Think Before Tag Someone in a Facebook Photo, It Can Cause Some Jail Time
The Facebook is a part of our life, many of us hating it and many like it. If you use the platform in a right way it can be useful; you can talk, chat, send files and photos to your friend or family members.
The Facebook is a part of our life, many of us hating it and many like it. If you use the platform in a right way it can be useful; you can talk, chat, send files and photos to your friend or family members. You can find your old friend with who you lost contact, can see the significant events in your friends life and never forget their birthdays. But if you don’t use it right, Facebook can cause many problems for you also.
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Many of the divorce cases, the Facebook platform used by the one of the couples to prove that their life companion is not loyal anymore. And this last case; Maria G., who not allowed to communicate with her sister-in-law Maribel C. as ordered by the court. But, Maria didn’t listen to the court and keep publishing posts in which, she kept tagging her sister-in-law and calling her stupid in the posts. Also, Maria G. added these words, according to the law journal: “You and your family are sad…You guys have to come stronger than that!! I’m way over you guys, but I guess not in yo agenda.”
As you know if you tagged in a post or on a photo, Facebook sends you a notification. And now Maria G. being charged with second-degree criminal contempt, this can lead to a year in prison. Maria’s attorney says; protection order didn’t exclude communication via Facebook. But still this is kind of harassment for us. Well, this kind of cases teaches us the be more careful about what we do or what we say in social media. Our actions can be used against us later.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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