Access to Innovation
Access to Capital
Access to Talent
Access to Market
Access to Knowledge
Date Trend snippet:
23 June 2021
Relevance date:
2020
Type of Treath or Oppertunity
Domain of application
Source of threat
Victim
Trends in Security
Trends in Security Information
The HSD Trendmonitor is designed to provide access to relevant content on various subjects in the safety and security domain, to identify relevant developments and to connect knowledge and organisations. The safety and security domain encompasses a vast number of subjects. Four relevant taxonomies (type of threat or opportunity, victim, source of threat and domain of application) have been constructed in order to visualize all of these subjects. The taxonomies and related category descriptions have been carefully composed according to other taxonomies, European and international standards and our own expertise.
In order to identify safety and security related trends, relevant reports and HSD news articles are continuously scanned, analysed and classified by hand according to the four taxonomies. This results in a wide array of observations, which we call ‘Trend Snippets’. Multiple Trend Snippets combined can provide insights into safety and security trends. The size of the circles shows the relative weight of the topic, the filters can be used to further select the most relevant content for you. If you have an addition, question or remark, drop us a line at info@securitydelta.nl.
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Law enforcement's increased reliance on data with regards to sex trafficking
It seems likely that law enforcement's use of AI-driven analytics will only become greater. However, this presents certain limitations: data gaps and knowledge gaps. Data on victims, traffickers, buyers, and exploiters is often unreliable or partial. Furthermore, there are knowledge gaps of trafficking flows in large parts of the world and estimates mostly stem from non-methodical or incomplete data based on reported cases only. Moreover, reliance on data also presents a security risk.
More source info
Law Enforcement’s Increased Reliance on Data With the ongoing production of digital data and the benefits that a data-driven approach brings, it seems likely that law enforcement’s use of AI-driven analytics will only become greater. However, this presents certain limitations. This technology depends on large and accurate datasets; yet, there exist significant “data gaps”.65 Data on “the distribution of victims, traffickers, buyers, and exploiters” is often unreliable or partial.66 Furthermore, there are knowledge gaps of trafficking flows in large parts of the world, such as areas in Africa and the Middle East, and estimates mostly stem from non-methodical or incomplete data based on reported cases only.67 This paints an inaccurate picture of the “nature and scale” of human trafficking globally, thus hindering the global framework and responses envisaged by the anti-trafficking community.68 Moreover, since “Big data collection will not count those whom it cannot see”,69 reliance on data constrains law enforcement to only act on crimes that create online data at some point. Sex trafficking is perhaps one of the crimes that can best be combatted through data-driven efforts due to the online advertisements placed by traffickers.70 Still, these represent only a fraction of the entire sex trafficking chain; most of it remains invisible, creating little data and thus little information to act on. Moreover, reliance on data also presents a security risk as criminals may discover how to better hide their data and make it unusable; or they may alter data to feed disinformation to law enforcement.
