Uploaded April 2025 | Updated September 2026, 8 hours ago
Client: Christopher Newfield, Independent Social Research Foundation
Alex Newsham, Hayden Young, Martin Guenther, Nigel Arun Jacob, Wei Heng Wong
Recent research has used machine learning methods to apply the language philosophy of Wittgenstein, in a way that can quantify the likelihood of any particular text being bulls**t. These results have extraordinarily exciting implications for political discussion, journalism, corporate press releases, even the content of Facebook or eX-Twitter. Your task is to create a BS-meter that uses these methods to produce an intuitive test device accessible to anyone, perhaps with an international authentication body that can apply
validated BS stamps to any text that deserves it.
Client: Christopher Newfield, Independent Social Research Foundation
Alex Newsham, Hayden Young, Martin Guenther, Nigel Arun Jacob, Wei Heng Wong
Recent research has used machine learning methods to apply the language philosophy of Wittgenstein, in a way that can quantify the likelihood of any particular text being bulls**t. These results have extraordinarily exciting implications for political discussion, journalism, corporate press releases, even the content of Facebook or eX-Twitter. Your task is to create a BS-meter that uses these methods to produce an intuitive test device accessible to anyone, perhaps with an international authentication body that can apply
validated BS stamps to any text that deserves it.
