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What Next: TBD | Tech, power, and the future

Can an Algorithm Spot a Shooter?

Jun 3, 2022
Arijit Sen, an expert in threat detection online, discusses the limitations of algorithmic software in identifying potential threats on social media. The podcast explores the challenges of monitoring linguistic variations and biases in text identification, highlighting concerns about privacy invasion and the potential misuse of social media monitoring services in schools.
23:43

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Social media monitoring software often fails to detect true threats due to limitations in algorithms and struggles with slang and linguistic variations, leading to potential bias.
  • The use of social media monitoring software in schools raises privacy concerns, as many students and parents are not informed or given the choice to opt out, and there are worries about monitoring protests and activism.

Deep dives

Effectiveness of social media monitoring software in preventing school shootings

The podcast episode explores the effectiveness of social media monitoring software in preventing school shootings. The reporter, Ari Sen, discovered that many school districts in Texas were using a service called Social Sentinel, which claims to scan social media for potential threats. However, most of the school districts did not find the service useful and canceled it after a year. Examples of false alerts included tweets with song lyrics, obvious jokes, and hyperbole. There are concerns about the algorithms used by these services, as they often struggle with slang and linguistic variations, leading to potential bias. Additionally, these services may be used for purposes beyond preventing school shootings, such as monitoring protests and activism. The podcast highlights the need for transparency and an open dialogue about the effectiveness and privacy implications of these services.

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