How machine learning improvements are helping to fight human trafficking

Human trafficking is one of the most serious issues facing our society today, with an estimated 25 million victims around the world and an estimated annual income of $150 billion. Unfortunately, the agencies and non-governmental organizations (NGOs) that are tasked with putting an end to trafficking are typically small and underequipped for the task. It often feels like a fight between David and Goliath, with the odds most definitely in favor of the traffickers.

Fortunately, technology is here to help and there is undoubtedly a silver lining in the battle against human trafficking: ensuring that the inequality of resources be that between individuals or NGOs, technology can help to reduce the gap. In particular, machine learning (ML) algorithms have made an impact in recent years.

Machine learning algorithms use artificial intelligence to analyze data, identify patterns and anomalies, and predict outcomes. This technology can be used to monitor the activity of traffickers and identify irregularities that could suggest trafficking activity. It can also be used to identify victims of trafficking and provide evidence that could be used to convict the traffickers. This means that machine learning algorithms are an extremely valuable tool in the fight against traffickers.

Unfortunately, technology can also be used by traffickers to enable their activities, so it is important to make sure that ML algorithms are implemented in a way that protect victims and survivors of trafficking. With the help of ML algorithms, agencies and NGOs tasked with the fight against human trafficking can level the playing field, providing greater safety and protection for victims.






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