Code Notelets

The good Recently, the Photos app on my Android phone automatically curated some of my photos into a "highlights" album for me. I thought this was a fantastic idea. I love this use of AI - it does something quickly and easily that would otherwise take a lot of human time.  The only downside was that the AI included a close-up pic I'd taken of a spot on the skin behind my husband's ear so he could see it. Now, if this AI had instead been for a self-driving car, then too bad, we likely would've had a terrible wreck at this point - endangering myself, any passengers, and other drivers on the road. But since this application of AI for photo selection did not have any life-threatening consequences, I was all for it. The bad I've said before, and I'll say it again, that AI as it currently stands should not be used for self-driving purposes and I have explained clearly why. Indeed, I believe that AI should not be used for any purpose that may have life-threaten

I used to think neural networks were a reasonably good technology, until I decided to try setting up a neural network myself. After some experimentation with neural networks, I dramatically reversed my stance. I now believe neural networks should not be in charge of any decisions such that could have life-or-death impact. Find out why below. Disclosure: These are my personal thoughts about neural networks based on my limited experience with them. I do not claim to be an expert in neural networks. First I'm going to propose a definition for a neural network: An interpolation system whose behavior becomes undefined when extrapolating beyond its training data. In simple language, "undefined" may be thought of as "random by human standards". OK, how did this definition come about? It all started when I desired to make a system for classifying fonts a year or two ago. Even Google Fonts had at the time very few parameters for manually finding suitable fonts. For pick