Homeland Security is a complex mission, one that is both vast in scale and broad in scope, and this creates a large volume of data that can help provide insight into operations and strategic decisions. From disaster preparedness to counterterrorism, Federal employees rely heavily on an abundance of data to assess problems accurately and implement effective solutions.
Reacting to crimes after a legal infraction has occurred used to be the norm in law enforcement for decades. The growth of new and improving tools and technologies has pushed the needle back to ‘prevention’ in recent years, though, with more innovative approaches available to make committing crimes more difficult. A big part of this trend is a stronger reliance on big data as a cost-effective way to direct resources to disrupt criminal activity and networks.
For many years, Governments have viewed data as a byproduct of activity with little value. This sentiment, however, is changing rapidly. Today, organizations are trying to get every little advantage they can get over another to achieve their goals, and in doing so, have taken advantage of what data has to offer.
Human Trafficking is a global problem, the extent of which is not clearly understood and is difficult to measure. To tackle this issue, Arc Aspicio’s SILab hosted Innovative Ideas to Combat Human Trafficking – A Conversation in November 2019. The SILab is a knowledge hub that accelerates innovative and sustainable solutions through methods, tools, thought leadership, events, and other resources to help our people, partners, and clients solve complex problems. Nearly 30 professionals with experience combating human trafficking in law enforcement, victim services non-profits, academia, and the private sector and a survivor participated to offer strategic and actionable solutions for combating human trafficking during the event.
Engaging with a great artificial intelligence (AI) application is like watching a professional athlete in a game. The greatest of athletes make their efforts look so easy that we often forget we’re seeing the result of decades of hard work. Just like athletes, established corporations that have repeatedly collected the same data over years also make their AI solutions look effortless. But, in most cases, their AI is using data that has been carefully refined over decades of transactions and is enabling machine learning and statistical analysis.
Without insight into data, people make decisions based on instinct, speculation, or prevalent theory.
Asking people to interpret statistics and numbers is not the most efficient way to communicate information – after all, scientific studies show that humans are notoriously bad at interpreting them
In 2014, The World Bank conducted research on their website traffic to determine if anyone was reading what they published online. They found that one third of the documents were never downloaded. Forty percent had fewer than 100 downloads. Only 13 percent had been downloaded more than 250 times.
