科技公司对你的孩子了解多少 Veronica Barassi: What tech companies know about your kids

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演员: Veronica Barassi


台词
Every day, every week,
每一天, 每一个星期,
we agree to terms and conditions.
我们都会同意各种服务条款。
And when we do this,
每当我们这样做,
we provide companies with the lawful right
我们其实就赋予了公司法律上的权利,
to do whatever they want with our data
用我们的数据去做任何事,
and with the data of our children.
也包括我们孩子的数据。
Which makes us wonder:
这难免使我们感到困惑:
how much data are we giving away of children,
我们到底提供了多少 关于孩子的数据,
and what are its implications?
它们的用途又是什么?
I'm an anthropologist,
我是个人类学家,
and I'm also the mother of two little girls.
也是两个女孩的母亲。
And I started to become interested in this question in 2015
2015 年,我开始关注这个问题,
when I suddenly realized that there were vast --
当时我突然发现很多科技公司
almost unimaginable amounts of data traces
从孩子那里搜集到了
that are being produced and collected about children.
庞大到无法想象的数据信息。
So I launched a research project,
所以我启动了一个研究项目,
which is called Child Data Citizen,
叫“儿童数据市民”,
and I aimed at filling in the blank.
希望能够填补空缺的信息。
Now you may think that I'm here to blame you
现在,你们有可能以为我在责怪你们
for posting photos of your children on social media,
在社交网络上传了孩子的照片,
but that's not really the point.
但是这不是重点。
The problem is way bigger than so-called "sharenting."
实际问题比分享要严重得多。
This is about systems, not individuals.
这事关系统,而不是个人。
You and your habits are not to blame.
你的行为习惯并没有错。
For the very first time in history,
历史上首次,
we are tracking the individual data of children
我们开始追踪孩子的个人数据,
from long before they're born --
从他们出生之前——
sometimes from the moment of conception,
有时候是从受孕开始,
and then throughout their lives.
然后贯穿他们的一生。
You see, when parents decide to conceive,
通常,当家长决定要一个孩子,
they go online to look for "ways to get pregnant,"
他们会在网上搜索 “怎么怀孕”,
or they download ovulation-tracking apps.
或者下载排卵期追踪软件。
When they do get pregnant,
等到真的怀孕了,
they post ultrasounds of their babies on social media,
他们会在社交网络上 发布宝宝的超音波图像,
they download pregnancy apps
下载关于怀孕的软件,
or they consult Dr. Google for all sorts of things,
或者在谷歌上搜索相关信息。
like, you know --
比如,
for "miscarriage risk when flying"
“乘飞机时的流产风险”
or "abdominal cramps in early pregnancy."
或者“怀孕早期的腹痛”。
I know because I've done it --
我知道这些, 因为我也有过类似的经历,
and many times.
而且是很多次。
And then, when the baby is born, they track every nap,
等到宝宝出生后, 他们会用不同的技术
every feed,
记录每个午觉、
every life event on different technologies.
每次喂食和每个重要时刻。
And all of these technologies
所有这些技术
transform the baby's most intimate behavioral and health data into profit
都会通过把宝宝的资料分享给别人
by sharing it with others.
从而换取利润。
So to give you an idea of how this works,
先给各位举一个例子,
in 2019, the British Medical Journal published research that showed
在 2019 年, 英国医学杂志发布了一项研究:
that out of 24 mobile health apps,
在 24 个健康类的手机软件里,
19 shared information with third parties.
有 19 个把用户资料 分享给了第三方,
And these third parties shared information with 216 other organizations.
而这些第三方又分享给了 216 个其他的组织。
Of these 216 other fourth parties,
而这 216 个第四方机构,
only three belonged to the health sector.
只有三个属于健康类机构,
The other companies that had access to that data were big tech companies
其他的则是大型科技公司,
like Google, Facebook or Oracle,
比如谷歌,脸书或甲骨文,
they were digital advertising companies
都是数据广告类的公司,
and there was also a consumer credit reporting agency.
而且还有消费信贷的报告机构。
So you get it right:
所以你的猜测是对的:
ad companies and credit agencies may already have data points on little babies.
广告公司和信贷机构 已经有了宝宝们的数据。
But mobile apps, web searches and social media
但是手机软件、网站搜索和社交媒体
are really just the tip of the iceberg,
只是冰山一角,
because children are being tracked by multiple technologies
因为孩子们的日常生活
in their everyday lives.
已经被很多科技追踪了。
They're tracked by home technologies and virtual assistants in their homes.
他们被家里的设备和虚拟助手追踪,
They're tracked by educational platforms
他们被教育网站
and educational technologies in their schools.
和学校里的教育技术追踪。
They're tracked by online records
他们被诊所的
and online portals at their doctor's office.
网上记录和门户网站追踪。
They're tracked by their internet-connected toys,
他们也在被连网的玩具、
their online games
在线游戏
and many, many, many, many other technologies.
和很多很多其他的技术追踪。
So during my research,
在我的研究过程中,
a lot of parents came up to me and they were like, "So what?
很多家长问我,“那又怎么样?
Why does it matter if my children are being tracked?
就算我的孩子被追踪,那又怎么样?
We've got nothing to hide."
我们又没什么见不得人的秘密。”
Well, it matters.
但是,这真的很重要。
It matters because today individuals are not only being tracked,
因为现如今,个人信息不仅仅被追踪,
they're also being profiled on the basis of their data traces.
还会被用来创建网络个人档案。
Artificial intelligence and predictive analytics are being used
那些公司会用人工智能和预测分析
to harness as much data as possible of an individual life
从不同渠道搜集越来越多的
from different sources:
个人数据:
family history, purchasing habits, social media comments.
家庭历史、购物习惯和社交媒体评论,
And then they bring this data together
然后将这些信息结合在一起
to make data-driven decisions about the individual.
去做出关于你的决定。
And these technologies are used everywhere.
这些技术几乎无处不在。
Banks use them to decide loans.
银行利用这些信息 决定批准谁的贷款,
Insurance uses them to decide premiums.
保险公司用它们决定保费额度,
Recruiters and employers use them
招聘人员和雇主用它们
to decide whether one is a good fit for a job or not.
来决定你们到底适不适合某个工作。
Also the police and courts use them
警察和法庭也利用它们
to determine whether one is a potential criminal
去决定这个人是不是罪犯,
or is likely to recommit a crime.
或者有没有可能犯罪。
We have no knowledge or control
这些购买、售卖 和处理我们信息的人
over the ways in which those who buy, sell and process our data
究竟如何调查我们和我们的孩子,
are profiling us and our children.
我们对此一无所知, 也没有任何控制权。
But these profiles can come to impact our rights in significant ways.
但这些信息会 严重影响我们的权益。
To give you an example,
举个例子,
in 2018 the "New York Times" published the news
2018 年《纽约时报》 发布的一则新闻称,
that the data that had been gathered
由线上大学规划服务
through online college-planning services --
搜集的数据——
that are actually completed by millions of high school kids across the US
这些数据都来自 全美数百万正在寻找
who are looking for a college program or a scholarship --
大学项目或奖学金的高中生——
had been sold to educational data brokers.
已经被售卖给了教育数据经纪人。
Now, researchers at Fordham who studied educational data brokers
福特汉姆的研究人员在对一些 教育数据经纪人进行分析之后透露,
revealed that these companies profiled kids as young as two
这些公司根据以下类别 对不小于两岁的孩子
on the basis of different categories:
进行了分组:
ethnicity, religion, affluence,
种族、宗教、家庭富裕程度、
social awkwardness
社交恐惧症,
and many other random categories.
以及很多其他的随机分类。
And then they sell these profiles together with the name of the kid,
然后他们会将这些资料, 以及孩子的名字、
their home address and the contact details
地址和联系方式
to different companies,
出售给不同的公司,
including trade and career institutions,
包括贸易和职业发展机构,
student loans
学生贷款
and student credit card companies.
和学生信用卡公司。
To push the boundaries,
更夸张的是,
the researchers at Fordham asked an educational data broker
研究人员要求教育数据经纪人
to provide them with a list of 14-to-15-year-old girls
提供一份对家庭生育服务感兴趣,
who were interested in family planning services.
年龄在 14 至 15 岁的少女名单。
The data broker agreed to provide them the list.
数据经纪人同意了。
So imagine how intimate and how intrusive that is for our kids.
所以不难想象,我们孩子的隐私 得到了何等程度的侵犯。
But educational data brokers are really just an example.
但是教育数据经纪人的例子 只是冰山一角。
The truth is that our children are being profiled in ways that we cannot control
诚然,孩子们的信息 正以不可控的方式被人操纵着,
but that can significantly impact their chances in life.
但这会极大地影响他们以后的人生。
So we need to ask ourselves:
所以我们要扪心自问:
can we trust these technologies when it comes to profiling our children?
这些搜集孩子们信息的技术 还值得信任吗?
Can we?
值得吗?
My answer is no.
我的答案是否定的。
As an anthropologist,
作为一个人类学家,
I believe that artificial intelligence and predictive analytics can be great
我相信人工智能和 预测分析可以很好的
to predict the course of a disease
预测疾病的发展过程
or to fight climate change.
或者对抗气候变化。
But we need to abandon the belief
但是我们需要摒弃
that these technologies can objectively profile humans
这些技术可以客观的分析人类数据,
and that we can rely on them to make data-driven decisions
我们能够以数据为依据做出 关于个人生活的决定
about individual lives.
这一想法。
Because they can't profile humans.
因为它们做不到。
Data traces are not the mirror of who we are.
数据无法反映我们的真实情况。
Humans think one thing and say the opposite,
人类往往心口不一,
feel one way and act differently.
言行不一。
Algorithmic predictions or our digital practices
算法预测或者数据实践
cannot account for the unpredictability and complexity of human experience.
无法应对人类经验的 不可预测性和复杂性。
But on top of that,
但是在此之上,
these technologies are always --
这些科技总是——
always --
总是——
in one way or another, biased.
以这样或那样的方式存在偏见。
You see, algorithms are by definition sets of rules or steps
要知道,算法的定义是 被设计成实现一个具体结果的
that have been designed to achieve a specific result, OK?
很多套规则或步骤,对吧?
But these sets of rules or steps cannot be objective,
但是这些都不是客观的,
because they've been designed by human beings
因为它们都是 由带有特殊文化背景,
within a specific cultural context
被特殊文化价值所塑造的人类
and are shaped by specific cultural values.
设计出来的。
So when machines learn,
所以当机器在学习的时候,
they learn from biased algorithms,
它们利用的是带有偏见的算法,
and they often learn from biased databases as well.
以及往往同样带有偏见的数据。
At the moment, we're seeing the first examples of algorithmic bias.
如今,我们已经看到了 第一批算法偏见的例子,
And some of these examples are frankly terrifying.
其中有一些真的很可怕。
This year, the AI Now Institute in New York published a report
今年,位于纽约的 人工智能现在研究所(AI Now Institute)
that revealed that the AI technologies
发表的一份报告揭示了
that are being used for predictive policing
预测警务领域的人工智能技术
have been trained on "dirty" data.
是使用非常糟糕的数据进行训练的。
This is basically data that had been gathered
这些数据基本上都是
during historical periods of known racial bias
在历史上存在已知的种族偏见 和不透明的警察行为时期
and nontransparent police practices.
收集的数据。
Because these technologies are being trained with dirty data,
因为这些技术都是 用这类数据训练的,
they're not objective,
它们无法做到客观,
and their outcomes are only amplifying and perpetrating
结果只是放大和进一步深化
police bias and error.
警察的偏见和错误。
So I think we are faced with a fundamental problem
所以我觉得我们是在面对社会中的
in our society.
一个基本问题。
We are starting to trust technologies when it comes to profiling human beings.
我们正在放心大胆的 用各种技术对人类信息进行分析。
We know that in profiling humans,
我们知道在这方面,
these technologies are always going to be biased
这些技术总是有偏见的,
and are never really going to be accurate.
结果也永远不可能准确。
So what we need now is actually political solution.
所以我们现在需要 一个政治层面的解决方案。
We need governments to recognize that our data rights are our human rights.
我们需要让政府认识到, 我们的数据权利也是人权。
(Applause and cheers)
(鼓掌和欢声)
Until this happens, we cannot hope for a more just future.
在这样的转变发生之前, 我们无法期待一个更加公平的未来。
I worry that my daughters are going to be exposed
我担心我的女儿们会暴露在
to all sorts of algorithmic discrimination and error.
各种算法的歧视与错误判断中。
You see the difference between me and my daughters
我和我女儿的区别就在于,
is that there's no public record out there of my childhood.
我的童年并没有公开的记录,
There's certainly no database of all the stupid things that I've done
当然,我十几岁时做过的傻事
and thought when I was a teenager.
和那些荒唐的想法也没有被记录。
(Laughter)
(笑声)
But for my daughters this may be different.
但是我的女儿们就不同了。
The data that is being collected from them today
今天从她们那里搜集的数据
may be used to judge them in the future
在将来有可能被用来 评判她们的未来,
and can come to prevent their hopes and dreams.
并可能阻止她们的希望和梦想。
I think that's it's time.
我觉得是时候了,
It's time that we all step up.
是时候
It's time that we start working together
采取行动——
as individuals,
无论是个人,
as organizations and as institutions,
还是组织和机构——
and that we demand greater data justice for us
在一切还来得及之前就开展合作, 为我们和我们的孩子
and for our children
争取更大程度的
before it's too late.
数据公正。
Thank you.
谢谢大家!
(Applause)
(掌声)