[논문 리뷰] How Knowledge Workers Think Generative AI Will (Not) Transform Their Industries

Allison Woodruff, Renee Shelby외 4명|arXiv (Cornell University)|2023. 10. 10.

Ethics and Social Impacts of AI참고 문헌 135인용 수 9

한 줄 요약

Qualitative study of seven knowledge industries에서 지식 근로자들이 제너레이티브 AI를 주로 단순 작업을 위한 노력을 절약해 주는 도구로 보고, 인간의 검토가 필요하며, 노동력 저하(deskilling), 비인간화(dehumanization), 단절(disconnection), 허위정보(disinformation)와 같은 사회적 힘을 강조한다.

ABSTRACT

Generative AI is expected to have transformative effects in multiple knowledge industries. To better understand how knowledge workers expect generative AI may affect their industries in the future, we conducted participatory research workshops for seven different industries, with a total of 54 participants across three US cities. We describe participants' expectations of generative AI's impact, including a dominant narrative that cut across the groups' discourse: participants largely envision generative AI as a tool to perform menial work, under human review. Participants do not generally anticipate the disruptive changes to knowledge industries currently projected in common media and academic narratives. Participants do however envision generative AI may amplify four social forces currently shaping their industries: deskilling, dehumanization, disconnection, and disinformation. We describe these forces, and then we provide additional detail regarding attitudes in specific knowledge industries. We conclude with a discussion of implications and research challenges for the HCI community.

연구 동기 및 목표

• 지식 근로자들이 제너레이티브 AI가 장래에 그들의 산업에 어떤 영향을 미칠지에 대한 기대를 탐구한다.
• AI 기반 업무에 대한 일반적 서사와 산업별 관점을 식별한다.
• AI 배치에 영향을 주는 사회적 힘—deskilling, dehumanization, disconnection, disinformation—을 형성하는 요인을 고찰한다.
• HCI 커뮤니티의 시사점 및 연구 도전에 대해 논의한다.

제안 방법

• Three-hour participatory research workshops conducted with 54 participants across seven knowledge industries (advertising, business communications, education, journalism, law, mental health, software development).
• Industry maps, change cards, and policy provocations used to surface use cases, concerns, and governance ideas.
• Reflexive thematic analysis of transcribed sessions and artifacts (industry maps, change cards, policies) to identify themes.

Figure 1. E6 ’s industry map for education. During check-in participants were invited to draw a map of their industry or field.

실험 결과

연구 질문

• RQ1 How do knowledge workers expect generative AI to affect their industries and tasks in the future?
• RQ2 What are the dominant narratives and industry-specific perspectives on AI-enabled work?
• RQ3 What social forces accompany AI deployment in knowledge work and how might they shape outcomes?
• RQ4 What governance structures or over­sight mechanisms do workers see as appropriate for AI use?

주요 결과

• Participants largely envision generative AI as an effort-saving tool for menial, routine tasks, with human review remaining essential.
• There is limited expectation of broad, transformative disruption across industries, contrasting sensationalist narratives.
• A dominant cross-industry narrative emerges: AI handles tedious outputs while humans provide oversight and decision-making, preventing full automation.
• Four social forces—deskilling, dehumanization, disconnection, and disinformation—are anticipated to accompany AI deployment in knowledge work.
• Industry-specific nuances emerge, with concerns about accuracy, brand/copyright constraints, and the need for professional validation of AI-generated work.
• Existing governance and review practices within industries are viewed as adaptable to include AI oversight rather than replacing professional judgment.

Figure 2. M2 ’s industry map for mental health.