Role play on Artificial Intelligence in the class

We all know of the very many ways in which Artificial Intelligence (AI) is playing a very important role in our daily lives.  From the very simple search on Google, to replying to our emails on Gmail, to translating docs from one of the popular languages on Google Translate to another language, to the use of Personal Assistants from Amazon, Google, Microsoft or Apple, the uses of AI are varied and colourful. 

One of the biggest challenges for an AI system is to collect enough training data to prepare the AI system to learn and help make correct future decisions. If we start on poor quality training data and low volumes of training data, the output also would be equally poor, incorrect and incompetent.

The availability of large volumes of high quality training data is gives organisation the early mover advantage. 

The entry of Google in the search domain decades back gives it so much of training data and strong algorithms that can help it get the right search output for your search inputs. It will be very difficult for a new search engine incumbent to beat Google in search at least for the next fifty years. 

Maybe a new SEARCH ENGINE player with a 

• radically different approach to AI effectiveness or 
• strong faster processors working on quantum computing or
• ultra fast communication protocol for the results from servers to customer desktops or
  
• an efficient, innovative and quick algorithm may be able to thwart Google.

The role play being designed in the class for students is to help them understand the importance of high quality training data for a high quality AI output. 

What are the different ways in which an organisation can try to collect large volumes of high quality training data in a short time ? (click here for interesting AI based case studies)

Can it collect this training data from 

• different functionally related areas, 
• geographically different areas 
• different set of customers
• equivalent product markets ??

Let us leave it to the ingenuity of the students to tell us from where to collect the training data to help the AI systems take the right decisions .. 

Ref : 1. Ajay Agrawal,Joshua Gans, and Avi Goldfarb, How to win with Machine Learning, HBR, Oct '20.

George..