[ESSEC Knowledge] by Vivianna Fang He - Professor at ESSEC Business School
The article discusses the role of researchers in the age of artificial intelligence and machine learning. While AI can identify complex patterns in large datasets and make predictions, it has not replaced the core tasks of researchers, particularly theory-building. Researchers can benefit from integrating machine learning techniques into their work, especially for pattern detection in data and enhancing predictive accuracy. Machine learning helps avoid issues like overfitting and can make the research process more transparent, reducing researcher bias. However, human expertise remains crucial for defining research factors, explaining relationships, and interpreting patterns.
The authors propose a four-stage procedure that combines machine learning and human input to enhance research. This approach has been applied in various disciplines, showing its versatility. Nevertheless, researchers should consider the stability of phenomena and potential biases when using machine learning. In summary, researchers are still needed, and machine learning complements their work by improving research robustness.
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