Customs & Border Management

Customs in the cognitive era (part 1)

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Norbert Kouwenhoven and I are writing an article about how cognitive computing can transform the way customs agencies supervise international merchandise trade. Over the next couple of months I plan to post a series of blog posts about customs in the cognitive era as we finalise the article. In part 1, we look at cognitive computing.

Data analytics – for example, automated selectivity rules – has become an increasingly important tool for customs agencies. However, conventional data analytics has some critical limitations. It can only look for pre-defined patterns and rules, and cannot make use of unstructured data, which comes in the form of emails, social media, blogs, documents, images and videos. Cognitive computing allows customs agencies to extract insights from both structured and unstructured data, discover new patterns and rules, capture the experience of top performers, and improve the quality and consistency of decision-making.

The dawn of the ‘cognitive’ era

On 11 May 1997, the Deep Blue computer system beat grandmaster and world chess champion, Garri Kasparov, after a six-game chess match. This represented a major milestone in the evolution of computer systems. The Deep Blue project inspired a more recent grand challenge: Building a computer that could beat the champions at a more complicated game, the American game show Jeopardy!

Over three nights in February 2011, this computer system – named Watson – took on two of the all-time most successful human players of the game, and beat them in front of millions of television viewers. The technology in Watson was a substantial step forward from Deep Blue. By understanding and processing a massive supply of unstructured data, Watson demonstrated that a whole new generation of human-machine interaction is possible. Watson had ushered in a new era of computing: The ‘cognitive’ era. Since then many large technology firms, such as Google, Facebook and Apple, have all developed cognitive computing technologies.

Cognitive systems have three characteristics that distinguish them from programmable era systems. They:

  1. Understand unstructured data, through sensing and interaction;
  2. Reason by generating hypotheses, considering arguments, and making recommendations;
  3. Learn from training by experts, from every interaction, and from continually ingesting data.

It is estimated that 80% of all data generated today is unstructured. The dawn of the cognitive era means that machines can, for the first time, create insights from this enormous volume of data. Unstructured data is data which is not organized in a pre-defined manner; it is typically text heavy and often consists of documents, reports and articles, but can also include images, social media and videos. This previously unintelligible pile of documents is now a rich source of data for cognitive systems which can process it faster and more accurately than humans ever could. Processing the entire content of Wikipedia is a piece of cake for a computer!

In part 2, we will look at the early commercial applications of cognitive technology and explore how it can improve compliance and facilitation by enabling customs officers to make better decisions. In the meantime, visit IBM Government’s website to learn more about customs in the cognitive era.

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