This comparison draws in part from “Behavior Analysis and Artificial Intelligence: Promoting Equity in Algorithms” by Jewel Parham, Ph.D., MS, BCBA-D, LBS (BehaviorLive), and extends it with peer-reviewed research from our library of 27,900+ ABA research articles. The decision framework, BACB ethics code references, and cross-links below are synthesized by Behaviorist Book Club.
View the original presentation →One of the most consequential decisions a behavior analyst makes is not just what intervention to use, but how to approach the clinical question in the first place. For behavior analysis and artificial intelligence: promoting equity in algorithms, the difference between an evidence-based, individualized approach and a traditional, protocol-driven one can significantly impact outcomes.
This guide lays out the key factors side by side to support your clinical decision-making.
| Factor | Evidence-Based Approach | Traditional Approach |
|---|---|---|
| Scope Of Use | For Promoting Equity in Algorithms, validated and supervised technology integration keeps scope of use tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves scope of use to informal judgment, which makes follow-through harder to defend when conditions change. |
| Privacy Protection | For Promoting Equity in Algorithms, validated and supervised technology integration keeps privacy protection tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves privacy protection to informal judgment, which makes follow-through harder to defend when conditions change. |
| Decision Support | For Promoting Equity in Algorithms, validated and supervised technology integration keeps decision support tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves decision support to informal judgment, which makes follow-through harder to defend when conditions change. |
| Supervision Burden | For Promoting Equity in Algorithms, validated and supervised technology integration keeps supervision burden tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves supervision burden to informal judgment, which makes follow-through harder to defend when conditions change. |
| Error Detection | For Promoting Equity in Algorithms, validated and supervised technology integration keeps error detection tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves error detection to informal judgment, which makes follow-through harder to defend when conditions change. |
| Staff Adoption | For Promoting Equity in Algorithms, validated and supervised technology integration keeps staff adoption tied to the technology-supported task, human oversight step, and error risk the team must define upfront and makes the decision easier to review in documentation workflows, supervision meetings, treatment planning, and quality review. | For Promoting Equity in Algorithms, novelty-driven adoption without safeguards leaves staff adoption to informal judgment, which makes follow-through harder to defend when conditions change. |
The ABA Clubhouse has 60+ on-demand CEUs including ethics, supervision, and clinical topics like this one. Plus a new live CEU every Wednesday.
Use this framework when approaching behavior analysis and artificial intelligence: promoting equity in algorithms in your practice:
Does the data support a need for intervention? Is there a meaningful impact on the individual's quality of life, safety, or access to reinforcement?
YES → Proceed to assessment NO → Document reasoning, monitor
A functional assessment should guide intervention selection. Avoid defaulting to standard protocols without individual analysis. Consider environmental variables, setting events, and private events.
YES → Select evidence-based approach matched to function NO → Complete assessment first
Goals should be co-developed. Assent and informed consent are ethical requirements. The individual's preferences and values matter in selecting both goals and methods.
YES → Proceed with collaborative plan NO → Engage in shared decision-making
This course covers the clinical and ethical dimensions in detail with structured learning objectives and CEU credit.
Behavior Analysis and Artificial Intelligence: Promoting Equity in Algorithms — Jewel Parham · 1 BACB General CEUs · $20
Take This Course →We extended this decision guide with research from our library — dig into the peer-reviewed studies behind each approach, in plain-English summaries written for BCBAs.
279 research articles with practitioner takeaways
239 research articles with practitioner takeaways
236 research articles with practitioner takeaways
1 BACB General CEUs · $20 · BehaviorLive
Research-backed educational guide
Research-backed answers for behavior analysts
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All behavior-analytic intervention is individualized. The information on this page is for educational purposes and does not constitute clinical advice. Treatment decisions should be informed by the best available published research, individualized assessment, and obtained with the informed consent of the client or their legal guardian. Behavior analysts are responsible for practicing within the boundaries of their competence and adhering to the BACB Ethics Code for Behavior Analysts.