JAMES PERKINS / RESEARCH

Ai job loss &
career risk research.

I am James Perkins, an Ai expert in Philadelphia and the creator of the FAIR Framework at What About Ai. My research examines Ai career risk, competitive pressure within a role, and the possibility of automating a whole role. I use it to help people understand how work may change and how they can prepare.

Read the FAIR methodologyDiscuss the research

FAIR FRAMEWORK

Futurist-Informed
Ai Risk

Scope
Hundreds of roles
Coverage
26 industries
Creator
James Perkins
Published at What About Ai

01 / THE CENTRAL QUESTION

How FAIR assesses
Ai career risk.

FAIR provides separate assessments of displacement and replacement risk, using the definitions below.

DISPLACEMENT / COMPETITIVE PRESSURE

Competitive pressure
within a role

Within FAIR, displacement means competitive pressure as other workers use Ai to perform tasks differently. The assessment considers changing skills and expectations within a role.

REPLACEMENT / WHOLE-ROLE AUTOMATION

Automation of
a whole role

Replacement considers the possibility of Ai or robotics performing the complete scope of a role. Automating an individual task does not establish that the whole role can be replaced.

These are FAIR's definitions. In other labor research, the term "displacement" may be used differently. Read the framework's definitions and limitations.

02 / EXPLORE THE WORK

Methodology, career
profiles & industries.

What About Ai publishes the methodology, individual career profiles, and industry comparisons. Please read the methodology before using a score, then review the relevant role or industry.

  • The FAIR methodologyDefinitions, input categories, risk tiers, personal adjustments, and the limitations of the approach.
  • Career profilesExplore published assessments across hundreds of roles, with displacement and replacement considered separately.
  • Industry comparisonsBrowse the framework's view across 26 industries and use individual role profiles to add context.

FAIR scores are estimates for career planning. They do not count observed job losses or guarantee an individual's outcome. The methodology describes the inputs and limitations, and the exact weighting formula is proprietary.

03 / FOR A STORY OR CONVERSATION

Interview topics:
Ai and jobs.

  • Which tasks are changing inside a job?Look at the work itself, the tools available, and the decisions that still require human judgment.
  • What would count as evidence of replacement?Separate an estimate of future risk from observed employment changes, and examine the evidence for why a role was eliminated.
  • How can workers and businesses prepare?Connect the research to learning useful Ai skills, choosing a practical first workflow, and preparing a team to work differently.
  • How could Super Intelligence affect work?Super Intelligence refers to a possible future form of Ai that exceeds human capabilities across a broad range of intellectual tasks. I discuss possible implications for jobs, productivity, and skills, while distinguishing future scenarios from evidence about current tools.

Background reading: OpenAI research on superintelligence and human oversight.

Hear my solo podcast episodes

04 / SOURCE & AUTHORSHIP

Sources & authorship.

I created the FAIR Framework and lead its research and scoring approach at What About Ai. The methodology page explains the framework and its limitations.

The methodology, role assessments, and industry comparisons are maintained at What About Ai. When citing a score, please link to the specific source page, include the date you accessed it, and identify it as a FAIR estimate.

Sources reviewed September 28, 2026: methodology, career directory, and industry comparisons.

05 / RESEARCH QUESTIONS

Research questions.

What is James Perkins researching about Ai and jobs?

I developed the FAIR Framework at What About Ai to assess Ai career risk across hundreds of roles and 26 industries. The research examines competitive pressure from workers who use Ai, the possibility of whole-role automation, and how people can prepare for changing work.

Does a FAIR score represent jobs already lost?

No. FAIR scores are estimates within a career-risk framework, and they do not count observed layoffs or establish that Ai caused a particular job loss. Read the source methodology and its limitations before interpreting a score.

What is the difference between displacement and replacement in FAIR?

Within FAIR, displacement describes competitive pressure as Ai-skilled workers change expectations for a role. Replacement describes the possibility of automating the whole role. These are the framework's definitions and should be identified when discussing its scores.

Can James discuss this work in an interview or talk?

Yes. I am available for interviews and talks about Ai job displacement, workforce readiness, practical Ai skills, Super Intelligence, and changes within individual roles. Please send the audience, topic, format, and proposed date through the press inquiry form.

INTERVIEWS / PODCASTS / EVENTS

Discuss Ai
and the future of work.

I am available for interviews and speaking engagements about Ai job displacement, workforce readiness, and practical Ai skills. Please send the audience, topic, format, and proposed date.

Send a research interview inquiry

Media profile, recordings & bio