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Automation Is Not Intelligence

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The AI Hype Train has left the station. You know you’re in the middle of a hype cycle when products and companies start using a term regardless of whether or not their product incorporates any of that technology. This is where we currently are with regards to the market for AI products and services. While there is a lot of great, new innovation that’s pushing the industry forward towards more intelligent systems capable of many of the challenging areas that have previously not been able to be solved due to extreme complexity or the need for human labor, there are just as many companies who are using the term AI as more of a marketing ploy or a way to raise money.

Many firms are claiming to be AI-enabled when all they have done is put some thin capability provided by a third-party library or API that doesn’t really transform their existing product into something that is inherently different with that new intelligent technology. One of the biggest offenders of this AI-as-a-buzzword is the entire Robotic Process Automation (RPA) market. While automation is they key word in this phrase, this corner of the process automation market somehow is identified not with the traditional workflow automation and Business Process automation or management (BPM) space that has existed for decades, but rather the more widely hype and strongly invested in AI space. This whole category is currently attempting to rebrand itself as intelligent and AI-enabled because they’ve added OCR or some other add-on. While automation is valuable and provides a ROI in and of itself, there’s no reason to conflate automation activities with intelligent activities. Automation is not intelligence.

What is automation?

Automation is not a bad word. The primary movement of the industrial revolution was to take much of what we were doing at the time with manual labor and automate that work so that we could achieve significantly greater productivity, quality of life, and transform society as a result. Automation is the process of applying technology to some repeatable task or process so that the task or process can be accomplished with predictable repeatability, lower total cost of operation, increased safety, and provide better efficiency. This is what we demand of most of our technology, and technology has delivered that value. In fact, technology continues to deliver increasingly greater value to enterprises and individuals, squeezing more efficiency and capabilities and increasing productivity on a daily basis. So, automation is good. There’s nothing bad about it.

Mechanization and the unleashing of power from steam and electricity, the development of the assembly line and factorization of manufacturing, and the evolution of computing and the Internet have truly revolutionized the way we work, live, and exist. However, while these are fundamentally potent and transformative technologies, they are not intelligent technologies. We can’t walk up to a steam engine and ask it to recognize who we are or answer a random question or even learn from its experiences. A web server is just a web server no matter how many times it’s served the same content to the same sort of people. Automation has provided enormous and fundamental value to society. However it is different than the value we are seeking from intelligent systems, because automation is not intelligence.

Intelligence is much more than automation

Humans demand more from intelligent systems than simply repeating or simplifying a repetitive task that requires zero cognitive skills. From the beginnings of what researchers have been attempting to do with AI, we’ve been striving for systems that can understand and comprehend their surroundings, learn from their experiences, make judgements and decisions that are based on rational thinking, handle new situations and apply their learning from previous experience, and perhaps even address bigger questions of self-awareness, consciousness, and more. These are complex problems AI researchers are trying to solve, and fundamental questions of cognition including self-awareness and reasoning.

We’re nowhere near the goal of achieving Artificial General Intelligence (AGI), which is an intelligent system that can perform all the cognitive tasks that a human can do with the same agility and handling of ambiguous environments. Yet, that doesn’t mean the current range of narrow AI applications are not helpful. Recognition systems, pattern and anomaly detection, machine learning approaches to predictive analytics, autonomous systems, conversational interfaces, goal-driven systems, and hyperpersonalization are all patterns that are immediately realizable by current AI technologies and approaches. As such, it should be expected that we’ll see more of those in our daily interactions with technology. This is what makes the automation-as-intelligence peddling even more perplexing. We clearly have the technology to enable basic levels of cognition. Therefore, we should be seeing more of that in the technology, not just more approaches to repeating the same thing over and over. No one would argue that facial recognition is automation, because intelligence is not automation.

Vendors that push automation solutions as intelligent are potentially hurting the industry. If customers are lead to believe that various automation solutions are what they can expect out of AI systems and humans are required to add intelligent components on their own to call their systems intelligent, then the industry is heading for a rapid correction. If we want to avoid another AI Winter, then the desired outcome of AI is one in which we’re solving increasingly harder problems that have not before been able to be solved by using systems that can learn and adapt. We have to ask more of the systems that call themselves artificially intelligent. 

When the vendors say their products have AI capabilities, don’t take them at face value. Ask how their offering is going to learn and adapt and perceive the environment. Ask what data they used to train their model. Ask how machine learning is being used not just as a bolt-on to existing automation but to make the automations themselves more intelligent. Find out how AI will replace a human who needs to define a process or decision making step. Companies that are truly building AI-enabled products in a way that will help the industry mature are the ones that are worth paying attention to in the context of AI, rather than in the context of automation.

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