(US and Canada) Justin Marsico, Chief Data Officer and Deputy Assistant Commissioner, U.S. Bureau of the Fiscal Service, and CDO Magazine Global Editorial Board Member, speaks with Denise Collison, SHI International SVP and President of Public Sector Sales, in this video interview about moving data to the cloud and the differences between artificial intelligence and machine learning.
Marsico says the Bureau of the Fiscal Service is in the early stages of moving its data to the cloud. Some of the organization’s systems are cloud-based and some are on-premises. He highlights the importance of considering the state of data in the systems and databases and the extent of work required while transitioning to leverage cloud capabilities. He adds that a key step is to avoid old work patterns and simply port data to the cloud.
He says MI is the ability of a machine to take over some type of processing typically done by humans. With AI, processing tends to be more cognitive and focuses on activities such as understanding complicated problems. Machine learning use cases tend to be more about feeding back data and having an algorithm that is self-learning and self-reinforcing.
Speaking further on the topic, Marisco explains that advanced analytics is separate from regular analytics and contains both AI and ML within one bucket. He reveals that the Bureau of the Fiscal Service is trying to create analytics capability across the workforce in the organization.
Marsico maintains that advanced analytics needs to be centralized and cannot be used by people who don't have the expertise and need to learn how to test it.
In conclusion, he says that the Bureau of the Fiscal Service wants to deploy AI and ML responsibly to avoid unintentional bias.
CDO Magazine thanks Justin Marsico for sharing his data and analytics insights with our global community.
See more from Justin Marsico