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자동화된 채용 심사에 관한 세미나

이름:날짜:

교수와 두 학생이 자동화된 도구가 입사 지원서를 공정하게 분류할 수 있는지, 그리고 조직에 어떤 안전장치가 필요한지 토론합니다.

오디오와 정답 확인: https://joy-english.com/ko/listening/hiring-software-seminar

태도, 의견, 추론

듣고 가장 알맞은 답을 고르십시오. 일부 답은 직접 언급되지 않습니다.

  1. What is Marco's main criticism of the company?
    • a) It used a program that was too slow
    • b) It refused to hire any new staff
    • c) It ignored its own past decisions completely
    • d) It treated the software as objective without questioning how it learned
  2. What point is Lin making about human recruiters?
    • a) They are always faster than software
    • b) They are also far from neutral, and a program can at least be checked
    • c) They should never review applications
    • d) They have no influence on the final decision
  3. What does the figure of seven seconds suggest to Lin?
    • a) That people judge applications very quickly
    • b) That programs read applications more slowly
    • c) That most applications are rejected unread
    • d) That recruiters are overworked
  4. What prevented the company from auditing the tool?
    • a) The company did not employ enough staff
    • b) The tool was too new to be tested
    • c) The supplier would not reveal how it worked
    • d) Applicants refused to give their data
  5. Why does Marco call the lack of explanation "the real scandal"?
    • a) It made the company lose money
    • b) Rejected applicants had no way to challenge the decisions
    • c) It broke the supplier's contract
    • d) It meant too many people were hired
  6. What does Lin mean by saying efficiency is "mistaken for fairness"?
    • a) Fair tools are always the most efficient
    • b) Efficient firms treat applicants better
    • c) Fairness is easier to measure than speed
    • d) A tool that saves effort is wrongly assumed to be just
  7. What reservation does Marco express about testing?
    • a) Firms only look for biases they already know about
    • b) Testing is too expensive for most firms
    • c) Tools cannot be tested before they are used
    • d) Testing always proves that a tool is fair
  8. What does the professor imply about a human decision at the end of the process?
    • a) It is unnecessary if the program is accurate
    • b) It should be carried out by the supplier
    • c) It is valuable only if the person genuinely judges the result
    • d) It always prevents unfairness

세부 내용 듣기

다시 듣고 빠진 단어나 숫자를 입력하세요. 숫자는 단어나 아라비아 숫자로 써도 됩니다.

  1. The software had learned from ___ years of past hiring decisions.
  2. Reviewers spent an average of ___ seconds on each application.
  3. The supplier described its method as a trade ___.
  4. Lin describes ___ applications in a week as a cost problem.
  5. Each student must draft a ___-page policy.

정답

태도, 의견, 추론

  1. d) It treated the software as objective without questioning how it learned그는 소프트웨어가 과거의 결정에서 배워 그 안의 패턴을 그대로 재현했을 뿐이므로, 그것을 객관적이라고 부른 것은 부주의했다고 말합니다.
  2. b) They are also far from neutral, and a program can at least be checked그녀는 사람이 결코 중립적이지 않다며 즉흥적인 판단을 예로 들고, 프로그램은 감사할 수 있다고 말합니다.
  3. a) That people judge applications very quickly그녀는 그것이 사람 검토자의 즉흥적인 판단이 많다는 것을 시사한다고 말합니다.
  4. c) The supplier would not reveal how it worked공급업체는 자사의 방식이 영업 비밀이라고 말했고, 그래서 회사는 탈락 이유를 설명할 수 없었습니다.
  5. b) Rejected applicants had no way to challenge the decisions그는 설명이 없으면 탈락한 지원자가 그 결정에 이의를 제기할 수 없다고 말합니다.
  6. d) A tool that saves effort is wrongly assumed to be just그녀는 그 도구가 비용 문제를 해결하지만 그것이 공정하다는 것을 입증해야 했던 사람은 아무도 없었다고 말합니다.
  7. a) Firms only look for biases they already know about그는 일부 기업이 신중하게 검사하지만 이미 알고 있는 편향에 대해서만 검사한다고 말합니다.
  8. c) It is valuable only if the person genuinely judges the result그녀는 단지 승인 버튼을 누르는 사람은 그다지 안전장치가 되지 못하므로, 그 사람의 실제 역할이 중요하다고 말합니다.

세부 내용 듣기

  1. ten / 10Marco는 그것이 10년간의 과거 결정에서 배웠다고 말합니다.
  2. seven / 7Lin은 평균 7초를 인용합니다.
  3. secret공급업체는 그 방식이 영업 비밀이라고 말했습니다.
  4. ten thousand / 10000 / 10,000Lin은 일주일에 지원서 10000건은 비용 문제이고, 그 도구가 그것을 해결한다고 말합니다.
  5. one / 1 / single교수는 각자에게 한 쪽짜리 정책안을 작성해 오라고 요청합니다.

스크립트

Professor Siddiqui: Last week we looked at how automated tools sort job applications. This week I'd like your reactions to the case study. Marco, you've read it. Was the company wrong to use the system?

Marco: Not necessarily wrong, though I'd say careless. The company claimed the software was objective because it had no opinions. But it had learned from ten years of past hiring decisions, and if those decisions favoured a certain kind of candidate, the system simply reproduced the pattern, only faster.

Lin: I'd push back a little. Human recruiters are hardly neutral. One study in the reading found that people reviewing applications spent an average of seven seconds on each one, which suggests plenty of snap judgements. At least a program can be audited.

Professor Siddiqui: An important distinction. Can it be audited in practice?

Lin: That depends on whether anyone is allowed to look inside. In this case the supplier refused, saying the method was a trade secret, so the company couldn't explain its own rejections.

Marco: Which seems to me the real scandal. Had the company been able to explain a decision, a rejected applicant could have challenged it. As it was, people were turned away by a process nobody could describe.

Professor Siddiqui: So the objection is not to the technology as such, but to its opacity.

Lin: Mostly, yes, though I'd add that efficiency is being mistaken for fairness. Ten thousand applications in a week is a cost problem, and the tool solves the cost problem. Whether it's fair is a separate matter that nobody was obliged to answer.

Marco: I'm not sure I'd go quite that far. Some firms do test their tools carefully. The difficulty is that they test for the biases they already know about.

Professor Siddiqui: Which brings us to your assignment. I'd like each of you to draft a one-page policy for a small organisation that wants to use such a tool. I don't want a ban, and I don't want blind enthusiasm. What safeguards would you require? Think about who should be able to see the results, how often the system should be reviewed, and what an applicant is entitled to ask.

Lin: Can the policy include a human decision at the end?

Professor Siddiqui: Certainly, but be specific about what that person actually does. A human who merely clicks approve on a machine's recommendation is not much of a safeguard.