以下是知名美国软件测试顾问Michael Bolton关于“机器学习”的沉思：
[引用] 无论机器如何“学习”任何有关人类的信息，它只能从供给它的字符串中学习。 严谨的来说，“无监督学习”并非真正的自主学习。如果我们具批判性思考，我们可能会注意到无监督学习其实是受到高度督促的。我们还应该注意到另一件事：机械无法真正理解人类。它只是产生可供机器解读、代表人类以及人类行为的电子数据，而不代表人类深刻、真实的意图、思想、情感或社会关系。
与其简单将AI视为以数据来检视现象和事物的科技，不如将AI视为人类的镜子。人工智能和机器学习可以帮助我们观照自己、了解自己。但是，如果人类仅通过AI来端详数据，我们将看不清自己。故此，我们必须观测AI，并从中找到我们的自我反省。 [/引用]
[Quote] Some musings on critical thinking about "machine learning": whatever the machinery "learns" about people, it learns only from strings of bits that have been supplied to it. "Unsupervised learning" isn’t learning, and if we think more critically, we might notice that it's highly supervised.
Another thing we ought to notice: the machinery doesn’t learn about people. It produces data about strings of bits that represent people and their machine-readable behaviours — not their deep, true, real intentions, thoughts, emotions, or social relationships.
[...]
Another crucial element of critical thinking is to focus on what's missing. Machine learning is literally limited to bits of ourselves. Walk around in your neighbourhood. Joke with the woman at the samosa shop. See the dad with the stroller. Smile back at the cyclist. Reflect on the weather and climate change. None of that gets into a training data set.
Instead of thinking of AI simply as a lens on data, it is crucial to think of it also as a mirror. AI and machine learning can help us to see what we're like. But we don’t see ourselves if we only look at data through AI. We must look at AI, and look for our own reflections in it. [/Quote]
资料出处/Reference Source：
https://www.linkedin.com/pulse/what-do-machines-really-learn-michael-bolton
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