The Key to Scalable AI Decision-Making? Even Better Training Data
If you learn nothing else from this blog, remember this: The most important step in adding AI to any process is correctly labeling the training data.
If you learn nothing else from this blog, remember this: The most important step in adding AI to any process is correctly labeling the training data.
It’s easy to get caught up in the hype and to forget all the groundwork and tactical steps it takes to effectively establish and use AI in an organization.
The sooner organizations embrace change and ready their staff for adoption, the sooner they can realize AI’s benefits. So, what’s the hold-up? In a word, culture. Changing the underlying principles of an organization takes time and serious effort.
Whereas repetitive and basic tasks in a traditional setting can take tens of thousands of hours to complete, software-enabled bots can accomplish these same tasks with rapid speed and infallible accuracy.
An agencywide data governance strategy puts the policies into place to take stock of data, standardize reporting, implement security procedures and discover potential use cases for data.
Traditional data platforms are insufficient in meeting the demanding requirements of a government that must move fast and make data-driven decision
There’s a popular saying that “numbers never lie.” It has a nice ring to it, but in reality, the adage requires that the numbers share a common language.
Governments of all sizes have created data and analytics departments to assess what they have, coordinate communication between agencies and report stories that the numbers show.
Data by itself doesn’t solve problems or bring value to an organization. We need to move beyond the data, and work on harnessing its value to the organization.
SaaS solutions help local governments offer better, more flexible services to their residents. If recent developments are any indication, partnerships between tech innovators and City Hall will transform the way people think about public services.