解决浏览器兼容性问题面试题

by Aline Lerner

通过艾琳·勒纳(Aline Lerner)

如果不解决技术面试问题，就无法解决技术多样性问题。 这是数据。 (You can’t fix diversity in tech without fixing the technical interview. Here’s the data.)

In the last few months, several large players, including Google and Facebook, have released their latest — and ultimately disappointing — diversity numbers.

在过去的几个月中，包括Google和Facebook在内的几家大型公司发布了他们最新的(最终令人失望的)多样性数字。

Even with increased effort and resources poured into diversity hiring programs, Facebook’s headcount for women and people of color hasn’t really increased in the past 3 years.

即使投入了更多的精力并投入了大量资源用于多元化的招聘计划，在过去三年中，Facebook为女性和有色人种的员工人数并没有真正增加。

Google’s numbers have looked remarkably similar. And both players have yet to make significant impact, despite a number of initiatives.

Google的数字看起来非常相似。 尽管采取了许多举措，但这两个参与者仍未产生重大影响。

They’ve tried everything from a points system rewarding recruiters for bringing in diverse candidates, to increasing funding for tech education, to hiring more diverse candidates in key leadership positions.

他们已经尝试了各种方法，从积分系统奖励聘用各种不同候选人的招聘人员 ，到增加对技术教育的拨款，再到在关键领导职位上聘用更多不同候选人。

为什么在多元化招聘中获得的收益普遍如此低迷？ (Why have gains in diversity hiring been so lackluster across the board?)

Facebook justifies these disappointing numbers by citing the ubiquitous pipeline problem. Namely, that not enough people from underrepresented groups have access to the education and resources they need to be set up for success.

Facebook通过引用无处不在的管道问题来为这些令人失望的数字辩护。 即，代表人数不足的人群中，没有足够的人获得成功所需的教育和资源。

And Google’s take appears to be similar, judging from the portion of their diversity-themed, forward-looking investments that are focused on education.

从Google多元化主题，前瞻性投资中专注于教育的部分来看，Google的做法似乎与此相似。

Facebook and Google have, in short, blamed the pipeline. But that’s not all. A growing flurry of conversations have offered alternative “real reasons” that diversity hiring efforts haven’t worked.

简而言之，Facebook和Google将此归咎于管道。 但这还不是全部。 越来越多的对话提供了另类的“真正原因”，即多样性招聘工作没有奏效。

Here are some common ones:

这是一些常见的：

• diversity training isn’t sticky enough多样性培训还不够棘手
• work environments remain exclusionary, and thereby unappealing to diverse candidates工作环境仍然是排他性的，因此对各种候选人都没有吸引力
• performance reviews are improperly calibrated绩效评估未正确校准
• companies don’t accounting for how marginalized groups actually respond to diversity-themed messaging公司没有考虑边缘化群体实际上如何回应以多样性为主题的消息传递

I’m on the front lines of the struggle for diversity in tech. I place developers at tech companies like these through our platform, interviewing.io. And while I’m excited that more resources are being poured into education and inclusive workplaces, I have an alternate explanation for why diversity hiring initiatives aren’t working.

我站在技术多元化斗争的最前沿。 我通过我们的平台访问我将这样的技术公司的开发人员安置在了诸如此类的高科技公司中。 尽管我为能在教育和包容性工作场所投入更多的资源感到兴奋，但我还有一个替代性的解释，说明为什么多样性招聘计划无法奏效。

After drawing on data from thousands of technical interviews, it’s become clear that the technical interviewing process itself is nondeterministic and often arbitrary.

从数千次技术采访中获取数据后，很明显，技术采访过程本身是不确定的，通常是任意的。

Technical interviewing is a broken process for everyone, but that the flaws within the system hit underrepresented groups the hardest. Because these people haven’t had the chance to internalize the extent to which technical interviewing is a numbers game.

技术面试对每个人来说都是一个破碎的过程，但是系统内的缺陷严重打击了代表性不足的群体 。 因为这些人还没有机会内化技术面试是一场数字游戏的程度。

Getting a few interview invites here and there through increased diversity initiatives isn’t enough. It’s a beginning, but it’s not enough. It takes a lot of interviews to get used to the process and the format.

仅通过增加多样性举措在这里和那里获得一些采访邀请是不够的。 这是一个开始，但还不够。 要适应流程和格式，需要进行大量采访。

It takes a while to internalize the fact that the stuff you do in technical interviews isn’t actually the stuff you do at work every day.

需要一段时间才能内化一个事实，即您在技术面试中所做的实际上并不是您每天在工作中所做的事情。

And it takes people in your social circle — all going through the same experience, screwing up interviews here and there, and getting back on the horse — before you’ll realize that poor performance in one interview isn’t predictive of whether you’ll be a good developer.

这需要您的社交圈中的人们-经历相同的经历，在这里和那里搞砸面试，然后重新骑马-在您意识到一次面试中表现不佳并不能预测您是否会做一个好的开发者。

技术面试简史 (A brief history of technical interviewing)

It was surprisingly hard to find a definitive account of the history of technical interviewing. But I was able to piece together a narrative by scouring books like How Would You Move Mount Fuji, Programming Interviews Exposed, and the bounty of the internets. The story goes something like this.

很难找到有关技术面试历史的确切记录。 但是，通过搜寻诸如《您将如何移动富士山》 ，《 编程采访公开 》以及互联网的慷慨之类的书籍，我得以整理叙述。 故事是这样的。

Technical interviewing has its roots as far back as 1950s Palo Alto, at Shockley Semiconductor Laboratories. Shockley’s interviewing methodology came out of a need to separate the innovative, rapidly moving, Cold War-fueled tech space from hiring approaches taken in more traditionally established, skills-based assembly-line based industry.

技术面试的历史可以追溯到1950年代位于Shockley Semiconductor Laboratories的Palo Alto。 肖克利的采访方法是出于将创新，快速发展，冷战推动的技术空间与更传统地建立，以技能为基础的流水线行业所采用的招聘方式分开的需要。

So Shockley relied on questions that could gauge analytical ability, intellect, and potential quickly. One canonical question in this category has to do with coins:

因此，肖克利依靠可以快速评估分析能力，智力和潜力的问题。 此类别中的一个典型问题与硬币有关：

You have 8 identical-looking coins, except one is lighter than the rest. Figure out which one it is with just two weighings on a pan balance.

您有8个外观相同的硬币，但其中一个比其他硬币轻。 用秤盘上的两个称重就可以确定是哪一个。

The techniques that Shockley developed were adopted by Microsoft during the 90s, as the first dot-com boom spurred an explosion in tech hiring.

微软在90年代就采用了Shockley开发的技术，因为第一次互联网泡沫的兴起刺激了技术招聘的爆炸式增长。

Shockley had set up a high analytical and adaptability bar for candidates to jump over. Microsoft, too, needed to vet people quickly for potential.

肖克利设立了一个高度的分析和适应标准，供考生跳过。 微软也需要Swift审查人们的潜力。

As software engineering became increasingly complex over the course of the dot-com boom, it was no longer possible to have a few centralized “master programmers” manage the design, and then delegate away the minutiae. Even rank and file developers needed to be able to produce under a variety of rapidly evolving conditions, where mere mastery of a specific skill wasn’t enough.

随着网络泡沫时代的到来，软件工程变得越来越复杂，不再有几个集中的“主程序员”来管理设计，然后再去分配细节。 即使是普通文件开发人员也需要能够在各种快速发展的条件下进行生产，而仅仅掌握特定技能是不够的。

The puzzle format, in particular, was easy to standardize, because individual hiring managers didn’t have to come up with their own interview questions. And a company could quickly build up its own interchangeable question repository.

特别是拼图格式很容易标准化，因为个人招聘经理不必提出自己的面试问题。 公司可以快速建立自己的可互换问题库。

This mentality also applied to the interview process itself. Rather than tell individual teams to run their own processes and pipelines, it made much more sense to standardize things.

这种心态也适用于面试过程本身。 与其让单个团队运行自己的流程和管道，不如将其标准化。

This way, in addition to questions, you could effectively plug and play the interviewers themselves. Any interviewer within your org could be quickly trained up, then assigned to speak with any candidate, independent of prospective team.

这样，除了问题之外，您还可以有效地插入和播放采访者自己。 您组织内的任何面试官都可以得到快速培训，然后指派与任何候选人交谈，独立于预期团队。

Puzzle questions were a good solution for this era, for another reason all together: collaborative editing of documents didn’t become a thing until Google Docs’ launch in 2007.

拼图问题在这个时代是一个很好的解决方案，这又是另一个原因：在2007年Google Docs推出之前，文档的协同编辑才成为问题。

Without that capability, writing code in a phone interview was untenable. If you’ve ever tried to talk someone through how to code something up without at least a shared piece of paper in front of you, you know how painful this can be.

没有这种能力，在电话采访中编写代码就站不住脚。 如果您曾经试图与某人讨论如何编写代码，而又没有至少一张共享的纸在您面前，那么您就会知道这会是多么痛苦。

In the absence of being able to write code in front of someone, the puzzle question was a decent proxy.

在无法在某人面前编写代码的情况下，难题是一个不错的代理。

Technology marched on, and its evolution made it possible to move from the proxy of puzzles to more concrete, coding-based interview questions.

随着技术的发展，它的发展使人们可以从难题的替代品转向更具体的，基于编码的面试问题。

Around the same time, Google itself publicly overturned the efficacy of puzzle questions.

大约在同一时间， 谷歌本身公开推翻了难题问题的功效 。

那么，这使面试状态离开了哪里呢？ (So where does this leave the state of interviews?)

Technical interviews are gradually becoming more concrete. But they’re still very much a proxy for the day-to-day work that a software engineer actually does.

技术面试正逐渐变得更加具体。 但是，它们仍然是软件工程师实际所做的日常工作的代理。

The hope was that this proxy would be decent enough. But no one forgot what these proxies ultimately were — proxies.

希望这个代理人足够体面。 但是没有人忘记这些代理最终是什么—代理。

Relying on a proxy had a positive cost-benefit ratio in most cases, where problem solving was more important than specific technical skills, and the need for hiring at scale was paramount.

在大多数情况下，依靠代理人具有正的成本效益比，其中解决问题比特定的技术技能更为重要，并且大规模招聘的需求至关重要。

As it happens, elevating problem-solving ability and the need for a scalable process are both eminently reasonable motivations. But here’s the unfortunate part: the second reason — namely the need for scalability — doesn’t apply in most cases.

碰巧的是，提高解决问题的能力和对可伸缩过程的需求都是非常合理的动机。 但是，这是不幸的部分：第二个原因，即对可伸缩性的需求，在大多数情况下并不适用。

Very few companies are large enough to need plug and play interviewers. But coming up with interview questions and processes is really hard, so despite their differing needs, smaller companies often take their cues from the larger players.

很少有足够大的公司需要即插即用的面试官。 但是，提出面试问题和流程确实很困难，因此尽管需求不同，但较小的公司通常会从较大的参与者那里获取线索。

They do this without realizing that companies like Google are successful at hiring because the work they do attracts an assembly line of smart, capable people. They succeed in hiring despite their hiring process, and not because of it.

他们这样做时并未意识到像Google这样的公司在招聘方面很成功，因为他们所做的工作吸引了一批精明能干的人才。 他们尽管进行了招聘过程，但仍成功地进行了招聘，并不是因为这样。

The result is a de facto interviewing cargo cult. Smaller players blindly mimic the actions of their large counterparts, and blindly hope for the same results.

结果是事实上采访了货物崇拜者。 较小的玩家盲目模仿大型对手的行为，并盲目希望获得相同的结果。

And the worst part is that these results may not even be repeatable. For anyone. To show you what I mean, let’s dive into some interviewing data we’ve collected at interviewing.io.

最糟糕的是，这些结果甚至可能无法重复。 对任何人。 为了向你展示我的意思，让我们潜入我们在收集了一些面试的数据interviewing.io 。

技术面试对每个人都是坏的 (Technical interviewing is broken for everybody)

面试的结果是任意的 (Interview outcomes are kind of arbitrary)

Interviewing.io is a platform where people can practice technical interviewing anonymously and, in the process, find jobs. Interviewers and interviewees meet in a collaborative coding environment and jump right into a technical interview question.

Interviewing.io是一个平台，人们可以在该平台上匿名进行技术面试，并在此过程中找到工作。 采访者和受访者在协作编码环境中会面，直接跳入技术采访问题。

After each interview, both sides rate one another. Interviewers rate interviewees on their technical ability. And the same interviewee can do multiple interviews, each of which is with a different interviewer and/or different company. This opens the door for some interesting and somewhat controlled comparative analysis.

每次面谈后，双方互相评价。 采访者对受访者的技术能力进行评分。 同样的受访者可以进行多次采访，每个采访都与不同的采访者和/或不同的公司进行。 这为进行一些有趣的且比较受控的比较分析打开了大门。

We were curious to see how consistent the same interviewee’s performance was from interview to interview, so we dug into our data.

我们很想知道同一位受访者在每次采访中的表现如何一致，因此我们深入研究了数据。

After looking at thousands of interviews on the platform, we’ve discovered something alarming: interviewee performance from interview to interview varied quite a bit, even for people with a high average performance.

在平台上查看了数千次采访后，我们发现了一些令人震惊的事情： 受访者在每次采访之间的表现差异很大，即使对于平均表现较高的人也是如此 。

In the graph below, every represents the mean technical score for an individual interviewee who has done 2 or more interviews on interviewing.io. The y-axis is standard deviation of performance, so the higher up you go, the more volatile interview performance becomes.

在下面的图表中，每个数字代表一个单独的被访者的平均技术得分，该受访者在受访中进行了2次或更多次采访。 y轴是绩效的标准偏差，因此，越往上走，面试绩效就越不稳定。

As you can see, roughly 25% of interviewees are consistent in their performance, but the rest are all over the place. And over a third of people with a high mean (>=3) technical performance bombed at least one interview.

如您所见，大约有25％的受访者表现稳定，但是其余的人却遍布各地。 超过三分之一的具有较高平均水平(> = 3)的技术表现的人至少轰炸了一次采访。

Despite the noise, from the graph above, you can make some guesses about which people you’d want to interview. But keep in mind that each person above represents a mean.

尽管有杂音，但从上表中，您可以对要采访的人做出一些猜测。 但是请记住，以上每个人都代表一个平均值。

Let’s pretend that, instead, you had to make a decision based on just one data point. That’s where things get dicey. Looking at this data, it’s not hard to see why technical interviewing is often perceived as a game. And, unfortunately, it’s a game where people often can’t tell how they’re doing.

让我们假设，您必须仅基于一个数据点来做出决定。 那就是事情变得轻松的地方。 查看这些数据，不难理解为什么技术面试通常被视为一种游戏。 而且，不幸的是，这是一个人们常常不知道自己的表现的游戏。

没有人能说出他们的状况 (No one can tell how they’re doing)

I mentioned above that on interviewing.io, we collect post-interview feedback. In addition to asking interviewers how their candidates did, we also ask interviewees how they think they did. Comparing those numbers for each interview showed us something really surprising: people are terrible at gauging their own interview performance, and impostor syndrome is particularly prevalent.

我在上面提到，在viewing.io上，我们收集面试后的反馈。 除了询问面试官其候选人的表现外，我们还询问面试官他们认为自己的表现如何。 比较每次访问的这些数字，给我们带来了真正令人惊讶的发现：人们很难衡量自己的访问表现，冒名顶替综合症尤其普遍。

In fact, people underestimate their performance over twice as often as they overestimate it. Take a look at the graph below to see what I mean:

实际上， 人们低估了自己的表现两倍以上 。 看看下面的图，了解我的意思：

Note that, in our data, impostor syndrome knows no gender or pedigree — it hits engineers on our platform across the board, regardless of who they are or where they come from.

请注意，在我们的数据中， 冒名顶替综合症不分性别或谱系 -不论他们是谁或来自哪里，它都会对我们平台上的工程师造成重大影响 。

Now here’s the messed up part. During the feedback step that happens after each interview, we ask interviewees if they’d want to work with their interviewer.

现在是混乱的部分。 在每次面试后进行反馈的过程中，我们询问被访者是否愿意与他们的面试者一起工作。

As it turns out, there’s a very strong relationship between whether people think they did well and whether they would indeed want to work with the interviewer.

事实证明，人们是否认为自己做得好与是否确实想与面试官一起工作之间有着非常密切的关系。

When people think they did poorly — even if they actually didn’t — they may be a lot less likely to want to work with you.

当人们认为自己做得不好(即使实际上并没有做)时，他们可能不太愿意与您合作。

And, by extension, it means that in every interview cycle, some portion of interviewees are losing interest in joining your company, just because they didn’t think they did well, regardless of their actual performance.

而且，从广义上讲，这意味着在每个访谈周期中，都有一部分受访者对加入您的公司失去兴趣，只是因为他们认为自己的表现不佳，无论他们的实际表现如何。

As a result, companies lose candidates from all walks of life because of a fundamental flaw in the process.

结果，由于流程中的一个基本缺陷，公司失去了各行各业的候选人。

表现不佳打击边缘群体最困难 (Poor performances hit marginalized groups the hardest)

Though impostor syndrome appears to hit engineers from all walks of life, we’ve found that women get hit the hardest in the face of an actually poor performance.

尽管冒充者综合症似乎已受到各行各业工程师的打击，但我们发现，面对业绩不佳的女性，女性遭受的打击最大。

As we learned above, poor performances in technical interviewing happen to most people. Even people who are generally very strong.

如上所述， 大多数人在技术面试中表现不佳。 即使是通常非常强壮的人。

But when we looked at our data, we discovered that after a poor performance, women are 7 times more likely to stop practicing than men.

但是，当我们查看数据时，发现在表现不佳之后， 女性停止练习的可能性是男性的7倍 。

A bevy of research appears to support confidence-based attrition as a very real cause for women departing from STEM fields. But I suspect that the implications of the attrition we witnessed extend beyond women to underrepresented groups, across the board.

大量研究似乎支持基于信任的损耗是妇女脱离STEM领域的一个非常真实的原因 。 但是我怀疑，我们所看到的流失的影响范围从女性扩展到了代表性不足的人群。

真正的问题是什么 (What the real problem is)

At the end of the day, because technical interviewing is indeed a game, like all games, it takes practice to improve. But unless you’ve been socialized to expect and be prepared for the game-like aspect of the experience, it’s not something that you can necessarily intuit.

归根结底，因为技术面试确实是一个游戏，就像所有游戏一样，因此需要实践来改进。 但是，除非您已社交化，可以期望并为游戏中类似游戏的方面做好准备，否则您不一定会直觉。

And if you go into your interviews expecting them to be indicative of your aptitude at the job — which is, at the outset, not an unreasonable assumption — you will feel crushed the first time you crash and burn.

而且，如果您进行面试，希望他们能表明您对工作的天赋-从一开始，这并不是一个不合理的假设-第一次崩溃和燃烧时，您会感到沮丧。

But this process isn’t a reliable indicator of your aptitude. And on top of that, it’s hard to tell how you’re doing, even when you’re doing really well.

但是，此过程并不是您能力的可靠指标。 最重要的是，即使您做得非常好，也很难说出自己的表现。

These are issues that everyone who’s gone through the technical interviewing gauntlet has grappled with. But not everyone has the wherewithal or social support to realize that the process is imperfect and to stick with it.

这些都是经过技术面试的每个人都在努力解决的问题。 但是，并非每个人都有金钱或社会支持来意识到这一过程是不完美的，并坚持下去。

There are many possible reasons why you wouldn’t know a lot of developers who are like yourself. Maybe they’re not the same color as you, or the same gender. Maybe not many people at your school studied computer science, or you dropped out. Or one of many other reasons.

有很多可能的原因导致您不认识很多像您一样的开发人员。 也许它们与您的颜色不同或性别不同。 也许您学校里没有多少人学习计算机科学，或者您辍学了。 或许多其他原因之一。

Whatever the reason, you’ll have less support, less insider knowledge of the technical interview process, and less of a 10,000 foot view of the situation than more traditional candidates. Full stop.

无论出于何种原因，与传统候选人相比，您所获得的支持更少，对技术面试流程的内幕知识更少，并且对情况的了解不到10,000英尺。 句号

包容和教育还不够 (Inclusion and education isn’t enough)

To help remedy the lack of diversity in its headcount, Facebook has committed to three actionable steps on varying time frames.

为了帮助弥补员工多样性的不足， Facebook承诺在不同的时间范围内采取三个可行的步骤 。

The first step involves creating a more inclusive interview/work environment for existing candidates.

第一步涉及为现有候选人创建更具包容性的面试/工作环境。

The other two are focused on addressing the perceived pipeline problem in tech:

另外两个专注于解决技术中已知的管道问题：

• Short term: building a diverse slate of candidates and an inclusive working environment短期：建立多元化的候选人名单和包容的工作环境
• Medium term: supporting students with an interest in tech中期：为对技术感兴趣的学生提供支持
• Long term: creating opportunity and access长期：创造机会和机会

Indeed, I applaud efforts to promote inclusiveness and increase funding for education. This is especially important since it’s hard to see results of investing in education until several years later.

实际上，我赞扬为促进包容性和增加教育经费所作的努力。 这一点特别重要，因为直到几年后才看到对教育的投资成果。

But both of these approaches take a narrow view of the problem. Both continue to funnel candidates into a broken system.

但是，这两种方法都对问题进行了狭view的研究。 两者都继续将候选人集中到一个破碎的系统中。

Erica Baker really cuts to the heart of it in her blog post about Twitter hiring a head of D&I:

埃里卡·贝克(Erica Baker)在其关于Twitter聘请D＆I负责人的博客文章中确实切入其中：

What irks me the most about this is that no company, Twitter or otherwise, should have a VP of Diversity and Inclusion. When the VP of Engineering… is thinking about hiring goals for the year, they are not going to concern themselves with the goals of the VP of Diversity and Inclusion. They are going to say ‘hiring more engineers is my job, worrying about the diversity of who I hire is the job of the VP of Diversity and Inclusion.’ When the VP of Diversity and Inclusion says ‘your org is looking a little homogenous, do something about it,’ the VP of Engineering won’t prioritize that because the VP of Engineering doesn’t report to the VP of Diversity and Inclusion, so knows there usually isn’t shit the VP of Diversity and Inclusion can do if the Eng org doesn’t see some improvement in diversity.

最令我烦恼的是，任何公司，无论是Twitter还是其他公司，都不应该拥有多元化和包容性的VP。 当工程副总裁…正在考虑本年度的招聘目标时，他们不会担心多元化和包容性副总裁的目标。 他们会说：“雇用更多的工程师是我的工作，担心我雇用的人的多样性是多样性和包容性副总裁的工作。” 当多样性与包容性副总裁说“您的组织看起来有点同质化时，请执行此操作”，工程副总裁不会优先考虑这一点，因为工程副总裁不会向多样性与包容性副总裁汇报，因此我们知道，如果Eng组织看不到多样性方面的改善，通常多样性和包容性VP可以做到。

Indeed, this is sad, but true.

确实，这是可悲的，但却是事实。

When faced with a high-visibility conundrum like diversity hiring, a pragmatic and even reasonable reaction on any company’s part is to make a few high-profile hires, and throw money at the problem. Then, it looks like they’re doing something.

当面对像多样性招聘这样的高知名度难题时，任何公司的务实乃至合理的React都是招募几位高调的员工，然后把钱扔给这个问题。 然后，看起来他们在做某事。

It’s a lot easier to spin up a task force, department, or a new set of titles than it is to uproot the entire status quo.

成立一个工作队，部门或一组新的职务要比拔掉整个现状要容易得多。

As such, we end up with a newly minted, well-funded department. It then pumps resources into finding diverse candidates — who don’t understand the game-like nature of interviewing — and dumping them into a broken, nondeterministic machine.

因此，我们最终建立了一个新成立的，资金充裕的部门。 然后，它将投入大量资源来寻找多样化的候选人-他们不了解面试的游戏式本质-并将其丢弃到破碎的，不确定的机器中。

This process is made further worse by the fact that it favors confidence and persistence over bona fide ability. The candidates have no idea that the link between their success in navigating the interview process — and their subsequent on-the-job performance — is tenuous at best.

事实是，与真正的能力相比，它更倾向于自信和持久性，这一过程变得更加糟糕。 候选人不知道，他们在面试过程中的成功导航与随后的在职绩效之间的联系充其量是微不足道的。

如何解决问题 (How to fix things)

In the evolution of the technical interview, we saw a gradual reduction in the need for proxies. With the advent of tools for writing code together remotely, companies could phase out the abstract, largely arbitrary puzzle questions.

在技​​术面试的过程中，我们看到对代理的需求逐渐减少。 随着用于远程一起编写代码的工具的出现，公司可以逐步淘汰抽象的，基本上是任意的难题。

So what’s the next logical step? Technology has the power to free us from relying on proxies. At interviewing.io, we make it possible to move away from proxies by looking at each interviewee as a collection of data points that tell a story, rather than one arbitrary glimpse of something they did once.

那么下一个合理的步骤是什么？ 技术可以使我们摆脱对代理的依赖。 在访谈.io中，我们可以通过将每个受访者视为一个讲述故事的数据点的集合，而不是他们一次做过的任何事情的一瞥，来摆脱代理。

But that’s not enough either. Interviews themselves need to continue to evolve. The process itself needs to be repeatable. It needs to predict the candidate’s aptitude at the actual job to be done, and not merely be a system to be gamed.

但这还不够。 采访本身需要继续发展。 该过程本身必须是可重复的。 它需要预测候选人在实际要做的工作上的才能，而不仅是要被游戏的系统。

Change needs to come first from the larger organizations whose processes act as a template for everyone. They need to lead this charge. Only then can we succeed in welcoming to a truly diverse group of candidates.

变革需要首先来自大型组织，这些组织的流程是每个人的模板。 他们需要领导这项指控。 只有这样，我们才能成功迎接真正多元化的候选人。

Want to become awesome at technical interviews and land your next job in the process? Join interviewing.io!

想要在技术面试中变得很棒，并在此过程中找到下一份工作吗？ 参加访谈吧！

翻译自: https://www.freecodecamp.org/news/you-cant-fix-diversity-in-tech-without-fixing-the-technical-interview-here-s-the-data-93130f977da2/

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