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.
Looking for better ways to analyze data? Do you want to see how other offices are simplifying computational tasks? Then come out to the Government Advances in Statistical Programming (GASP!) workshop. This is a one-day workshop with a wide range of speakers who will present their work using open-source software for either analysis or dataRead… Read more »
AI systems are igniting new opportunities across industries, but you must start your AI journey by building a technical infrastructure that will support it.
AI solutions drive informed human capital management, using data-driven insights to put employees in situations where they can succeed.
by Daniel Chenok, Executive Director, IBM Center for The Business of Government Contributors: Claude Yusti, Tatiana Sokolova with IBM, and Katie Malague and Peter Kamocsai with the Partnership for Public Service Few technological innovations offer the many potential benefits of artificial intelligence. AI tools range from entertaining to productivity-improving to life-saving, from playing poker orRead… Read more »
In this post, we talk about what most people ignore — the risks of AI. Prior to deploying the technology across your organization, it’s critical to identify and understand these risks and have a plan in place to mitigate them.
As with every new technology, AI comes with its own set of challenges, especially in the realm of data and compute. Data is the raw material of AI; the more data you have, the more accurate the AI learning process will be.