At the Institute for Political Strategy and Applied Economics, our values serve as the cornerstone of our mission and guide every aspect of our work.
Collaboration is at the heart of our approach, as we believe in the power of diverse perspectives and interdisciplinary cooperation to generate innovative solutions. We are dedicated to advancing knowledge, informing decision-makers, and actively fostering the evolution of human society. Our commitment to societal impact drives us to translate our insights into informed and actionable policies and strategies.
We believe that policies should serve as facilitators, not barriers, to innovation, acting as conduits of comprehensive information to navigate complexities and empower science and enterprise to capitalize on opportunities while considering widespread impacts.
Embedded within our work at I.P.S.A.E. is a robust theoretical framework that encompasses advanced methodologies such as embracing Behavioral and Engineering Design Innovations.
Simultaneously we strongly believe in the value of Tacit Knowledge and non-transferrable skills, and we endeavor to evolve the conceptual framework for enabling their transferability and integration.
We aim to develop a situated Function-Behaviour-Structure (FBS) framework that provides a more comprehensive understanding of the design process in a constantly changing world.
The Institute aims to be at the forefront of applying the Behavioral Problem/Solution (BPS) matrix in our research and policy analysis. This approach systematically examines the interactions between problem features and solution principles, drawing on an extensive analysis of behavioral design interventions across various domains.
By harnessing the power of big data analytics, artificial intelligence, and machine learning, we will push the boundaries of what is possible in our field, setting new standards for research, policy-making, and strategic planning.
Institute for Political Strategy and Applied Economics is at the forefront in the research of Tacit Knowledge and in the development of theories and practices that bridge between tacit knowledge, symbolic knowledge, rigorous knowledge and machine learning, which in the case of black box AI represents a new frontier to navigated: the cascade of multiple layers of unexplainable, yet effective, sets of rules and knowledge.