In this episode, co-hosts Jennifer Miller and Ron Landis discuss the emerging field of artificial intelligence (AI). In particular, they discuss machine learning and two broad categories of algorithms, unsupervised and supervised learning.  

In this podcast episode, we had conversations around these machine learning questions:  

• What is artificial intelligence?  
• What is machine learning?  
• What are some applications of machine learning in People Analytics?  
• What is the difference between supervised and unsupervised learning?  

4 Key Takeaways on Machine Learning

• AI is the field of computers simulating human capabilities to process data. Several examples of AI exist in our everyday environment including products like Alexa and Siri and other processes like financial detection fraud, purchasing recommendations, and driverless cars.  
• Machine learning helps automate the analytic process. Supervised learning is an approach that predicts or classifies outcomes via "labeled" datasets. In this approach, the user has to determine the outcome and inputs that are used by the algorithm. Regression is a common type of supervised learning.  
• Unsupervised learning is an approach that uncovers hidden patterns in the data utilizing "unlabeled" datasets. In this approach, the user does not contribute to the initial model building process. Cluster analysis is one example of an unsupervised learning technique.
• Ron and Jennifer discuss how machine learning can be used in the context of People Analytics.