TED演讲:为什么智能统计数据是打击犯罪的关键(8)
What judges see if they run the risk assessment tool is this — it’s a dashboard.
如果他们使用了这个风险评估工具，你就会看到这个–一个评分板。
At the top, you see the New Criminal Activity Score, six of course being the highest,
在顶部的，是新的刑事犯罪活动评分，六当然是最高分，
and then in the middle you see, “Elevated risk of violence.”
然后在中间你可以看到“增长的暴力风险”。
What that says is that this person is someone who has an elevated risk of violence that the judge should look twice at.
说的是，这个人进行暴力行为的概率有所升高，这是法官应该注意的重点。
And then, towards the bottom, you see the Failure to Appear Score,
然后在底部，你看到的是未能出庭的分数，
which again is the likelihood that someone will come back to court.
这也是判断此人会回到法庭的可能性。
Now I want to say something really important.
现在我想说些非常重要的事。
It’s not that I think we should be eliminating the judge’s instinct and experience from this process. I don’t.
我不认为在整个过程中应该排除法官的直觉和经验。我不这样想。
I actually believe the problem that we see and the reason that we have these incredible system errors,
事实上，我相信我们看到的问题以及系统内出现令人难以置信的错误的原因，
where we’re incarcerating low-level, nonviolent people and we’re releasing high-risk, dangerous people,
也就是我们关押低级、非暴力的人，我们释放高风险的、危险的人的原因，
is that we don’t have an objective measure of risk.
是因为我们没有客观的衡量风险。
But what I believe should happen is that we should take that data-driven risk assessment
但我相信我们应该将这种数据驱动的风险评估，
and combine that with the judge’s instinct and experience to lead us to better decision making.
与法官的直觉和经验相结合，会使我们做出更好的决策。
The tool went statewide in Kentucky on July 1, and we’re about to go up in a number of other U.S. jurisdictions.
该评估工具于7月1日在肯塔基州全面推行，我们还要在许多其他美国司法管辖区内推行。
Our goal, quite simply, is that every single judge in the United States will use a data-driven risk tool within the next five years.
我们的目标很简单，就是让全美的每一个法官都能使用这种数据驱动的风险评估工具在未来五年内实现。
We’re now working on risk tools for prosecutors and for police officers as well,
我们现在正在研究风险工具以便检察官和警官使用，
to try to take a system that runs today in America the same way it did 50 years ago,
想要把过去50年不变的系统继续运行下去，
based on instinct and experience, and make it into one that runs on data and analytics.
基于直觉和经验，并把它变成一种运用数据分析的系统。
Now, the great news about all this, and we have a ton of work left to do,
现在，我们仍有大量的工作要做，
and we have a lot of culture to change, but the great news about all of it is that we know it works.
仍要改变相关文化，但关于这所有一切有个好消息，那就是我们知道这很管用。
It’s why Google is Google, and it’s why all these baseball teams use moneyball to win games.
这就是为什么数据成就了谷歌，为什么棒球队会因使用点球成金的方法而打赢比赛。
The great news for us as well is that it’s the way that we can transform the American criminal justice system.
还有一个好消息是，我们可以用这种方法转变美国的刑事司法系统。
It’s how we can make our streets safer, we can reduce our prison costs,
它可以使我们的周边环境更安全，可以减少我们的监狱花销，
and we can make our system much fairer and more just.
可以让我们的司法系统更公平，更公正。
Some people call it data science. I call it moneyballing criminal justice. Thank you.
有人说这是数据科学。我称之为点球成金式刑事司法。谢谢。
当安妮米尔格拉姆2007年出任新泽西州的司法部长之时，很快便发现了某些惊人的事实：她的团队不仅对蹲监狱的人不甚了解，而且也无法确定他们所作的判决是否真正加强了公众安全。因此，她展开了一次鼓舞人心的探索，即将数据分析与统计分析应用到美国刑事司法体系当中。