What tech companies know about your kids Veronica Barassi

Transcriber: Leslie Gauthier
Reviewer: Joanna Pietrulewicz

Every day, every week,

we agree to terms and conditions.

And when we do this,

we provide companies with the lawful right

to do whatever they want with our data

and with the data of our children.

Which makes us wonder:

how much data are we giving
away of children,

and what are its implications?

I’m an anthropologist,

and I’m also the mother
of two little girls.

And I started to become interested
in this question in 2015

when I suddenly realized
that there were vast –

almost unimaginable amounts of data traces

that are being produced
and collected about children.

So I launched a research project,

which is called Child Data Citizen,

and I aimed at filling in the blank.

Now you may think
that I’m here to blame you

for posting photos
of your children on social media,

but that’s not really the point.

The problem is way bigger
than so-called “sharenting.”

This is about systems, not individuals.

You and your habits are not to blame.

For the very first time in history,

we are tracking
the individual data of children

from long before they’re born –

sometimes from the moment of conception,

and then throughout their lives.

You see, when parents decide to conceive,

they go online to look
for “ways to get pregnant,”

or they download ovulation-tracking apps.

When they do get pregnant,

they post ultrasounds
of their babies on social media,

they download pregnancy apps

or they consult Dr. Google
for all sorts of things,

like, you know –

for “miscarriage risk when flying”

or “abdominal cramps in early pregnancy.”

I know because I’ve done it –

and many times.

And then, when the baby is born,
they track every nap,

every feed,

every life event
on different technologies.

And all of these technologies

transform the baby’s most intimate
behavioral and health data into profit

by sharing it with others.

So to give you an idea of how this works,

in 2019, the British Medical Journal
published research that showed

that out of 24 mobile health apps,

19 shared information with third parties.

And these third parties shared information
with 216 other organizations.

Of these 216 other fourth parties,

only three belonged to the health sector.

The other companies that had access
to that data were big tech companies

like Google, Facebook or Oracle,

they were digital advertising companies

and there was also
a consumer credit reporting agency.

So you get it right:

ad companies and credit agencies may
already have data points on little babies.

But mobile apps,
web searches and social media

are really just the tip of the iceberg,

because children are being tracked
by multiple technologies

in their everyday lives.

They’re tracked by home technologies
and virtual assistants in their homes.

They’re tracked by educational platforms

and educational technologies
in their schools.

They’re tracked by online records

and online portals
at their doctor’s office.

They’re tracked by their
internet-connected toys,

their online games

and many, many, many,
many other technologies.

So during my research,

a lot of parents came up to me
and they were like, “So what?

Why does it matter
if my children are being tracked?

We’ve got nothing to hide.”

Well, it matters.

It matters because today individuals
are not only being tracked,

they’re also being profiled
on the basis of their data traces.

Artificial intelligence and predictive
analytics are being used

to harness as much data as possible
of an individual life

from different sources:

family history, purchasing habits,
social media comments.

And then they bring this data together

to make data-driven decisions
about the individual.

And these technologies
are used everywhere.

Banks use them to decide loans.

Insurance uses them to decide premiums.

Recruiters and employers use them

to decide whether one
is a good fit for a job or not.

Also the police and courts use them

to determine whether one
is a potential criminal

or is likely to recommit a crime.

We have no knowledge or control

over the ways in which those who buy,
sell and process our data

are profiling us and our children.

But these profiles can come to impact
our rights in significant ways.

To give you an example,

in 2018 the “New York Times”
published the news

that the data that had been gathered

through online
college-planning services –

that are actually completed by millions
of high school kids across the US

who are looking for a college
program or a scholarship –

had been sold to educational data brokers.

Now, researchers at Fordham
who studied educational data brokers

revealed that these companies
profiled kids as young as two

on the basis of different categories:

ethnicity, religion, affluence,

social awkwardness

and many other random categories.

And then they sell these profiles
together with the name of the kid,

their home address and the contact details

to different companies,

including trade and career institutions,

student loans

and student credit card companies.

To push the boundaries,

the researchers at Fordham
asked an educational data broker

to provide them with a list
of 14-to-15-year-old girls

who were interested
in family planning services.

The data broker agreed
to provide them the list.

So imagine how intimate
and how intrusive that is for our kids.

But educational data brokers
are really just an example.

The truth is that our children are being
profiled in ways that we cannot control

but that can significantly impact
their chances in life.

So we need to ask ourselves:

can we trust these technologies
when it comes to profiling our children?

Can we?

My answer is no.

As an anthropologist,

I believe that artificial intelligence
and predictive analytics can be great

to predict the course of a disease

or to fight climate change.

But we need to abandon the belief

that these technologies
can objectively profile humans

and that we can rely on them
to make data-driven decisions

about individual lives.

Because they can’t profile humans.

Data traces are not
the mirror of who we are.

Humans think one thing
and say the opposite,

feel one way and act differently.

Algorithmic predictions
or our digital practices

cannot account for the unpredictability
and complexity of human experience.

But on top of that,

these technologies are always –

always –

in one way or another, biased.

You see, algorithms are by definition
sets of rules or steps

that have been designed to achieve
a specific result, OK?

But these sets of rules or steps
cannot be objective,

because they’ve been designed
by human beings

within a specific cultural context

and are shaped
by specific cultural values.

So when machines learn,

they learn from biased algorithms,

and they often learn
from biased databases as well.

At the moment, we’re seeing
the first examples of algorithmic bias.

And some of these examples
are frankly terrifying.

This year, the AI Now Institute
in New York published a report

that revealed that the AI technologies

that are being used
for predictive policing

have been trained on “dirty” data.

This is basically data
that had been gathered

during historical periods
of known racial bias

and nontransparent police practices.

Because these technologies
are being trained with dirty data,

they’re not objective,

and their outcomes are only
amplifying and perpetrating

police bias and error.

So I think we are faced
with a fundamental problem

in our society.

We are starting to trust technologies
when it comes to profiling human beings.

We know that in profiling humans,

these technologies
are always going to be biased

and are never really going to be accurate.

So what we need now
is actually political solution.

We need governments to recognize
that our data rights are our human rights.

(Applause and cheers)

Until this happens, we cannot hope
for a more just future.

I worry that my daughters
are going to be exposed

to all sorts of algorithmic
discrimination and error.

You see the difference
between me and my daughters

is that there’s no public record
out there of my childhood.

There’s certainly no database
of all the stupid things that I’ve done

and thought when I was a teenager.

(Laughter)

But for my daughters
this may be different.

The data that is being collected
from them today

may be used to judge them in the future

and can come to prevent
their hopes and dreams.

I think that’s it’s time.

It’s time that we all step up.

It’s time that we start working together

as individuals,

as organizations and as institutions,

and that we demand
greater data justice for us

and for our children

before it’s too late.

Thank you.

(Applause)

抄写员:Leslie Gauthier
审稿人:Joanna Pietrulewicz

每天、每周,

我们都同意条款和条件。

当我们这样做时,

我们为公司提供了合法

权利,可以对我们的数据和我们孩子的数据做任何他们想做的事情

这让我们想知道:

我们向儿童提供了多少数据

它的含义是什么?

我是一名人类学家,

也是两个小女孩的母亲。


在 2015 年开始对这个问题产生兴趣,

当时我突然
意识到正在生成和收集关于儿童的大量——

几乎无法想象的数据跟踪

所以我发起了一个

名为 Child Data Citizen 的研究项目

,我的目标是填补空白。

现在你可能
认为我在这里责备你

在社交媒体上发布你孩子的照片,

但这并不是重点。

这个问题
比所谓的“共享”要大得多。

这是关于系统,而不是个人。

你和你的习惯不应该受到责备。

历史上第一次,

我们

从孩子出生之前就开始跟踪他们的个人数据——

有时是从受孕的那一刻开始,

然后是他们的一生。

你看,当父母决定怀孕时,

他们会上网
寻找“怀孕的方法”,

或者下载排卵跟踪应用程序。

当她们怀孕时,

她们会
在社交媒体上发布婴儿的超声波照片,

下载怀孕应用程序,

或者咨询 Google 医生
的各种信息,

比如,你知道的

——“飞行时的流产风险”

或“腹部绞痛” 早孕。”

我知道,因为我已经这样做了——

而且很多次。

然后,当婴儿出生时,
他们使用不同的技术跟踪每一次午睡、

每一次喂食、

每一次生活
事件。

所有这些技术通过与他人分享,

将婴儿最亲密的
行为和健康数据转化为利润

因此,为了让您了解其工作原理

,2019 年,英国医学杂志
发表的研究表明

,在 24 个移动健康应用程序中,有

19 个与第三方共享信息。

这些第三方
与其他 216 个组织共享信息。

在这 216 个其他第四方中,

只有三个属于卫生部门。

其他可以
访问这些数据的公司

是谷歌、Facebook 或甲骨文等大型科技公司,

它们是数字广告公司

,还有
一家消费者信用报告机构。

所以你是对的:

广告公司和信用机构可能
已经有了小婴儿的数据点。

但移动应用程序、
网络搜索和社交

媒体实际上只是冰山一角,

因为儿童在日常生活中
被多种技术跟踪

他们在家中被家庭技术
和虚拟助手跟踪。

他们被学校的教育平台

和教育
技术跟踪。

他们被医生办公室的在线记录

和在线门户网站跟踪

他们
的联网玩具

、在线游戏

和许多、许多、许多、
许多其他技术都在跟踪他们。

所以在我的研究过程中

,很多家长来找我
,他们就像,“那又怎样?

我的孩子被跟踪

有什么关系?我们没有什么可隐瞒的。”

嗯,这很重要。

这很重要,因为
今天不仅要跟踪个人,

还可以
根据他们的数据跟踪对他们进行分析。

人工智能和预测
分析被用来从不同来源

尽可能多地
利用个人生活数据

家族史、购买习惯、
社交媒体评论。

然后他们将这些数据汇总在一起,

以针对个人做出数据驱动的决策

这些
技术无处不在。

银行使用它们来决定贷款。

保险使用它们来决定保费。

招聘人员和雇主使用它们

来决定一个人
是否适合某项工作。

警察和法院也使用它们

来确定一个人
是否是潜在的罪犯

或可能重新犯罪。

我们不了解或

控制那些购买、
出售和处理我们数据的

人对我们和我们的孩子进行分析的方式。

但这些资料可能会
以重大方式影响我们的权利。

举个例子

,2018 年《纽约时报》
发布的消息

称,这些数据是

通过在线
大学规划服务收集的——

这些数据实际上是由全美数百万正在寻找
大学的高中生完成

的。 大学
课程或奖学金——

已出售给教育数据经纪人。

现在,
研究教育数据经纪人的福特汉姆研究人员

透露,这些公司

根据不同的类别对年龄只有两岁的孩子进行了描述:

种族、宗教、富裕程度、

社交尴尬

和许多其他随机类别。

然后他们将这些资料
连同孩子的姓名

、家庭地址和联系方式一起出售

给不同的公司,

包括贸易和职业机构、

学生贷款

和学生信用卡公司。

为了突破界限,

福特汉姆的研究人员
要求教育数据经纪人

向他们提供一份对计划生育服务感兴趣
的 14 至 15 岁

女孩的名单

数据经纪人同意
向他们提供清单。

所以想象一下
这对我们的孩子来说是多么的亲密和侵扰。

但教育数据
经纪人实际上只是一个例子。

事实是,我们的孩子正在
以我们无法控制的方式被描绘出来,

但这会显着影响
他们的生活机会。

所以我们需要问自己:

在对我们的孩子进行剖析时,我们能相信这些技术吗?

我们可以吗?

我的回答是否定的。

作为一名人类学家,

我相信人工智能
和预测分析可以很好

地预测疾病的进程

或应对气候变化。

但我们需要放弃这样的信念

,即这些技术
可以客观地描述人类

,并且我们可以依靠它们
来做出

关于个人生活的数据驱动决策。

因为他们无法描述人类。

数据痕迹不是
我们是谁的镜子。

人类的想法是一样的
,说的却是相反的,

感觉是一样的,行为是不同的。

算法预测
或我们的数字实践

无法解释人类体验的不可预测性
和复杂性。

但最重要的是,

这些技术总是——

总是——

以一种或另一种方式存在偏见。

你看,根据定义,算法是为实现特定结果而设计
的规则或步骤集

,好吗?

但这些规则或步骤
不可能是客观的,

因为它们是
由人类

在特定文化背景下设计的,


受到特定文化价值观的影响。

因此,当机器学习时,

它们会从有偏见的算法中学习,

而且它们通常也会
从有偏见的数据库中学习。

目前,我们看到
了算法偏差的第一个例子。

其中一些
例子坦率地说是可怕的。

今年,纽约 AI Now
研究所发布的一份报告

显示,

用于预测性警务的 AI 技术

已经接受了“脏”数据的训练。

这基本上
是在

已知的种族偏见

和不透明的警察行为的历史时期收集的数据。

因为这些技术
是用脏数据训练的,

它们不客观

,它们的结果只会
放大和犯下

警察的偏见和错误。

所以我认为我们面临

着我们社会的一个根本问题。

在对人类进行剖析时,我们开始信任技术。

我们知道,在对人类进行分析时,

这些技术
总是会有偏见

,而且永远不会真正准确。

所以我们现在需要
的实际上是政治解决。

我们需要政府
承认我们的数据权利就是我们的人权。

(掌声和欢呼)

在这之前,我们不能
指望一个更公正的未来。

我担心我的女儿
们会

面临各种算法
歧视和错误。

你看
我和我女儿们的不同之处

在于我的童年没有公开记录。

我十几岁时做过和想过的所有愚蠢事情肯定没有数据库

(笑声)

但对于我的女儿们来说,
这可能会有所不同。 今天从他们

那里收集的数据

可能会在未来用来判断他们,

并可以阻止
他们的希望和梦想。

我认为是时候了。

是时候我们都站出来了。

现在是我们

作为个人

、组织和机构开始合作的时候了

,我们要求
为我们

和我们的孩子提供更大的数据正义

,以免为时已晚。

谢谢你。

(掌声)