Reading the Robot Mind

"Update Robot Doctor Now?"​ Gulp! In April 2019 the US Food and Drug Administration proposed a new regulatory framework that would cover when a robot doctor gets a software upgrade. Yikes! Naturally, they didn't use the term "Robot Doctor." The FDA calls a robot doctor an "Artificial Intelligence/Machine Learning (AI/ML) Based Software as a Medical Device (SaMD)." Whether you call it a robot doctor or a AI/ML SaMD, they show up in your daily life in the form of devices and machines that use software to inform or even drive medical decisions, and in certain cases, even treat or diagnose without the need for human intervention. These are definitely very different classes of devices! Most of the devices we encounter deal with non-serious healthcare situations, like standing on a bathroom scale that also informs you of your BMI. Sometimes though, the healthcare situations are serious or even critical. It makes sense to treat each of these situations, and a...

Introduction to this Blog: Research interests include pattern analysis and machine intelligence. My machine learning programming focus is what I call "Reading the Robot Mind" which is closely related to "explainability." This ability to peer into the inner workings of trained inference engines is needed in order to spot intentional and unintentional bias, privacy violations, and performance bugs. The techniques discussed here relate to reverse processing of neural networks, so that example input data can be generated for different categories and classes. Similar to Generative networks, as well as Autoencoders, the premise is that a subject matter expert should be able to qualitatively assess the performance of a trained AI system, without the need for programming expertise. Keywords include: Pattern Analysis Machine Intelligence PAMI Reading the Robot Mind Mind Reading Generative Networks Generative Adversarial Netowrks GAN Autoencoder Auto Encode Subject Matter Exp...