An Applied Inquiry Method for Interventionist Sciences - Meira, Silvio Romero de Lemos (Anais Estendidos do Congresso Brasileiro de Software: Teoria e Prática (CBSoft); 2025: Anais Estendidos do XVI Congresso Brasileiro de Software: Teoria e PráticaDO - 10.5753/cbsoft_estendido.2025.36967, 2025)
The 21st century’s most consequential applied disciplines, like software engineering, innovation management, marketing science, and strategic planning, face a profound epistemological crisis. These ”interventionist sciences” actively construct the realities they study rather than merely describing pre-existing phenomena, yet they lack methodological frameworks adequate for their constructive mission. Operating within complex ”phygital” spaces where physical, digital, and social dimensions are inseparably fused, these fields confront a validation crisis that threatens their scientific legitimacy and social responsibility. Classical scientific methods, designed for observational inquiry into stable natural phenomena, prove structurally inadequate for domains where intervention constitutes the primary mode of knowledge generation. Contemporary alternatives — Action Research, Design Science Research, and Lean methodologies — while offering valuable insights, fall short of providing the comprehensive, philosophically coherent, and ethically integrated framework required for navigating phygital complexity. This paper introduces the Adaptive Interventionist Method (AIM), a novel scientific methodology specifically designed for rigorous inquiry within interventionist domains. AIM operationalizes five core principles: phygital contextualization treating physical, digital, and social dimensions as inseparable reality; explicit ethical integration as an epistemically necessary component; model-centric epistemology focused on building adaptive representations rather than discovering universal laws; embedded observation and reflexivity acknowledging researcher participation in studied systems; and multi-dimensional validation concurrently assessing pragmatic utility, systemic viability, and ethical desirability. These principles structure a seven-phase inquiry cycle designed for adaptive learning in complex, uncertain environments. Recognizing the meta-methodological challenge of validating a new scientific method, we propose a novel ”bootstrapping” validation protocol wherein AIM systematically applies its own principles to test and refine its effectiveness through iterative real-world application. This approach offers a pathway for establishing methodological credibility while generating justifiable and responsible knowledge in the very fields that are actively constructing our sociotechnical future. AIM represents not merely a methodological innovation but a foundational step toward legitimate scientific practice for the disciplines shaping the 21st century.