The portal flickers again. The scene resolves into a vast, neon-lit cityscape: billboards flicker with “Now Hiring (AI-Friendly Skills Only),” drones hum overhead delivering packages, and in the distance, an entire district sits dark—its shops closed, windows papered over. The map pulses with heat zones, showing where opportunity is growing and where it’s quietly vanishing.
Welcome to the next level of AI’s influence—not in algorithms or clinical tools, but in the world they’re reshaping around us. This is about jobs, justice, and the systems that govern who gets access to both.
The Big Picture: Why AI’s Societal Impact Isn’t “Someone Else’s Problem”
In behavior analysis, we tend to focus on local contingencies: the learner in front of us, the team in our clinic, the organization we run. But AI is shifting macrocontingencies—the large-scale, interconnected systems that set the context for every micro-level behavior we see.
Three forces in particular matter right now:
- Jobs: AI is redefining what skills are valuable, automating parts of clinical and administrative work, and changing how people enter, stay in, or leave the workforce.
- Justice: Algorithms are increasingly embedded in systems that affect healthcare eligibility, educational supports, and even who gets evaluated for certain services.
- Policy Power: Decisions about AI regulation and funding are being made, often without behavior scientists at the table. This leaves gaps in how fairness, access, and evidence-based practice are defined.
Let's take these three categories one at a time.
Jobs — What Happens When the “Skill Tree” Gets Rewritten
Just like in Ready Player One's OASIS, a patch update can suddenly nerf one skill and buff another. AI is doing that to real-world work.
What’s changing in ABA:
- Automation of entry-level tasks: Session note drafting, schedule matching, and basic data summaries can now be handled by AI, reducing the hours needed for RBTs or admin staff.
- Shift in demand toward oversight & analysis: The most valuable clinicians will be those who can audit AI outputs, integrate them with behavioral principles, and communicate the rationale to stakeholders.
- Emergence of new hybrid roles: “Clinical Data Analysts” and “Behavioral AI Coordinators” are starting to appear in large providers. These roles didn’t exist 5 years ago.
Behavior-analytic parallel: Think of an intervention where an assistive device takes over some learner tasks. Here, the role of the instructor changes. The instructor doesn’t become less important, but differently important.
The same applies to clinicians in an AI-enabled workplace.
Questions for the field:
- Are we preparing supervisees for AI-augmented clinical work?
- Will automation reduce job opportunities for entry-level practitioners—or free them for more direct client time?
- How will changes in job structure affect career pipelines into the BCBA role?
Justice — How AI Can Shift Access and Equity
In Ready Player One, access to the OASIS was universal—anyone with a rig could log in. Our world isn’t like that. AI can either reduce or widen inequities depending on how it’s deployed.
Current risks in healthcare and education:
