1+1 > 2: Integrating Analytical Techniques in the Age of AI
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Abstract
The premise that combining analytical techniques yields results greater than the sum of their parts, captured in the expression 1+1 > 2, has gained renewed urgency in an era marked by the proliferation of artificial intelligence (AI), the explosion of unstructured data, and mounting pressure on researchers to demonstrate both rigor and relevance. However, integrating methods remains more promising than practice in many fields. Survey evidence indicates that while 87 percent of organizations have adopted AI for task automation, only 23 percent employ it in strategic decision-making (McKinsey & Company, 2024; MIT Sloan Management Review, 2024). Similarly, despite decades of methodological pluralism in the social sciences, the dominant mode of inquiry continues to privilege single-technique approaches that sacrifice contextual richness for analytical tractability. This editorial argues that the contemporary landscape demands a different paradigm: one in which hybrid architectures — combining frequentist and Bayesian inference, structured and unstructured data, human judgment, and machine computation — are the norm rather than the exception.
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