A Framework for Strategic and Responsible Predictive Modeling in the U.S. Technology Industry and How It Improves The Company

Powered by recent breakthroughs in machine learning, predictive modeling has become a cornerstone of the modern digital economy. It is generally considered a major source of competitive advantage for the most successful U.S. technology firms. The current study is a guided inquiry into the presence of predictive models in the U.S. technology industry, a panoramic overview of its uses and applications, and the machine-learning approaches that enable its functionality, as well as the major limitations in the realm of model correctness: that is, accuracy, fairness, and security. By examining empirical research and initiatives applied in leading technology companies, a consistent body of issues that may complicate the successful and responsible use of these potent instruments will be considered. A new concept, model-based and named the Responsible Predictive Modeling Deployment Framework (RPMD), is offered to address these challenging aspects of integrating technical validation, fairness and bias auditing, and continuous observation. The results indicate that the use of such a structured framework is non-negotiable in efforts to alleviate risks, foster consumer trust, and protect the advancement of U.S. national interests by maintaining the U.S. as a world leader in technological innovation.