Stanford University

The Working in America project will fuse the Lab’s data-driven insights with stories of US workers and the obstacles and opportunities they experience in the digital age.

The Stanford Digital Economy Lab is embarking on a far-reaching multimedia project that will explore how AI and other digital technologies are transforming the future of work in America—and how companies and workers can adapt and thrive.

Project goals

  • Spotlight the realities of workers on the front lines of change due to digitization and automation.
  • Contextualize and humanize data to reach a general audience beyond academia.
  • Highlight pathways forward for workers whose occupations are likely to experience a transition.
  • Promote the Lab’s vision of a tech-driven economy that benefits everyone.
  • Produce a repository of research and stories about people and occupations at a critical moment in American history.

Working in America will portray the human story of the automation revolution supported by research and evidence-based data from the Stanford Digital Economy Lab and other trusted sources.

The stories

Working in America will document a key moment in the history of labor and automation.

  • The project will portray real workers across a range of roles—from blue-collar to white-collar to gig workers—who are experiencing the effects of automation.
  • Depict themes affecting specific communities or geographic regions.
  • Explore the connective tissue between various lines of work and examine how displacement in one occupation might affect others.
  • Demonstrate how workers are adapting—or not—to change, such as re-skilling or pursuing a new occupation.
  • Examine how policymaking related to digitization is affecting people and occupations.

The data

Working in America will harness the Lab’s granular research and data focused on digitization and the future of work.

  • Suitability for Machine Learning Rubric
    In previous research, we evaluated every job task in the ONET database for its suitability for machine learning, or SML, using a rubric that scores each task on 23 different criteria. A new project, Suitability for Machine Learning Rubric (SML), offers a theoretical framework for how occupations will change and predicts which occupations specifically are most exposed to advances in machine learning methods as they propagate through the network of job tasks.
  • work2vec
    Using data from 200 million online job postings, the Lab is training a natural language processing (NLP) model to learn the language of jobs. The work2vec project analyzes how jobs have changed in the past decade and demonstrates how different words in postings denote different occupations. In using this approach, researchers will create novel indexes of jobs, such as work-from-home ability.

Media +

African-American nurse smiling

Digital series

A media-rich web and digital presence will serve as the nexus of the project, with content pushed to social channels, including Twitter, LinkedIn, Instagram, YouTube, and Medium.  

Erik Brynjolfsson talking at an event


In-person and virtual events will bring researchers, industry experts, thought leaders, and the general public together to discuss and debate the future of work.

Screenshot of Working in American podcast page


Podcast series will elevate the voices and experiences of workers on the front lines of change with themes based on geography, socioeconomics, or other connective thread.

Man working with tools in workshop


A multi-episodic examination of how automation is changing work in America featuring stories of real people on the front lines of change.

Two hands holding coffee table book


A large-format publication will serve as a repository of stories and data—a time capsule documenting a key moment in the history of labor and automation in America.

By 2030, automation may force as many as 375 million workers around the world to switch occupational categories and learn new skills.

One-third of the U.S. workforce could be affected.


Be part of the groundbreaking Working In America project.

  • Be a Working In America Supporter
    Make a grant or donation to help fund the Working in America project.
  • Be a Working In America Outreach Partner
    Help us spread the word through social and organizational networks.
  • Be a Working In America Production Collaborator
    Join forces with us to co-create and distribute original content.

Contact Christie Ko, executive director of the Stanford Digital Economy Lab, at

Giving levels

Number of donors neededAmount
1 @$1M
3 @$250,000
5 @$50,000

Total funding needed: $2M
Timeframe: Aug 2021 – July 2023

About us

The Stanford Digital Economy Lab is an integral part of the Stanford Institute for Human-Centered AI (HAI). We are the Institute’s primary hub for conducting research related to the economic implications of technology—a demonstration of HAI’s multidisciplinary approach to addressing complex problems. The Lab is co-sponsored by the Stanford Institute for Economic Policy Research.

Stanford University