Ted Talk -- 大数据中所忽略的人们视角

The human insights missing from big data

Ted Talk link

Ted Talk

在统计学当中也有关于对数据的分析,而大数据,也是这么回事。收到的数据虽然是真实的,而且有一定量可以来分析绝大部分人的偏好还有行为,同时可以顾及到所有人的真实情况。

然而,大数据并不能代表一切,因为大数据是死的,而且来自于历史,来自于过去。当然,它确实可以有之前说的优点。但是呢,大数据呢,并不能全面代表人们的行为。因为人的行为是变化的,而且也是无常的,并不是一成不变的,更甚者,人会学习新东西,也会接受新东西。就好比,以前没有电灯,没有电话,没有电视这些东西,但是经过时间的演变,人们逐渐适应同时一并适用,并且推广到了全世界,其他的东西亦如此。所以,大数据里头并没有显示人们的心情,人们的追求,还有人们的意向。就好比,大数据并不能遇见到人们对新产品的需求,人们对新东西的接受程度还有人们的生活变数。如果没有进入具体的环境中,单单靠大数据并不能模拟出一个真实的世界来的,所以和真实程度的偏差就会大大增加。所以大数据并不是全部,而且一个辅助工具,我们可以通过大数据得到的结果来接近真实结果。


make the big and right important decision for consulting the oracle of future

  • Big data: solve the question by making prediction
  • Object: big data doesn't help for right decision because investment big data but low return with 73% of data are non-profitable
  • the way for using big data: quantifying in the contained system
  • Quantification Bias (quant model): the unconscious belief of valuing the measurable over the immeasurable <-- cannot see something outside of it because the environment is complex and unpredictable, especially the human behavior, which can be merged with new factor and change by learning something
  • result: relying on big data alone increases the chances we'll miss something while giving us the illusion we know everything
  • quantifying is addictive
  • the greater risk to be blind in the unknown and consciously thinking that we know
  • using thick data: small data size but include incredible data meaning to complement with the quant model
  • Integrate big data + think data == form a complete picture
  • asking question after collecting data for using data: what this happening?
  • Goal: great data insight the algorithm to analyze the question

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