Intelligence in Artificial Intelligence

TL;DR

This paper discusses the complex nature of intelligence in AI, contrasting bio-inspired continuous learning models with practical enterprise needs, questioning the pursuit of human-level AI and suggesting simpler biological models like worms for business applications.

Contribution

It offers a critical perspective on the elusive goal of human-level AI, emphasizing the importance of understanding intelligence as a continuous, experience-based process rather than discrete functions.

Findings

AI has evolved from winter to a media frenzy.

Current enterprise AI may not require human-level intelligence.

Simpler biological models like worms could be more practical for business applications.

Abstract

The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of an app or from a shrink-wrapped software defined point solution, is in contrast to the bio-inspired view of intelligence as an outcome, perhaps formed from a tapestry of events, cross-pollinated by instances, each with its own microcosm of experiences and learning, which may not be discrete all-or-none functions but continuous, over space and time. The enterprise world may not require, aspire or desire such an engaged solution to improve its services for enabling digital transformation through the deployment of digital twins, for example. One might ask whether the "work-flow on steroids" version of decision support may suffice for intelligence? Are we harking back to the era of rule based expert systems? The image conjured by the publicity machines offers deep solutions with human-level AI and preposterous claims about capturing the "brain in a box" by 2020. Even emulating insects may be difficult in terms of real progress. Perhaps we can try to focus on worms (Caenorhabditis elegans) which may be better suited for what business needs to quench its thirst for so-called intelligence in AI.