{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","title":"[数字经济前沿]技术封建主义","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787300328508","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","id":"06dd97ec-cce5-45df-9acf-40e36f07dab3","uuid":"06dd97ec-cce5-45df-9acf-40e36f07dab3","title":"[数字经济前沿]技术封建主义","normalized_title":"数字经济前沿技术封建主义","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787300328508","isbns":["9787300328508"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":259,"navigation_url":"https://workshop.closeclaw.top/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3","title_url":"https://workshop.closeclaw.top/ai/title/%5B%E6%95%B0%E5%AD%97%E7%BB%8F%E6%B5%8E%E5%89%8D%E6%B2%BF%5D%E6%8A%80%E6%9C%AF%E5%B0%81%E5%BB%BA%E4%B8%BB%E4%B9%89","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/06dd97ec-cce5-45df-9acf-40e36f07dab3/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/06dd97ec-cce5-45df-9acf-40e36f07dab3","page_url":"https://workshop.closeclaw.top/api/ai/books/06dd97ec-cce5-45df-9acf-40e36f07dab3/page","search_url":"https://workshop.closeclaw.top/api/ai/books/06dd97ec-cce5-45df-9acf-40e36f07dab3/search"},"page":{"printed_page":102,"pdf_page":142,"physical_index":142,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"2800b738cf7ecc098660f6e6e9a09b606c7abcd7a92c8bda01fb4abf4551bfd9"},"chapter":"第二章","content":"困难之一在于定义适当的指标来衡量所需的效果，这是一种被专家称为总体评估标准（Overall EvaluationCriterion）的综合指标。例如，点击率的提升可能是一个误导性的利好信号，因为该提升实际上伴随着网站流量的下降。因此，有必要找到一种令人满意的方法来捕获这两个方面，并确保结果的可靠性，特别是排除软件机器人的活动产生的错误信号。然而，一旦这些困难得到充分考虑，实验就变得非常可靠。\n\n谷歌首席经济学家哈尔·瓦里安（HalVarian）认为，随机实验“是因果关系的黄金标准。如果你真的想了解因果关系，就必须做实验。如果你不断地做实验，你就能改进你的系统”①。从技术上讲，瓦里安错了。测试本身并不能解释因果关系，即它们只能告诉我们相关性在统计学上的稳健性，但并不能说明造成相关性的原因。例如，可以确定的是，改变广告的颜色会提高点击率。但为什么会存在这种联系？是什么文化、社会或生物机制在起作用？我们不得而知。唯一能证明的就是这种联系。不过，从工具主义的角度来看，这已经足够了。这些相关性为建立有利可图的系统提供了充分的基础。\n\n技术封建主义\n\n① Hal R. VARIAN, «Beyond Big Data» , loc. cit., p. 29.\n\n102","previous_page":101,"next_page":103}