TITLE: What are the differences between automation and AI? AUTHOR: Eddie S. Jackson, MrNetTek DATE: August 17, 2022 at 7:11 AM EST RESEARCH: Google search, current news, books, Copilot. EDITING: Grammarly
Computer automation and artificial intelligence are two related but distinct concepts that have significant impacts on various fields and industries. In this brief article, I will explain what each term means, how they differ, and how they can work together to create intelligent systems.
Computer automation is the process of using machines or software to perform tasks that would otherwise require human intervention or supervision. Automation can be applied to various domains, such as manufacturing, transportation, utilities, defense, facility operations, and business. The primary benefits of automation are increased efficiency, productivity, quality, safety, and cost savings. The main challenges of automation are ethical, social, and economic issues, such as job displacement, privacy, security, and regulation. I have spent most of my career in automation.
Artificial intelligence (AI) is the branch of computer science that aims to create systems that can perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, perception, and natural language processing. AI can be classified into two types: narrow AI and general AI. Narrow AI (weak AI) refers to systems that can perform specific tasks within a limited domain, such as speech recognition, machine translation, face detection, and product recommendation. General AI (strong AI) refers to systems that can perform any intellectual task that a human can do across multiple domains, such as common sense reasoning, creativity, and self-awareness. General AI is still a hypothetical goal that has not been achieved yet.
The main difference between computer automation and artificial intelligence is that automation does not necessarily involve intelligence or learning (no training required), while AI does (training required). Automation is based on predefined rules and patterns that are programmed by humans or derived from data. AI is based on algorithms that can learn from data and experience and improve its performance over time. Automation can perform repetitive or routine tasks that are well-defined and structured. AI can perform complex or novel tasks that are ambiguous and dynamic.
However, computer automation and artificial intelligence are not mutually exclusive. They can work together and complement each other to create intelligent automation systems that can adapt to changing environments and user needs. For example, robotic process automation (RPA) is a form of automation that uses software robots to mimic human actions on a computer interface. RPA can be enhanced with AI techniques such as machine learning (ML), natural language processing (NLP), computer vision (CV), and optical character recognition (OCR) to handle unstructured data, extract information, understand context, and make decisions. Another example is industrial automation which uses sensors, actuators, controllers, and communication networks to monitor and control physical processes. Industrial automation can be integrated with AI techniques such as deep learning (DL), reinforcement learning (RL), anomaly detection (AD), and predictive analytics (PA) to optimize performance, detect faults, prevent failures, and improve quality.
Computer automation and artificial intelligence are two different but related concepts that have significant implications for various fields and industries. It is easy to confuse or conflate the two because many industrial and commercial applications blend the technologies. What you need to know is this, using the terms interchangeably has the potential of causing a litany of problems in expectations. There will be tasks that computer automation simply cannot do; there will be tasks that AI is ill-suited for. It is important to understand what you are trying to achieve, and then leverage the right technology most practically. I realize this is easier said than done. That is why it requires a lot of smart people to design, implement, and support modern technology-based systems, especially ones that incorporate computer automation and AI.
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