摘录

Many of them conduct their studies in their spare time, using their skills as programmers, academics and statisticians to find out how the world is being reshaped by algorithms. 

All the big Internet services – including Google, Yahoo, Facebook, Microsoft and Apple – build up a personalised picture of our interests and use these to decide what adverts to show us. 

Even when we use our settings to tell Google which adverts we do and don’t want to be shown, it makes its own decisions about what to show us. 

These black boxes were influencing the information we saw and making decisions about us, while we were left unable to work out how these algorithms operate.

algorithms were making arbitrary decisions about us, often based on dubious assumptions and inaccurate data. 
In the future, society might demand that we link up our search, social media and health data, in order to get a complete picture of who we are and why we get ill.

We are designing algorithms to recognise faces, to understand language and to learn our music tastes. We are building personal assistants and chatbots that can help you fix your computer. We are predicting the outcome of elections and sporting events. We are finding the perfect match for single people or helping them swipe through all available alternatives. We are trying to provide the most relevant news for you on Facebook and Twitter. We are making sure that you find out about the best holiday breaks and cheap flights. Our aim is to use data and algorithms as a force for good. 

Algorithms are used everywhere to help us better understand the world. But do we really want to understand the world better if this means dissecting the things we love and losing our personal integrity? Are the algorithms we develop doing things society wants to do or just serving theinterest of a few geeks and the multinational companies they work for? And is there a risk, as we develop better and better artificial intelligence (AI), that the algorithms start to take over? That maths starts to make our decisions for us?
The real world has real problems and it is our job to come up with real solutions. There is so much more complexity to every problem than just making calculations. 

The social media giant was the best place to start investigating how algorithms classify us.

Are mathematicians making the world a better place? 
Over the past 50 years, sociologists and psychologists have used PCA to categorise our personalities, our societal values, our political views and our socio-economic status. We like to think of ourselves as multi-dimensional. We see ourselves as complicated individuals with many different sides to our characters. We tell ourselves that we are unique, that we are shaped by the millions of unique events that occur during our lifetimes. But PCA can reduce those millions of dimensions of complexity to a much smaller number of dimensions which can be used to put us in boxes or, to use a more appropriate visual metaphor, to represent us as a few different symbols. PCA tells me that I can, more or less, see my friends as clusters of circles, squares and crosses. 
Big Five components of personality: openness, conscientiousness, extroversion, agreeableness and neuroticism.
We are clicking our personalities into Facebook, hour after hour, day after day. Smileys, thumbs ups, ‘likes’, frowns and hearts. We are telling Facebook who we are and what we think. We are revealing ourselves to a social media site in a level of detail that we usually reserve for only our closest friends. And unlike our friends – who tend to forget the details and are forgiving in the conclusions they draw about us – Facebook is systematically collecting, processing and analysing our emotional state. It is rotating our personalities in hundreds of dimensions, so it can find the most cold, rational direction to view us from.

humans think about other people in just a small number of dimensions – age, race, gender and, if we know them a bit better, personality – while algorithms are already processing billions of data points andmaking classifications in hundreds of dimensions. When we don’t understand how Facebook classifies us, the joke is on us, not on the algorithms. We no longer have the capability to fully understand the output of the algorithms we have created.

If you regularly use Facebook, Instagram, Snapchat, Twitter or any other social media site, then you are outnumbered. You are allowing your personality to be placed as a point in hundreds of dimensions, your emotions to be enumerated and your future behaviour to be modelled and predicted. This is all done effectively and automatically, in a way that most of us can hardly comprehend.
世界不是非黑即白，可是大多数人没有办法做到多维度看待问题，我也一样。
In fact, it is often humans that see things in binary states of black and white. We make statements like ‘he is too stupid to understand’, ‘she is a typical Republican’ or ‘that person shares everything on Twitter’ almost reflexively, without thinking about the lack of subtlety of our judgements. It is humans who see the world in binary.
No matter how good a regression technique is, without data a model can’t work.
‘Can a computer ever understand us better than a human?’

The data scientist says it can.

One day, he says, we might fall in love with a computer that understands us better than our partner.
幽灵般的广告，你记不住的兴趣爱好，你的浏览器会帮你记得。
The other major source of ‘spooky’ adverts is retargeting: we simply forgot that we searched for a trip to the Algarve, but your web browser has remembered and fed this information to TUI, who are now offering you a room in their finest hotel. 

We are subjected to such vast quantities of advertising and spend such long periods of time staring at our phones and screens, that now and again adverts appear to have read our minds.
我的懒人心理被抓住了。
 ‘Basically, if you assume people are lazy then you can predict most of their behaviour.’

‘The more options people are shown on sites like these, the fewer options they look at.’ When we are shown too much information, our brains decide that the best thing to do is just ignore it.