When people mistake control for AI

Yesterday I came across this video on LinkedIn. The poster commented, sarcastically, that he could not wait for AI to take over the world. Of course, I understand the sarcasm and the joke, but looking at the discussions underneath the post, I also concluded that a lot is to be learned, by many. Hence, I decided to spend a little post on it myself, to give my complete view, based on a number of comments I wrote on the original post.

Photo by David Levรชque on Unsplash

What bugs me with the whole story is that there seem to be a number of misconceptions that get into peopleโ€™s minds when they see this video. There are two that I want to point out explicitly here.

First of all, this is an automated system, not an artificial intelligence solution. Robots and sensors have been running production lines for decades already, without what we now call AI. This robot can be controlled using a simple closed loop of sensors and actuators to control the motions, without any need for complex data analysis of the kind that is done in neural networks and other learning systems. As simple camera or sensor is sufficient to tell the software controlling the robot whether or not a bun is in the present in the correct position, or whether the bun is covered by a bag in step two of the process shown. In short: what is missing is not AI, what is missing is the normal closed loop of a control system.

Second, and more important, this is not an AI or software problem. Yes, the robot is likely controlled by software, but the problems shown here are first of all hardware flaws. If a sausage needs to be put in a bun in a system like this, the bun should be properly supported by guides so that it doesnโ€™t fall sideways if the sausage hits it by accident. Same for the โ€˜bagging stationโ€™: the slide on mechanism looks nice, but fails because the bags are too short relative to the support for the bun. A โ€œdrop the bun in the bagโ€ solution would be much more robust. It would drop the bun into a bag underneath, even if someone filled the system with too small bags. Blaming the software for these things indicates a lack of systems thinking: the system consists of hardware (robot, supports) , software (control), and consumables (the food and the bags). The overall design of mainly the hardware is wrong here. The mindset of many machine building companies is that โ€œthe software will fill the gapsโ€. That is impossible in this case, ergo the whole system needs to be redesigned.

My take on this, based on the video, the comments it drew and what I wrote above:

  1. The video hopefully shows an intentionally failing system, no company in their right mind would release a system like this to production
  2. Despite over 50 years of designing systems that combine hardware and software, it is still hard for manby to see the system rather than the (discipline defined) parts
  3. There is a huge misconception of what AI is โ€” a robot controlled by software is not AI, assuming it is in this case disqualifies control systems engineering as well as AI.



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Angelo Hulshout ๐Ÿ‡ณ๐Ÿ‡ฑ๐Ÿ‡ฎ๐Ÿ‡น

Angelo Hulshout ๐Ÿ‡ณ๐Ÿ‡ฑ๐Ÿ‡ฎ๐Ÿ‡น


CEO at Schinchoku and software architect at Delphino Consultancy B.V. โ€” writing about software, and about the Shinchoku startup.