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      University of Phoenix research chair presents pilot findings on AI-assisted empathy at 2026 American Psychological Association convention

      University of Phoenix logo with the black and white phoenix bird.

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      University of Phoenix

      Aug 07, 2026, 15:29 ET

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      Dr. Rodney Luster shares early findings and ethical considerations for using generative AI as an adjunct to psychotherapy and counselor training.

      PHOENIX, Aug. 7, 2026 /PRNewswire/ -- Rodney Luster, PhD, University research chair and chair of the Center for Leadership and Entrepreneurial Research (CLER) in the University of Phoenix College of Doctoral Studies, presented pilot research examining the potential use of generative artificial intelligence to support structured empathy practice at the 2026 American Psychological Association annual convention.

      Luster's virtual poster, "In-Session AI Reflection and Empathy: Pilot Findings and Practice Implications," will be presented August 8 as part of the Society for the Advancement of Psychotherapy, Division 29 virtual poster session. The study explored whether professionally facilitated engagement with researcher-constructed AI personas could provide a repeatable environment for practicing perspective-taking, emotional labeling, validation and repair-oriented communication.

      Key points from the pilot study include:

      • Ten adults completed two facilitated AI-persona encounters and pre- and post-experience empathy assessments.
      • Mean empathy assessment scores increased from 23.10 to 25.80, with nine of 10 participants recording higher post-experience scores.
      • The research emphasizes that generative AI should be considered an adjunctive process tool, not a standalone intervention or substitute for instructors, supervisors, clinicians or human relationships.
      • The exploratory findings demonstrate feasibility and a promising association, not evidence that AI independently caused lasting changes in empathy.

      "Empathy is central to effective counseling, yet it can be difficult to practice and assess consistently," Luster said. "This small pilot explored whether professionally facilitated AI personas could offer a repeatable, transcript-rich environment for structured rehearsal and reflection. The goal is not to replace instructors, supervisors or human relationships, but to examine how AI might responsibly support the work they already do."

      Pilot study explores structured empathy practice

      Generative AI is increasingly used by individuals to reflect on interpersonal conflict and emotional distress, but clinicians and counselor educators have limited research-based guidance on whether AI-facilitated reflection can support processes associated with therapeutic change.

      The pilot study examined structured interactions with AI personas created by the researchers to present participants with complex relational experiences. Participants were guided to consider multiple viewpoints, identify and label emotions, respond with curiosity and validation, and develop language oriented toward relational repair.

      Participants completed an eight-item empathy self-assessment before and after the experience. Researchers also reviewed the interaction transcripts for indicators such as perspective taking, empathic concern, emotional labeling, continuity tracking, curiosity and meaning-making.

      The transcripts allowed researchers to examine not only participants' final responses, but also how their communication developed throughout each interaction. According to the pilot findings, progression appeared to depend on accumulated relational safety rather than a single "correct" response.

      Early findings suggest potential for guided reflection

      Mean empathy scores increased by 2.70 points, from 23.10 before the facilitated experiences to 25.80 afterward. The study reported a within-person effect size of dz = 0.89, and nine of the 10 participants increased their assessment scores.

      Nine participants also reached the third level of the researchers' relational progression framework, which represented disclosure of an underlying emotional wound. Qualitative findings included:

      • Greater emotional clarity
      • Increased openness to alternative perspectives
      • Reduced certainty in hostile interpretations of another person's actions
      • Greater readiness to use repair-oriented language
      • Increased recognition of emotional meaning across an interaction

      The results are preliminary. The small pilot did not include a control group, and the findings should not be interpreted as proof that AI caused durable changes in empathy. Participant expectations, the facilitation process and other factors may have contributed to the observed changes.

      Ethical use depends on clinician oversight

      Luster's presentation placed significant emphasis on the ethical and professional guardrails required when integrating generative AI into psychotherapy or counselor preparation.

      The proposed implementation framework maintains that clinicians, instructors and supervisors must retain responsibility for interpreting AI-generated material and determining how, or whether, it should be incorporated into an individual's treatment or learning experience.

      Considerations outlined in the presentation include:

      • Providing clear informed-consent language
      • Protecting client privacy and confidentiality
      • Establishing appropriate therapeutic and instructional boundaries
      • Documenting the use of AI-assisted exercises
      • Preserving client autonomy
      • Reviewing AI-generated output rather than accepting it uncritically
      • Recognizing circumstances in which AI-assisted activities may be inappropriate

      The presentation identified potential contraindications involving high-acuity situations, paranoia or impaired reality testing, heightened suggestibility and increased privacy vulnerability. These guardrails reinforce the study's central position that generative AI should strengthen rather than replace human relationships and professional judgment.

      Implications for research and practice

      The pilot suggests that professionally facilitated AI personas may offer a structured setting for rehearsing difficult conversations, receiving immediate relational feedback and reviewing detailed transcripts with an instructor, supervisor or clinician.

      Potential applications identified in the presentation include guided reflection involving relationship rupture, workplace conflict, values-based decision-making and supervised counselor empathy practice. The approach may allow participants to practice communication responses repeatedly before applying them in interpersonal or professional settings.

      Further research is needed to determine whether the findings can be replicated and whether observed changes continue over time. Recommended next steps include studies with larger and more demographically diverse samples, controlled comparisons, independent validation of the researchers' relational progression framework and assessment of outcomes across different participant and clinical populations.

      View the presentation abstract and poster on the APA 2026 program website.

      About Rodney Luster

      Rodney Luster, PhD, LPC, is a University research chair and chair of the Center for Leadership and Entrepreneurial Research in the University of Phoenix College of Doctoral Studies. CLER supports applied, multidisciplinary research related to leadership, organizational strategy, industrial-organizational research and transformative learning. Luster's scholarship examines relational dynamics, difficult conversations and practical approaches that may help individuals and organizational leaders navigate complex interpersonal experiences. He also publishes regularly on the Psychology Today blog.

      About the College of Doctoral Studies

      University of Phoenix's College of Doctoral Studies focuses on today's challenging business and organizational needs, from addressing critical social issues to developing solutions to accelerate community building and industry growth. The College's research program is built around the Scholar, Practitioner, Leader Model which puts students in the center of the Doctoral Education Ecosystem® with experts, resources and tools to help prepare them to be a leader in their organization, industry and community. Through this program, students and researchers work with organizations to conduct research that can be applied in the workplace in real time.

      About University of Phoenix

      University of Phoenix is Built for Real Life. 50 Years Strong. The University innovates to help working adults enhance their careers and develop skills in a rapidly changing world through flexible online learning, relevant courses, academic AI pillars, and skills-mapped curriculum for associate, bachelor's and master's degree programs. Active students and alumni have access to Career Services for Life® resources including career guidance and tools. For more information, visit phoenix.edu.

      SOURCE University of Phoenix

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