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我们被人工智能歧视了吗?
毛西
2018-06-09
?
毛西
剑桥大学二语教育硕士英语戏剧导演
今日导读
人工智能和算法都是近年来大热的科技词,
而人工智能算法偏见是一个更新的词汇。
p>
它代表
着每天在用各种互联网产品的时候,
你也许已经无意间被算法歧视了。
算法的本质是自动化
地作出决
策,
那人工智能做的决策就能绝对公平吗?微软最近开发了一个新工具来甄别人工
智能算法中的偏见,我们来一起看今天的新闻来了解一下。
带着问题听讲解
Q1:
人工智能算法偏见是怎样产生的?
Q2:
“
在群里潜水”
用英文怎么表达?
Q3:
文中教授对
侦查算法偏见的工具有怎样的建议?
新闻正文
Microsoft is creating an
oracle
for catching biased
AI algorithms
微软正在创建一个“先知”工具来捕捉
AI
算法偏见
Microsoft is building a
tool to automatically identify bias in a range of
different AI algorithms. It is
the
boldest
effor
t
yet
to automate
the
detection
of
unfairness
that
may
creep
into
machine
learning
—
and
it
could
help
businesses
make
use
of
AI
without
inadvertently
discriminati
ng
against certain people.
微软正在开发一个工具来自动识别一系列不同
AI
算法中的偏见。
这在自动侦查可
能渗入机
器学习的不平等方面,
是迄今为止最大胆的尝试,
p>
且它还能帮助企业在利用人工智能的同时
防止无意间歧视某些群体。
Algorithmic
bias
is
a
growing
concern
for
many
researchers
and
technology
experts.
As
algorithms
are
used
to
automate
important
decisions,
there
is
a
risk
that
bias
could
become
automated, deployed
at scale,
and more difficult for the
victims to spot
.
算法偏见是研究人员和技术专家日益担忧的问题,
由于算法将做重要决定的过程自动化
,
因
此存在着这样的风险:偏见也可能自动化和大规模地产生作
用,并且让受害者更难以察觉。
“
Things like
transparency
,
intelligibility,
and
explanation
are new
enough to the field that few
of us have
sufficient experience to know everything we should
look for and all the ways that bias
might
lurk
in
our models,” says Rich Caruna, a senior
researcher at Microsoft who is working on
the bias-detection
dashboard
.
从事偏见检测控制面板研究的微软高级研究员里奇·卡鲁纳说:
“透明度、
可理解性和解释
这类东西对这个领域来说是全新的,我们很少有人有足够的经验来明白我
们该寻找的东西,
以及偏见可能潜伏在我们模型中的所有方式。
”
Facebook
announced its own tool for detecting bias at its
annual developer conference
on May 2.
Its tool, called
Fairness Flow,
automatically
warns if an algorithm is making an unfair
judgement
about someone based on his or
her
race, gender, or age.
脸书在
5
月
2
日的
年度开发者大会上宣布了其自己的偏见检测工具。
这个工具命名为
“公
平畅行”
,如果算法根据一个人的种族、性别或年龄做出
了不公平的判断,它就会自动发出
警告。
Bin Yu, a professor at
UC Berkeley
, says the tools
from Facebook and Microsoft seem like
a
step
in
the
right
direction
,
but
may
not
be
enough.
She
suggests
that
big
companies
should
have
outside
experts
audit their
algorithms
in order to
prove they are not biased.
“
Someone else has
to
investigate Facebook's algorithms
—they
can't be a secret to everyone,” Yu
says.
加州大学伯克利分校教
授郁彬表示,
来自脸书和微软的工具似乎是朝着正确方向迈出的一步,
< br>但可能还不够。
她建议大公司应该让外部专家审核他们的算法,
< br>以证明它们没有偏见。
郁彬
说:
“其他人也得调查脸书的算法。它们不应对所有人都保密。
”
—————
文章来源
/ MIT
Technology Review
?
重点词汇
oracle
/???r?
kl/
n.
神谕者;专家
e.g.
He is regarded as the
oracle on health.
bias
/?ba??
s/
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