夜雨聆风A few years ago, Ken Schumacher was working for a technology company.
几年前，肯·舒马赫在一家科技公司工作。
Part of his job involved assessing potential hires: hopping on a Zoom call, giving an applicant an engineering test (kind of like a crossword puzzle with code instead of words), and going on “mute for an hour” as the applicant struggled through it.
他工作的一部分是评估潜在的求职者：参加Zoom电话会议，给求职者进行一项工程测试（有点像用代码而不是文字的填字游戏），然后在求职者努力完成测试时“静音一小时”。
Except many of the candidates weren’t struggling.
然而，很多求职者并没有陷入困境。
The firm’s exercises were getting posted on sites such as Glassdoor.
该公司的测试题被发布在了诸如Glassdoor这样的网站上。
“All these savvy 23—year—olds would, of course, practice the problem three times, come to me, and crush it,” Schumacher told me.
舒马赫告诉我：“这些聪明的23岁年轻人当然会把题目练习三遍，然后来找我，并且轻松应对。”
“Now the bigger problem is everyone’s using AI to write their resume.”
“现在更大的问题是，每个人都在用人工智能来写简历。”
They’re also using AI—powered chatbots and teleprompters to help them get to the next round.
他们还使用人工智能驱动的聊天机器人和提词器来帮助自己进入下一轮面试。
It’s become “really, really hard for anyone to figure out who’s real and who’s fake,” Schumacher said.
舒马赫说：“现在任何人都很难分辨出谁是真材实料，谁是弄虚作假。”
(This turned out to be its own market opportunity—he now runs a start—up using AI to detect AI cheating by job candidates.)
(事实证明，这本身就是一个市场机会——他现在经营着一家初创公司，使用人工智能来检测求职者是否利用人工智能作弊。)
The problem might be particularly acute in software engineering.
这个问题在软件工程领域可能尤为严重。
But the same dystopian phenomenon is contorting the whole labor market.
但同样的反乌托邦现象正在扭曲整个劳动力市场。
AI has Tinderized hiring.
人工智能让招聘变得像使用交友软件Tinder一样。
Workers are applying to hundreds of positions and never hearing back; companies are receiving thousands of resumes and struggling to respond.
求职者申请了数百个职位却得不到回音；公司收到数千份简历，却难以回复。
More than that, AI has Amazoned hiring.
不仅如此，人工智能让招聘变得像亚马逊购物一样。
It has scrubbed the uniqueness out of applications, flooded the market with same—same—seeming offerings, increased the number of frauds, and replaced personal discretion with brute algorithmic assessment.
它消除了申请的独特性，让市场充斥着千篇一律的求职申请，增加了欺诈行为的数量，并用粗暴的算法评估取代了人为的判断。
People had once hoped that Silicon Valley might not only smooth out the logistics of getting a job but also make the process fairer.
人们曾经希望，硅谷不仅能理顺找工作的流程，还能让这个过程更加公平。
Unbiased tools would replace alma—mater networks.
公正的工具将取代校友关系网。
Digital portals would accept applications from anyone, anywhere.
数字门户将接受来自任何地方任何人的申请。
Workers would get free access to templates, practice exams, and advice.
求职者可以免费使用模板、参加模拟考试并获得建议。
“Technology in general tends to improve the efficiency of job matching,” Mitchell Hoffman, a labor economist at UC Santa Barbara, told me.
加州大学圣巴巴拉分校的劳动经济学家米切尔·霍夫曼告诉我：“总体而言，科技往往会提高就业匹配的效率。”
But AI in particular seems to destroy it.
但尤其是人工智能似乎在破坏这种效率。
Employers and employees are locked in an “arms race, where it’s AI—on—AI crime,” Kathleen Creel, a philosopher and computer scientist at Northeastern University, told me.
东北大学的哲学家兼计算机科学家凯瑟琳·克里尔告诉我：“雇主和雇员陷入了一场‘军备竞赛’，这是一场人工智能之间的较量。”
In just a few years, tools such as ChatGPT and Claude have commoditized the production of cover letters and resumes.
仅仅几年时间，像ChatGPT和Claude这样的工具就使求职信和简历的制作变得商业化了。
Large shares of job applicants are using generative chatbots to polish their language and summarize their accomplishments—raising the average quality of these personal documents, at the cost of “compressing” and “homogenizing” the information they convey, as one Columbia Business School paper put it.
很大一部分求职者正在使用生成式聊天机器人来润色他们的语言并总结他们的成就——正如哥伦比亚商学院的一篇论文所说，这提高了这些个人文件的平均质量，但代价是“压缩”和“同质化”了它们所传达的信息。
In Silicon Valley, the phenomenon is sometimes called “signal collapse.”
在硅谷，这种现象有时被称为“信号崩溃”。
CVs used to be filled with advertent and inadvertent signals for hiring managers to parse: degrees and certifications and languages spoken, as well as formatting errors and unusual digressions and over—honest admissions.
过去，简历上满是供招聘经理解析的有意和无意的信号：学位、证书、会说的语言，以及格式错误、不寻常的离题内容和过于坦诚的自白。
Now everyone looks better and everyone looks the same and everyone parrots important key words and everyone uses punchy action verbs.
现在，每个人看起来都更出色，每个人看起来都一样，每个人都重复重要的关键词，每个人都使用有力的行动动词。
Hiring managers are straining to “distinguish underlying expertise,” and to separate precious signal from cacophonous chatbot noise.
招聘经理正在努力“辨别潜在的专业能力”，并从嘈杂的聊天机器人生成的内容中分离出有价值的信息。
Because AI has reduced the time job seekers spend writing applications, people are submitting hundreds of them on ZipRecruiter, LinkedIn, and other sites—often for positions that are not quite a fit, often never to hear anything back.
因为人工智能减少了求职者撰写申请的时间，人们在ZipRecruiter、领英和其他网站上提交了数百份申请——这些申请往往针对的是不太合适的职位，而且常常得不到任何回复。
Applicants aren’t getting feedback on their strengths and weaknesses.
求职者没有得到关于自身优缺点的反馈。
They’re not getting intel on what they might need to do to get hired, or the skills they might need to obtain the job they want.
他们没有得到关于为了获得工作可能需要做什么，或者为了得到心仪工作可能需要掌握哪些技能的信息。
Signal collapse is running in both directions.
信息传递不畅的问题在双向都存在。
To sift through all of those applications, companies are turning, again, to AI.
为了筛选所有这些申请，公司再次将目光转向了人工智能。
A recent survey by Resume Builder found that four in five companies are using AI to scan resumes, two in five are using chatbots to communicate with candidates, and one in five is giving AI interviews.
Resume Builder最近的一项调查发现，五分之四的公司正在使用人工智能来扫描简历，五分之二的公司正在使用聊天机器人与求职者沟通，五分之一的公司正在进行人工智能面试。
AI screening tools in particular are creating an “algorithmic monoculture” in hiring, a new study of 4 million job applications has found.
一项针对400万份求职申请的新研究发现，尤其是人工智能筛选工具正在招聘领域造成一种“算法单一文化”。
More candidates are being rejected by every firm that they apply to; in general, hiring decisions are more uniform than they would be if HR managers were not using algorithmic screens.
更多的求职者被他们申请的每家公司拒绝；总体而言，与人力资源经理不使用算法筛选相比，招聘决策更加统一。
A decade or three ago, firms would “go through the resumes and pick out schools they knew, or fancy schools, or schools that had good programs” in relevant fields, Creel told me.
克里尔告诉我，三四十年前，公司会“浏览简历，挑选出他们熟悉的学校、名校，或者在相关领域有优秀项目的学校”。
“That’s bad in its own way, from an egalitarian point of view. But at least different people had different arbitrary screening criteria.”
“从平等主义的角度来看，这本身是不好的。但至少不同的人有不同的随意筛选标准。”
Moreover, screening algorithms are discriminating against Black and Asian candidates, the paper found.
此外，该论文发现，筛选算法正在歧视黑人和亚洲候选人。
“There’s this filtering happening, and we don’t understand it, because these systems are opaque and custom-built for different institutions, and we don’t know the functionality,” Sarah Bana, a co-author of the paper and a digital fellow at the Stanford Digital Economy Lab, told me.
“正在进行这种筛选，但我们不理解，因为这些系统不透明，是为不同机构定制的，而且我们不知道其功能。”该论文的合著者、斯坦福数字经济实验室的数字研究员莎拉·巴纳告诉我。
Nevertheless, the algorithms’ tendency to advantage the advantaged and disadvantage the disadvantaged seems clear.
然而，算法倾向于让优势群体更有优势、让弱势群体更弱势，这一点似乎很明显。
For candidates who make it past an AI screen, a test such as the one Ken Schumacher administered may await.
对于通过人工智能筛选的候选人来说，可能会面临像肯·舒马赫所组织的那种测试。
Companies ask applicants to describe how they would respond to an unruly customer, or figure out an engineering fix to a software problem.
公司要求应聘者描述他们会如何应对难缠的客户，或者想出解决软件问题的工程方案。
In a lot of cases, this step involves AI writing the exam, proctoring the exam, and taking the exam.
在很多情况下，这一步骤包括人工智能出题、监考和判卷。
“I look at this stuff all day, every day, and even I have to pinch myself sometimes—the amount of fraud!” Schumacher said.
“我每天整天都在看这些东西，有时候连我都得掐自己一下——欺诈的情况太严重了！”舒马赫说。
“It’s just totally ridiculous.”
“这简直太荒谬了。”
The result is that AI is slowing HR down instead of speeding it up, because companies have to spend more time scrutinizing applications and performing background checks.
结果是，人工智能非但没有加快人力资源工作的速度，反而使其放缓，因为公司不得不花费更多时间审查申请并进行背景调查。
A number of large firms are making face-to-face interactions a bigger part of the hiring process again.
许多大公司再次将面对面交流纳入招聘流程的重要环节。
Google is ensuring that candidates have “at least one round” of in-person interviews, to “make sure the fundamentals are there,” Sundar Pichai, its CEO, has said.
谷歌首席执行官桑达尔·皮查伊表示，谷歌正在确保候选人至少进行“一轮”面对面面试，以“确保基本素质达标”。
Cisco is increasing “verification steps and enhanced background checks that may involve an in-person component.”
思科正在增加“验证步骤和强化背景调查，可能包括面对面调查环节”。
Companies are also extending probationary periods and hiring people on contract, with the intention of turning them into full-time employees after managers can vet their work.
公司还在延长试用期，并以合同形式雇佣员工，打算在经理评估他们的工作表现后将其转为全职员工。Finally, some firms are resorting to old-fashioned methods: referrals, alumni networks, local job boards, headhunters.
最后，一些公司正在采用传统方法：推荐、校友网络、本地招聘信息板、猎头。
Schumacher said that firms were “retreating to pedigree.”
舒马赫说，公司正在“回归对出身的看重”。
They aren’t doing this because “the Harvard engineers are the best in the world,” he said.
他说，他们这样做并不是因为“哈佛的工程师是世界上最优秀的”。
“But it’s the safer play in an era where it’s really hard to tell who is legit and who is kind of full of crap.”
“但在一个很难分辨谁是真有本事、谁是徒有其表的时代，这是更保险的做法。”
Even with those techniques, hiring has simply gotten harder—so much so that the entire labor market might become a touch more sclerotic, and business dynamism might dim a bit.
即使有了那些技巧，招聘也变得更难了——以至于整个劳动力市场可能会变得更加僵化，企业活力可能会稍有减弱。
Companies are concerned that worker tenure will go down, as managers end up having to fire underqualified workers and ill—suited employees get frustrated and leave.
企业担心员工的在职时长会缩短，因为经理们最终不得不解雇不合格的员工，而不适合的员工会感到沮丧并离职。
Bana worries about businesses replicating their current workforces, and missing out on employees who might break them out of groupthink and expand their ambitions.
巴娜担心企业会复制现有的员工队伍，从而错过那些可能让他们摆脱群体思维、拓展抱负的员工。
Hoffman, the labor economist, raised the issue of AI reducing workers’ incentive to learn new skills and deepen their expertise.
劳动经济学家霍夫曼提出了人工智能降低员工学习新技能和深化专业知识动力的问题。
What should a person looking for a job in this AI hellscape do?
在这个人工智能的糟糕环境中找工作的人应该怎么做呢？
Nobody I spoke with was certain.
