Tech Term Decoded: Weak AI

Definition

Weak AI, also known as Narrow AI, is the use of artificial intelligence technologies to implement a high-functioning system that recreates, and perhaps improve on human intelligence for a dedicated purpose.  A good example to explain this concept is Predictive maintenance models. These models depend on data from machines, usually collected through sensors, to help anticipate when a machine part may malfunction and inform users ahead of time [1].

Weak AI
Insight on Weak AI [2]

Origin

The term "weak AI" is attributed to philosopher John Searle, who introduced the concept in the 1980s to differentiate between AI systems designed to perform specific tasks (weak AI) and those that could potentially achieve a level of consciousness similar to humans (strong AI); essentially, "weak AI" refers to the idea that a computer can effectively simulate aspects of the human mind without actually possessing a mind itself [3].

Context and Usage

Weak AI assists in transforming big data into information fit for use by identifying patterns and making predictions. For instance, in Retail, chatbots are used to assist customers with order tracking and product recommendations. In Manufacturing, robots are used to automate assembly lines process and reduce errors.

Why it Matters

Weak AI has become increasingly important in the technology industry because of its ability to automate routine tasks, process large amounts of data, and provide intelligent solutions to complex problems [2].


In Practice

A real-life case study of weak ai been practiced include Meta's (formerly Facebook) newsfeed, Amazon's suggested purchases, and Apple's Siri, the iPhone technology that answers users' spoken questions [4].

See Also 

Related Learning Approaches: 
Transfer Learning: Using knowledge gained from one task to improve performance on another
Unsupervised Learning: Learning without labeled data 
Zero-shot Learning (ZSL): Making predictions without training examples

References

Egegbara Kelechi

Hi. Am a Computer Science lecturer with over 12 years of experience, an award winning Academic Adviser and the founder of Kelegan.com. With a background in tech education and membership in the Computer Professionals of Nigeria since 2013, I've dedicated my career to making technology education accessible to everyone. I have published papers that explores how emerging technologies transform various sectors like education, healthcare, economy, agriculture, governance, environment, etc. Beyond tech, I'm passionate about documentaries, sports, and storytelling - interests that help me create engaging technical content. Connect with me at kegegbara@fpno.edu.ng to explore the exciting world of technology together.

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