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One of the many tech giant-driven issues that the docudrama highlights is the danger of fake news. As we navigate through the pandemic, the age of 'disinformation' has reared its very and hazardous head unlike ever before. Different foods, botanicals, recreational drugs, and others took centre-stage as the cure du jour, when the blunt truth is that we simply don't have a cure, and that the reports are a load of a-word-I-probably-shouldn't-use. Having said that, the financial damage of fake news can stem beyond simply less revenue and expensive reparation. In 2017, fake news began spreading that the CEO of Ethereum, Vitalik Buterin, had died in a car accident. Vitalik had to publicly confirm that he was still alive, but by that time, the overall market value of Ethereum had fallen by around $4 billion.
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One of the many tech giant-driven issues that the docudrama highlights is the danger of fake news. As we navigate through the pandemic, the age of 'disinformation' has reared its very and hazardous head unlike ever before. Different foods, botanicals, recreational drugs, and others took centre-stage as the cure du jour, when the blunt truth is that we simply don't have a cure, and that the reports are a load of a-word-I-probably-shouldn't-use. Having said that, the financial damage of fake news can stem beyond simply less revenue and expensive reparation. In 2017, fake news began spreading that the CEO of Ethereum, Vitalik Buterin, had died in a car accident. Vitalik had to publicly confirm that he was still alive, but by that time, the overall market value of Ethereum had fallen by around $4 billion.
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For me, it would be great if everyone would stop worrying about whether a review is fake or not. From the user experience point of view, I'd rather have reviews tagged as useful or not, personalized to my past history of review tagging. In machine learning, this is a somewhat easier problem to solve. Users tag reviews as useful or not and post their own reviews. ML algorithm takes this data and can then tag other reviews with a score, 0-100% useful to me, the user. This is easier than spotting fake reviews; we may have to guess whether a review is fake, but we know whether I tagged a review as useful, so the data going into the algorithm is certain. Other users' useful tags would not be used, or weighted far less heavily, than my useful tags, so gaming the system would be harder.
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