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Research Assistant
Working in America project

Stanford Institute for Human-Centered Artificial Intelligence
Stanford Digital Economy Lab

Posted
March 31, 2023

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Background
The Working in America Project at the Stanford Digital Economy Lab (DEL) aims to explore how AI and other digital technologies are transforming the future of work in the United States. The project has two main components—quantitative datasets and qualitative interviews—that we will bring together in multimedia formats. The primary website will provide quantitative data about each of 50 selected occupations. These data visualizations will include common, publicly-available measures (e.g., wages and employment trends) as well as the Lab’s original research (e.g., vulnerability to automation, work from home potential, and skill composition).

These data will be presented alongside multimedia narratives derived from 60-minute interviews with members of each occupation. The interview and resulting stories will contextualize and humanize the quantitative data, enabling core messages about the future of work in America to be delivered to a broader audience than academia. We envision the website and other materials being useful for Americans seeking new career opportunities or a better understanding of their prospects; organizations seeking to understand the trajectories of the workforce and their industries; educational institutions seeking to better prepare students for the jobs of the future; and policymakers, unions, and other groups seeking to inform their efforts to improve employment prospects, working conditions, and overall economic prosperity.

To apply
Please send your CV to Susan Young at susany@stanford.edu.

Job description

The RA will be responsible for two core tasks: (1) recruiting interviewees and (2) cleaning interview transcripts. We anticipate the work to take between 5 and 10 hours a week through June 2023.

Recruiting Interviewees
Responsibilities: The qualitative portion of the project centers around interviews with workers in 50 occupations, ranging from blue-collar work, such as construction, to white-collar work, such as software engineering. The RA will be responsible for recruiting 25 to 30 individuals from the remaining occupations on our list. Recruitment requires:

  • – Sending emails and messages (e.g., LinkedIn messages) to prospective interviewees
  • – Conducting outreach phone calls to organizations (e.g., businesses, government agencies, or unions) to inquire about potential interviewees
  • – Posting advertisements (e.g., Craigslist, Reddit, online forums) to reach occupational communities
  • – Coordinating delivery, signing, and archiving of audio/video release forms
  • – Scheduling interviews using Calendly
  • – Answering process questions or rescheduling requests for potential and scheduled interviewees, in consultation with the qualitative research lead

Skills:

  • – Very strong written and verbal communication skills
  • – Persistence in following up on leads
  • – Creativity in pursuing new recruitment avenues when others fail
  • – Ability to explain the purpose/outputs of the project and the consent process
  • – Ability to walk potential interviewees and their organizations through the risks and non-risks of participating

Cleaning Transcripts
Responsibilities: Each interview will be recorded in audio and/or video format and uploaded to a transcription tool (Ottter.ai). The text output of the transcription is not always 100% accurate. The RA will be responsible for:

  • – Reading through the transcript and identifying issues, then going back to the audio to listen for corrections and edit the transcript
  • = Common errors include occupation-specific jargon and proper nouns (e.g., names of software or organization acronyms), which requires using online search to find the actual words and insert them into the transcript.
  • – Additional errors include regional accents and dialects and distorted audio.
  • – Removing extraneous words such as “um,” “err,” and other phrases when they distract from the core message of the interviewee
  • – Formatting the transcript from the output of the transcription tool using a predefined template
  • – Forwarding receipts for the transcription service invoice to DEL administrators

Skills:

  • – Attention to detail
  • – Ability to creatively use search tools to discern jargon and other transcription issues
  • – Eagerness to learn Otter.ai functionality and use it effectively, particularly audio-text matching
  • – Optional: Interest in identifying “interesting” quotes from interviews to flag for the research team

Other opportunities (optional)
The RA will be welcome to join and contribute to research and editorial team meetings, where we discuss ongoing work and the project’s direction.

To apply
Please send your CV to Susan Young at susany@stanford.edu.


The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned. 

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

About us

The Stanford Digital Economy Lab brings together an interdisciplinary group of passionate researchers to study how digital technologies are transforming work, organizations, and the economy. Our insights are helping companies, policymakers, students, and professionals rise to the challenges and opportunities created by digitization. We believe in the power of human work and that augmenting human capabilities with machine capabilities will lead to the most profitable gains for everyone.

The Lab is part of the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and is co-sponsored by the Stanford Institute for Economic Policy Research (SIEPR).

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