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AI for Management Science

(Northwestern University - ROC (Taiwan) Student Association at Northwestern)

- Overview

Artificial intelligence (AI) is reshaping the research philosophy and methodology of management science. In empirical research, some researchers have asked: Is traditional empirical research based on sampling (as opposed to full samples based on big data and AI) dying? In analytical modeling, "heuristic" methods based on AI are better than "optimal" methods. Scholars are worried whether the era of OR (operations research) will end? 

In terms of qualitative methods, new methods such as robot-assisted ethnography, AI archival research, AI-assisted grounded theory, and a new generation of "text" mining are being developed. 

"Mind reading" or "face value" based on artificial AI has been used in bank borrower review and human resources management. Is it science or a new version of physiognomy?


- AI in Management Science

AI decision-making is revolutionizing business intelligence by analyzing vast datasets to improve decision-making processes. Machine learning, natural language processing, and computer vision are key components of AI that aid in faster and more accurate decision-making. 

Artificial intelligence (AI) can be used in many ways in management science, including:

  • Predictive analytics: AI can analyze data to identify patterns and trends, helping organizations predict potential obstacles, resistance, or areas of success.
  • Data management: AI algorithms can scan datasets for errors, inconsistencies, and anomalies, and then fill in missing values with estimated values.
  • Repetitive tasks: AI can automate repetitive tasks, freeing up managers' time to focus on more strategic and creative aspects of their roles.
  • Decision-making: AI can help managers make accurate predictions regarding future events and trends based on data sets. AI can also analyze the demand for products and services, competition, and other factors to simplify the team's decision-making process.
  • Maintenance planning: AI can be applied to production data to improve failure prediction and maintenance planning. This can result in less costly maintenance for production lines.
  • Demand forecasting: AI can help with more accurate demand forecasting.
  • Material waste: AI can help with less material waste.

An AI management system is an organic body consisting of a data management system and an expert system.


- AI Management Systems and AI Service Management

An AI management system, as specified in ISO/IEC 42001, is a set of interrelated or interacting elements of an organization intended to establish policies and objectives, as well as processes to achieve those objectives, in relation to the responsible development, provision or use of AI systems. 

An AI management system is a combination of an expert system and a data management system. It can develop models for information transmission and control, and provide technical solutions for AI applications. 

AI service management (AISM) is a new approach to IT service management that uses AI to enhance support and service delivery. 

AI software is a type of computer software that uses AI to process large amounts of data to solve tasks that require human intelligence. These tasks include: Image recognition, Video analytics, Generative AI, Voice recognition, Text recognition, NLP.



[More to come ...]



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