Artificial Intelligence (AI) and Machine Learning technologies have steadily increased in number and capability over the past 10 years. They are much more accessible to Government leaders, staff, and policy makers due to the popular “Large Language Models” such as ChatGPT, Bing, Bard, and others.
Climate change is a complex and far-reaching threat that impacts far more than the environment.
While some days, it seems impossible to focus on any threats other than the vulnerabilities and accompanying hardship of the current COVID-19 pandemic, it is critical that senior Government leaders take a more strategic and long-term view of all potential threats over the next four to ten years. These are threats that we can only imagine, beyond today’s reach and capabilities, but nonetheless plausible from those who intend to do us harm or from potential threats that natural or man-made catastrophes can cause. Once senior leaders are aware of the threats, they must prioritize them and make choices about where to invest in preparation and prevention.
We tell ourselves, our coworkers, and our kids to at least try before saying “I can’t.” So, what happens when we are presented with an urgent challenge that, on paper, just seems impossible? The resources, the budget, and the schedule might just not add up.
Across the Federal government, agencies and programs have been tasked with building, training, and retaining the workforce needed to serve the American people. Public-sector leaders have been struggling with the right approach to this challenge, but we are now seeing more and more agencies turn to implementing private industry ’lean’ methods as a potential solution. Lean strategies aim to identify and improve an organization’s pain-points by following a set of principles and techniques focused on minimizing risk, optimizing cost and quality of processes, and engaging employees to deliver value-added benefits and improvements aligned to the organization’s mission and goals.
As threats evolve and technology reinvents how we perform work, the Government must continue to find solutions to increasingly complex and multifaceted problems. Thanks to the expanded availability and relevance of data, agencies are now equipped with more resources to make accurate fact-based decisions surrounding these complex issues. As agencies make increasing use of this data, they need to determine whether to implement a centralized or decentralized analytical structure.
How can the Department of Homeland Security (DHS) approach the magnitude of protecting ports and waters, anticipating risk of visitors to the U.S., or confirming that immigrants should become U.S. citizens because they pose no threat?
Scientists predict that the next full-margin rupture of the Cascadia subduction zone will produce the worst natural disaster in the history of North America. With many experts suggesting we are overdue for the “big one,” it is critical for the Department of Homeland Security (DHS) to incorporate effective risk management methods within their mission-critical, national, and high profile programs to improve their ability to prepare for, protect against, respond to, and recover from the potentially devastating effects of this imminent threat.
The United States confronts a wide array of threats. Terrorism. Transnational criminal organizations. Drug and weapons smuggling. Human trafficking. Cybercrime. And the ongoing challenge of illegal migration across U.S. borders.
Hurricane season has always been a big deal in Miami, but not so much in Philadelphia. This could change soon.
Advances in tooling, education, and job training provide organizations with the opportunity to advance their own cybersecurity programs. If not impenetrable, they are at least harder to breach and therefore a less attractive target than the next organization. It may be tempting to assume new tools solve problems and erase or lessen the need to understand management fundamentals as they apply to cybersecurity. Instead, it is vital to consider how effective cybersecurity depends on management fundamentals, especially on sound resource allocation.
