ENABLING EXPLAINABLE ARTIFICIAL INTELLIGENCE (XAI) TO NARRATE PATENT SCENARIOS IN DEVISING SCIENCE POLICY DECISIONS & TECHNOLOGY FORECASTS

Abstract

Machine learning methods, offering unique characteristics for variable identification and its importance, are now gradually occurring. The are now used for prediction, forecasting, and devising important scenarios for integrated decision-making. It shows that sequential and dynamic growth in emerging technologies can fundamentally become a foremost indicator to measure technology strength in innovation and development.

Similarly, prudent and systematic data generation is part of the evidence analysis and service/product development. Assisted machine learning solutions provide data-driven prediction for medical analysis, fraud detection & disease detection, etc. providing solutions with explainable intelligence. Assisting solutions with more data-driven explainable solutions, during the performance of advanced machine learning has created impactful stage for generating white box solutions out of the black box interpretation. Explainable artificial intelligence provides superior and solution-based AI, optimal solutions and an impactful decision-making solution.  The approach of explainable artificial intelligence being used here represents the assessment for ML algorithms to predict accurate results. It is well represented that innovation and development can be identified via various innovation indicators, where patents are one of the important solution providers for futuristic technologies. In this paper patent data obtained from the Organisation for Economic Cooperation and Development (OECD) database, are used of patents for India have been taken to represent technological mandate.

Key Words: Analytics, Organisation for Economic Co-operation and Development (OECD), H2o.ai, Explainable Artificial Intelligence (XAI), Machine Learning, Decision Science