引导式测验 · 硬 等级

人工智能与就业测验

测试任务暴露、采用不确定性、增强、审查工作量、工人代理、工作质量和当地劳动力市场证据。

相关引导路径人工智能工作
问题 1 的 8

某个职业的 AI 暴露得分较高。这个分数说明了什么？

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  1. 某个职业的 AI 暴露得分较高。这个分数说明了什么？
    • 潜在的任务重叠，不能直接预测失业
    • 每个工人都将被替换
    • 将创造多少新就业岗位
    • 工作场所采用人工智能的日期
  2. Why analyze tasks within a job rather than treating the occupation as one unit?
    • Every task in an occupation has the same technical requirements
    • A role combines tasks that may be automated, augmented, or still need human context
    • Occupation titles fully describe daily work
    • One automated task means the role can be removed
  3. A model can draft a report. Why might an organization still not adopt it?
    • Technical feasibility guarantees deployment
    • Only model size determines adoption
    • Reliability, cost, integration, regulation, and work choices affect adoption
    • Worker training is irrelevant
  4. A tool speeds up one stage but adds a large review queue. What should be evaluated?
    • Only generation speed
    • The number of prompts used
    • The model’s benchmark score alone
    • Total work and job quality after review and correction are included
  5. Which statement distinguishes augmentation from replacement?
    • A system may assist one workflow while automating part of another
    • Every AI use either fully replaces or never changes a job
    • Augmentation means no work changes
    • Replacement can be inferred from task exposure alone
  6. What labor-market evidence should inform a career decision?
    • A global exposure estimate used as a personal forecast
    • Current information for the specific location or occupation
    • A single company’s product launch
    • An old job title list without a date
  7. Which capability can help workers evaluate AI-supported tasks?
    • Prompt memorization without subject knowledge
    • Avoiding all review responsibility
    • Domain knowledge, output evaluation, exception handling, and clear communication
    • Choosing a model by parameter count
  8. Why should workers be able to challenge inaccurate AI outputs?
    • A challenge process guarantees no errors
    • Only managers can detect mistakes
    • A model recommendation removes human accountability
    • They may carry error responsibility and need a way to correct outcomes