The REAL Framework
Character Strengths as Emotional Signals
Human emotion is structured around stable, cross-cultural character strengths revealed through behavior, language, and choice - or through opt-in enthusiasm of 850 million fans of positive psychology globally who already seek to exercise their character strengths in their time spent, purchases and media.
When emotional expression aligns with underlying character, people experience meaning and connection. Incongruence produces friction, distrust, and disengagement.
Congruence Builds Trust
Explainable by Design
REAL translates emotional dynamics into measurable, auditable signals that integrate cleanly into modern AI systems without black-box ambiguity.
Composable by Design
REAL can be deployed as a standalone emotional intelligence layer or composed across creative, targeting, personalization, and governance systems — without replacing existing stacks.
Integration & Licensing
REAL Engagement AI operates as a licensable intellectual framework supporting system integration, product design, emotional alignment standards, and long-term governance of emotionally intelligent systems.
We partner with organizations building technology where emotional intelligence must be effective, explainable, and durable over time.
Origin
REAL Engagement AI emerged from clinical and human-development research into positive emotion, meaning, and character — not from persuasion technology or attention optimization.
Our goal is not to make systems more persuasive.
It is to make them more human-compatible, trustworthy, and sustainable at scale.
Framework
REAL Engagement AI is built on the premise that emotion reflects meaning, values, and character — not merely stimulus and response.
Our framework enables emotionally intelligent systems to remain aligned, interpretable, and trusted as they scale across domains and use cases.
Resources
Primary References
Journal of Marketing Research (JMR) — Character Strengths & Consumer Behavior
https://journals.sagepub.com/home/mrj\ Peer‑reviewed research published in the Journal of Marketing Research, with Olivier Toubia as primary author and Renée Bunnell as coauthor, in collaboration with Columbia University researchers. The study demonstrates that character strengths are predictive of consumer preferences and purchasing behavior, establishing character strengths as measurable signals relevant to marketing, media, and decision contexts. This work informs REAL’s use of character strengths as a predictive, humanistic metric rather than a persuasive tactic.
IEEE Standards Association — Ethically Aligned Design & Autonomous Systems
https://standards.ieee.org/industry-connections/ec/autonomous-systems.html\ IEEE standards and guidance for autonomous and intelligent systems emphasize human well‑being, transparency, accountability, and alignment with human values. Emerging IEEE work on flourishing and human‑centered metrics explicitly supports the use of character strengths and virtues as evaluative measures for autonomous and agentic systems, aligning with REAL Engagement AI’s humanistic and APA‑compatible approach.
Association of National Advertisers (ANA) — Digital Character and the Humanization of Brands
https://www.ana.net/miccontent/show/id/kp-emoto-digital-character-humanization\ An ANA Insights article by Renée Bunnell examining how character‑based, humanistic branding drives deeper engagement, trust, and long‑term brand value. The article translates academic findings (including JMR research) into applied advertising and brand strategy contexts beyond clinical psychology.
Journal of Marketing Research (JMR) — Character Strengths & Media Effectiveness
https://journals.sagepub.com/home/mrj
Peer‑reviewed research published in the Journal of Marketing Research, in collaboration with Columbia University researchers, demonstrating that character‑strength–congruent media significantly outperforms non‑congruent media on measures of engagement, meaning, and commercial effectiveness. This work anchors REAL’s approach to emotionally aligned media and system design.
VIA Institute on Character — Character Strengths Research
https://www.viacharacter.org
Decades of peer‑reviewed research establishing 24 cross‑cultural character strengths and their relationship to emotion, behavior, and well‑being. VIA’s work underpins the scientific validity of character strengths as stable, measurable psychological constructs used globally in research and applied settings.
KRW International — Character‑Based Leadership Research
https://www.krw-intl.com
Longitudinal studies across Fortune‑100 organizations, including a widely cited KRW analysis finding that CEOs and senior leaders who consistently applied character‑based leadership practices achieved up to a 5× increase in return on assets (ROA) compared to peers. The research links character alignment to trust, decision quality, cultural coherence, and sustained financial performance.
Harvard Business Review — Why Character Matters in Leadership
https://hbr.org/2015/01/why-character-matters-in-leadership
This article synthesizes research on leader character, trust, and performance, reinforcing the business relevance of character‑based leadership frameworks examined in KRW’s work.
Columbia University & Columbia Technology Ventures — Research & Commercialization Partner
https://techventures.columbia.edu
Columbia Technology Ventures supported the translation of character‑based research into applied commercial contexts, bridging academic validation with real‑world deployment and licensing pathways.
Secondary & Contextual References
Jebara, T. — Machine Learning: Discriminative and Generative
(Springer; Columbia University)
https://www.springer.com/gp/book/9781402076481\ A foundational text by Columbia University professor Tony Jebara on modular and compositional approaches to machine learning. The book presents methods for combining heterogeneous signals and representations within unified models, providing theoretical grounding for composable AI architectures relevant to agentic, multi-layer, and human-aligned AI system design.
Bunnell, R. (2014). Research on Positive Appraisal Sensations
(Research findings; citation available upon request)
Early empirical research demonstrating that character‑congruent media produces significantly higher positive emotional appraisal and improved conversion outcomes compared to non‑congruent content.
Experian / Mosaic Segmentation Studies
https://www.experian.com
Third‑party dataset analyses demonstrating that large population segments exhibit distinct character‑strength profiles, supporting scalable personalization and alignment in commercial systems.
Brynjolfsson, Li & Raymond (Stanford / MIT) — Human–AI Collaboration Research
https://www.nber.org
Large‑scale field studies showing that human–AI collaboration improves productivity, decision quality, and task throughput, supporting REAL’s human‑centered, augmentation‑first approach to intelligent systems.
Ju & Aral (MIT) — Human–AI Team Performance
https://ide.mit.edu
Experimental research demonstrating that mixed human–AI teams outperform human‑only teams on complex tasks, highlighting the importance of alignment and interpretability in AI system design.
American Psychological Association — Ethics & Human‑Centered AI
https://www.apa.org
APA guidelines emphasize transparency, beneficence, non‑maleficence, and respect for human autonomy, principles that inform REAL’s approach to explainable and psychologically aligned emotion AI.
Empire AI Initiative — Explainable & Ethical AI
AI. https://www.empireai.org
Public‑sector initiative promoting transparent, explainable, and ethically aligned AI systems in high‑impact domains, aligned with REAL’s humanistic emotion framework.
Columbia University — Digital Twins & Character Strengths (Ongoing Research)
https://www.columbia.edu
Ongoing academic research exploring how digital representations of individuals can reflect stable character‑based patterns over time, informing emotionally congruent personalization and system design.