idea that AI represents a singularly familiar design and implementation concept is proving to be an early mirage (see Figure 2) of what is coming, what has arrived, and what will continue to define extraordinary complex interfaces.
[1] Over the last two decades, it was information engineering, relational databases, cloud computing, blockchain, and more recently, SaaS.