YSUY: Your Smartphone Understands You—Using Machine Learning to Address Fundamental Human Needs

Most machine learning (ML) models are geared toward improving some desired metric like classification accuracy or inference latency. Given the significant successes of such models, especially supervised ones, in addressing such metrics, the time has come to ask if they can also be put to direct use in understanding the users and addressing basic human needs, e.g., subsistence, protection, affection, understanding, participation, leisure, creation, identity, and freedom. A prerequisite to addressing such human needs is that the ML models exhibit a basic grasp of human psychology. In this article, we present ML models that can be embedded in our smartphone and enable it to understand us. We call this system your smartphone understands you (YSUY). YSUY uses wearable medical sensors to understand our physical, mental, and four-class (two-class) emotional states with 90.0%, 90.3%, and 98.4% (99.5%) accuracy, respectively. After verifying YSUY’s ability to understand the human condition from various perspectives, we evaluate the relationship between the different states and discuss how YSUY can be taken one step further to start playing a helpful role in addressing human needs of the types mentioned above from four different perspectives: “being,” “doing,” “having,” and “interacting.” We show that YSUY is a a promising candidate for adapting ML models to human-centric needs. We view this only as an initial step, hopefully, spurring other researchers to investigate the relationship between ML models and fulfilling human needs in much greater depth.