Explaining Explainable AI: Beyond Hyped Marketing

As the term "explainable AI" gains prominence in the tech world, it is crucial to distinguish between its true meaning and the often misleading hype surrounding it. The concept of explainable AI is fundamentally about transparency in the algorithms and decision-making processes that underpin artificial intelligence systems. However, the reality is more nuanced and less sensational than its marketing slogans suggest.

The True Meaning of AI

At its core, AI is not a single, monolithic technology but rather a broad field of study. It encompasses various techniques, tools, and methodologies aimed at creating systems that can perform tasks requiring human intelligence, such as learning, reasoning, and problem-solving. Regardless of the specific application, AI is a research domain through which scientists and engineers seek to understand and emulate aspects of human intelligence.

Just as the term "AI" is versatile and context-specific, so too are the problems and technologies it covers. Whether it is developing new algorithms, enhancing existing ones, or working with systems that do not yet fully align with our understanding of intelligence, anything within this domain can be labeled "AI," at least for a while. This label often remains in use as the technology moves into specialized fields, even if the core principles do not change significantly.

The Role of Labeled Technologies

It is important to note that nearly everything once labeled as "AI" has been developed primarily outside the context of AI research. For example, the development of UNREAL in 1996, a game engine that revolutionized the video game industry, is an interesting case study. Despite its numerous applications, none involved "AI" due to the lack of such technology at the time.

Similarly, IBM's Watson Supercomputer, an exceptional case in the use of AI, was never marketed as "AI." Instead, IBM referred to it as a "computer system" or "supercomputer." This distinction underscores the fact that "AI" is not a product but a descriptive label. By stating "Watson AI" or "supercomputer AI," one can maintain clarity about the technology's nature, thus avoiding the pitfalls of misleading marketing.

The Reality of "AI" Marketing

The current atmosphere in the tech industry is characterized by an overwhelming amount of "AI" hype. Many products claiming to harness AI are essentially repackaged technologies that have been around for decades. This deliberate obfuscation is a tactic that has been employed to bypass skepticism and create the perception of novelty and breakthroughs.

For instance, the idea of magical, revolutionary AI products that can solve all problems is widespread. However, such hype often fails to provide a realistic understanding of how these systems work, their limitations, and their true capabilities. This can mislead consumers, delay critical decision-making, and ultimately harm the legitimate development of AI.

Moreover, the term "AI" as a religion has led to a proliferation of gimmicks and pseudoscientific claims. Many companies have leveraged the allure of "AI" to market products that may have been more appropriately labeled as "automation," "software," or simply "technology." In doing so, they take advantage of the perceived prestige and mystery associated with artificial intelligence.

Conclusion

Explainable AI, like any other AI technology, aims to provide transparency in its decision-making processes. However, the real value lies in understanding the true nature of AI and its applications. As consumers and stakeholders, we must be vigilant and demand clarity from vendors about the capabilities and limitations of their products.

Let us focus on the genuine benefits and realistic expectations of AI, rather than succumbing to the unrealistic promises and marketing hype. By doing so, we can foster a more informed and responsible approach to AI development and implementation.