Translating the Experience of emotions into Numbers
Imagine an AI system that can understand the ups and downs of our lives just as well as a trusted friend. Owing to advancements in artificial intelligence (AI), this is becoming an increasingly realistic possibility. However, the development of emotionally aware AI is not without risks. One of the major concerns with this technology is the potential for emotional manipulation. Like optimizing AI for "engagement" on social media platforms, at the expense of "users" mental health. While emotionally aware AI has the potential to revolutionize our interactions with technology, we must also acknowledge the risks and challenges.
One of the main challenges in developing emotionally aware AI is the difficulty in defining and measuring emotions. Emotions are complex and multidimensional constructs, and there is ongoing debate and controversy within the field of psychology about how to best measure and understand them. Additionally, emotions are highly individualized, making it difficult to develop a standardized emotional framework that can be applied to everyone. To overcome these challenges, we are using a concept called emotion vector space, which is a mathematical representation of emotions in a multidimensional space. Our approach takes into account the most important emotional states measured in population-based mental health surveys. And by so doing, enables a more nuanced understanding of emotions such as fear, anxiety and despair, some of more challenging aspects of the human experience.
Explainability is another challenge when it comes to emotionally aware AI. As AI has the capacity to manipulate our emotions, it's important to understand how they arrive at their decisions. However, emotions are complex and subjective, and the inner workings of AI systems can often be opaque and difficult to interpret. This has led some experts to liken these systems to a "black box." To ensure ethical and responsible use of emotionally aware AI, efforts must be made to increase transparency and understandability.
Emotionally aware AI has immense potential to transform our relationship with technology, but it also comes with significant risks and challenges. Measuring emotions is complex, and explainability is a critical issue. However, by developing AI systems that prioritize transparency and incorporate a more nuanced understanding of human emotions, could be a net positive for human flourishing.