Artificial Intelligence – Choosing to Be a Victim or a Victor
Last week, serial entrepreneur Mark Cuban created a stir with his statement at the SXSW (South by Southwest) conference that the world’s first trillionaire will be someone who masters artificial intelligence (AI). In the past, Cuban has been an avowed proponent of the value of a liberal arts degree for its ability to teach critical thinking. However, at SXSW, he advocated the study of computer science, stating, “Whatever you are studying right now, if you are not getting up to speed on deep learning, neural networks, etc., you lose.”
I have written about AI in the past, looking at its implications for both the workforce and education. I agree with Cuban that someone who masters AI in a new way will make a lot of money ($1 trillion sounds like a lot, but so did a billion a few years back). Anyone with a background in computer science should learn about deep learning and neural networks. However, I also think that there are other areas of future knowledge just as important. With the amount of data increasing at an incredibly fast pace, thanks to the Internet of Things and multiple smart devices that track our steps, location, heartbeat, driving, location, etc., data analytics has become an important field.
I recently visited a Boston company that created a database of email addresses for people in the U.S. and validated each address with publicly available data to associate them with a name and create a profile for each individual. URLs associated with the addresses allow the company to track web activities for each individual using that address. From that information, the company can build smaller datasets of people with similar consumer preferences.
The database has approximately 250 million unique addresses. I was not told how many fields exist for each address, but assume it is significant if individual information is included, along with sites visited from the most commonly used URL. The potential value of this database is immense. However, it’s not valuable if the data integrity is in question. The company did not disclose how many employees maintain, update, and validate the data, but I assume it’s not insignificant. Given the importance of consumer data to corporations and governments, there are likely thousands of similar databases, and I assume that many people are regularly involved in creating, updating, validating, and analyzing them.
Data analysis is grounded in statistics, with more sophisticated tools and techniques available for analyzing larger datasets. Every college student should be required to take statistics, and I recommend more advanced analytics courses to anyone seeking to understand how to assess large amounts of data. With larger and larger datasets, we shouldn’t make decisions based on medians or means without the tools to understand projected trends and variances.
Whether inside or outside the office, we should be wary of decision makers seeking to implement change by using often-misleading averages when the nuances of the data tell us something else. Understanding the basics of statistics and data analytics ultimately makes us better citizens as well. Taking the time to learn more than the basics provides us with more career opportunities as the data collected by corporations and government agencies continues to increase exponentially.