Introduction

Jordan Caldwell

The State of: Language Arts & Research (2023)

Affective computing is a framework of study for developing computational systems that may recognize, interpret, process, and simulate human affect¹. The framework affirms emotion as a central facility in rational decision-making, such that it sets out to enhance computer logic with emotion-driven capabilities. Dealing with emotional intelligence, as it remains an overlooked grey area in most modern cultures, the advancements to machines proposed by affective computing carry precarious possibilities. Latent potentials point towards a future where artificial intelligences (AI) may extend past the emotional aptitudes of conscious humans on the planet. Modernized culture’s state of emotional ignorance stems from a recent history where philosophy and sciences fail to address the implicit learning and unconscious patterns that control explicit thinking². AI systems designed to work with data mined from the human unconscious now awaken us to critical blind spots, including stalled progress in emotion theory. 

Part of the reason why emotion theory has seen so little progress is that emotional patterns depend on the context in which they are elicited. So far, this research has been limited to lab settings, when real-life observation provides ideal scenarios. Historically, carrying studies outside of lab environments with realistic results presented difficulties, and new theories rarely developed. Although some experiments may be valid within controlled lab settings, most cannot claim to have validity to true life experiences, which is also due to severe lack of representation amongst study subjects³. Greater breadth of observational, in-situation studies are more achievable now thanks to recent commercial developments and the market research they require. At the same time, commercial endeavors also aid in loopholes away from greater knowledge access, including emotional learning⁴. Systemic obstructions to emotion theory, inside and outside of lab-based information systems, mitigate the fertility of affective language; collective tools needed for working with the feeling self that have not received light to grow. Emotion retains copious illegible forms, making it hard to tap its prescient role within our intelligence structure. 

We are presented with a two-pronged problem requiring a multifaceted approach. One prong, what this project sees as second of the two, is the need to develop and implement affective computing systems in order to support emotional fitness. If we are to practically while safely reap the benefits of emotionally intelligent advances in technology, an earlier prong is called forward: a prerequisite that is the learning, retention and embodiment of affective wisdom and emotional understanding. For example, there is a reason why people must learn to drive before there is a need for building faster, more complex cars.

Raising individual and global consciousness can help us improve personal and collective health, well-being and harmony. We suggest that this begins with people taking greater responsibility for their day-to-day decisions, actions and behaviors, which can result in establishing a new and healthier physiological and psychological internal baseline reference.

‍The Intuitive Heart (2014) HeartMath Research Center

Holding both prongs in body and mind, Resonance is an intimate research domain⁶ for developing calm technologies⁷. The project’s goal is to support human orientation, as well as development toward integrated emotional access. The conceptual framework threads together ideas about physical resonance, audiovisual media, internal emotion architecture, and methods for observing an emotional baseline. The methodology acknowledges the lack of real-life observation and inclusive representation in emotion theory, and aims to proactively address privacy concerns that increasingly surround personal biometric data, while also integrating the values of the open source community. By generating alternative tools, mindsets and approaches for affective computing, this research intends to engender and promote reflective self-healing modalities. 

The motivation for this paper is to ground the context that Resonance sits within, in the realms of both intangible ideology and tangible reality. Establishing this referential frame will serve to inform any future ideas that emerge within the Resonance research domain. The following sections of this paper discuss adverse effects of the modern technology development paradigm; look at how emotion is regarded in this paradigm; and calls forth divergent contextualization to further affective computing; advocating a balanced technoculture in support of bidirectional emotional learning between humans and machines.  

To these endpoints, Resonance works with language forms and “self-orienting” design as key tool and mindset categories, respectively. Keys in the sense that they can enable access to pathways  that are yet to be traversed. Pathways are meeting places, directions, journeys and wanderings; they show us to opportunities for communal work like decoding emotional grey areas, building shared language, and seeing personal technologies as powerful intermediaries for affective awareness.