Raw LLM Responses

This story is blown waaaay out of proportion. From the available information and statements from the company, they are using a machine learning sensor (aka a person detector.) This module is **not** facial recognition in the traditional sense, it is more like facial *detection.* There are probably a thousand ways yot can wire a circuit to detect a human presence. Microwave, ir, radar, wifi/blutooth, co2, magnetic interference, capacitive sensors, object detection, ultrasonic sensors... the list will go on. We have gotten to the point with technology where one of the easiest and most efficient ways to detect a human presence reliably is by checking if the object has a face. These sensors are readily available and there is a ton of information out there. Several YouTube personalities in the maker community have covered these sensors and shown how they work. Here is a [link to the Github wiki](https://github.com/usefulsensors/person_sensor_docs) from the company that started making these sensors. Here is a [link to their research paper](https://arxiv.org/pdf/2206.03266.pdf) explaining the problems, concerns, and methodology for developing these sensors. **"AH HA! I Googled it and saw the word FACIAL RECOGNITION!!1!“** As mentioned before, this is not facial recognition in the traditional sense. It is absolutely true that this sensor can both detect your face *and* fingerprint your face, to which it will assign an identification number onboard. It can store this fingerprint ID for only **eight** faces. The idealogy for this fingerprinting is to give makers and enthusiasts access to an affordable and streamlined solution for projects, VS using large clunky cameras and associated hardware. Think more like "I made this thing that will automatically raise/lower my desk depending on which member of my family is there" and less like "we are building a database of 7 billion faces so we can control everything about you". This fingerprinting is mostly a vestigial feature tha