NYC311 has made great strides in evidencing the power of data analysis and innovation within the government, through opening up its data. Now it needs to build capacity in-house and answer tough questions to solidify the long-term impacts of open innovation.
Intelligence agencies are considering open innovation to better predict geopolitical trends and to better respond to the new face of terrorism. Is this a great idea or a misguided attempt at forecasting the future?
Rapid-Flow is solving traffic congestion by offering governments a real-time traffic signal control system powered by machine learning.
Could open innovation initiatives allow U.S. governmental agencies to tackle intractable problems more quickly and cost effectively? Could the U.S. government effectively transition to open platforms to address its most contentious and politicized challenges?
Following alleged Russian interference in the 2016 U.S. elections, voting-machine vendors face increasing public pressure for more open innovation of its products to enhance security.
While machine learning is typically discussed in the context of major technology companies, city governments, institutions rarely thought of as innovators have begun to use machine learning to better understand the data they collect and use those insights to improve their processes.
An examination of the potential to harness big data to improve public health and safety using natural language processing.
Governments have to innovate to meet the growing and complex demands of its constituents, but how? And with who?
How do we thoughtfully use data to increase efficiency for the greatest amount of people in a sector that has historically and exclusively been driven by human judgement? Where is human oversight non-negotiable?
vTawain–a government crowdsourcing platform–takes citizen input on how to legislate up and coming industries
