在 Hacker News 上看到的消息，是關於「使用類神經網路產生新聞」(也就是透過程式大量產生假新聞)，這次的結果包括了「產生」與「偵測」兩個面向：「Grover – A State-of-the-Art Defense Against Neural Fake News (allenai.org)」。
實驗的網站在「Grover - A State-of-the-Art Defense against Neural Fake News」這邊，另外也有論文「Defending Against Neural Fake News」可以讀。
幾個月前，OpenAI 利用類神經網路，研發出「自動寫新聞」的程式，當時他們宣稱因為效果太好，決定不完整公開成果：「Better Language Models and Their Implications」，中文的報導可以參考 iThome 這篇：「AI文字產生技術引發假新聞爭議，OpenAI決定只公開部份技術成果」。
而現在 The Allen Institute for Artificial Intelligence 則是成功重製了 OpenAI 的成果，取名叫 Grover，發現訓練出來的模型除了可以拿來寫新聞外，也可以拿來偵測文章是不是機器產生的，而且就他們自己測試，辨識成功率還蠻高的：
To study and detect neural fake news, we built a model named Grover. Our study presents a surprising result: the best way to detect neural fake news is to use a model that is also a generator. The generator is most familiar with its own habits, quirks, and traits, as well as those from similar AI models, especially those trained on similar data, i.e. publicly available news. Our model, Grover, is a generator that can easily spot its own generated fake news articles, as well as those generated by other AIs. In a challenging setting with limited access to neural fake news articles, Grover obtains over 92% accuracy at telling apart human-written from machine-written news. Please read our publication for more information.
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