It is important for cities to understand and adopt intelligent automation to advance their smart cities strategy, or risk falling behind.
AI and ML can rapidly detect gaps or abnormalities on agency networks, and respond with a programmed, precautionary or reactionary action immediately.
The hope is the community will feed into a larger initiative, aimed at embedding AI professionals within agencies to help improve services to the public.
During a recent cybersecurity conference, major federal figures expressed worry about threats ranging from China to deepfakes.
Public sector leaders need all the help that they can get in defining their Smart Cities strategy. With programs like the Smart Cities Innovation Accelerator by Harvard, it’s clear that academia is leading the way in offering this guidance.
This month, the Defense Logistics Agency (DLA) released a foundational data and analytics document that will direct data governance, acquisition strategies and the incorporation of emerging technologies for the military’s combat logistics branch.
Leaders in government and industry must be thoughtful and circumspect as we race to the future. We must consider not only the implications of replacing humans with machines, but also the fallout of treating humans as machines along the way.
Agencies will struggle to adopt artificial intelligence (AI) if they don’t consider how it will impact their employees, according to two federal officials.
What makes a community intelligent? How is it different from a smart city?
Artificial intelligence is trending, but fears of bias and discrimination can cause public outcry. In Canada, the public and private sector work together to mediate concerns.