Empowering the Psychology Major Through AI Integration: Comment on Robinson et al. (2026)

Empowering the Psychology Major Through AI Integration: A Commentary

Artificial intelligence (AI) is reshaping higher education at an extraordinary pace. Consider this fact: Bowen and Watson published the first edition of their book Teaching with AI: A Practical Guide to a New Era of Human Learning in 2024, and they immediately published a second edition in 2025. “Now completely revised!” says the book's website, and I do not doubt it. Of course, I cannot say for sure because I have not had time to read the second edition between completing AI workshops, writing articles on teaching with AI, serving on AI-focused professional committees, editing journal submissions about AI, and revising my courses each semester to better address AI. As a psychology professor involved in teaching, scholarship, and service, it has become impossible to track the frenzy of AI developments in education, let alone systematically implement them in my courses. I need AI help, and I am not alone.

In response to educators’ need for AI guidance, Robinson et al. (2026) provide a model for integrating AI into the teaching of psychology. Their model is informed by their work as members of the American Psychological Association's (APA) Board of Educational Affairs and Committee on Associate and Baccalaureate Education. Robinson et al. argue that there is “a unique and time-sensitive opportunity for the development of a psychology major that integrates AI proficiency as a key component.” Robinson et al. frame the integration of AI skills into the curriculum as an obligation that psychology educators have to students and to higher education. Integration would involve adding AI proficiency to the APA undergraduate learning goals (American Psychological Association, 2023), principles for quality in undergraduate education (American Psychological Association, 2011), and definition of workplace skills (Naufel et al., 2019). Robinson et al. initiate this process by offering examples of how AI skills could be aligned with each of these APA resources.

Robinson et al. (2026) provide a cogent and useful proposal for teachers of psychology. Three key assumptions underlie the proposal: (1) the educational implications of AI should not be ignored, (2) students will increasingly need AI skills to be successful in psychology and the workforce, and (3) efforts to integrate AI skills into the curriculum should be structured around the APA's resources on undergraduate education. I accept these assumptions based on philosophical and practical grounds. Therefore, I agree that educators should begin the substantial task of defining what it means to provide an AI-infused undergraduate education. Before commencing such an important task, however, there are additional points to consider. Building from Robinson et al.'s (2026) work, I will provide special emphasis to some of the proposal's points, illustrate some ideas that require further development, and pose some open questions.

Points of Special Emphasis

Robinson et al. (2026) make many important points about integrating AI into undergraduate psychology, but some deserve special emphasis. Perhaps the most interesting argument in Robinson et al.'s (2026) article is that the discipline of psychology has an obligation to lead higher education's efforts to integrate AI into the curriculum. Is psychology responsible for this task? Obligated or not, psychology is better situated than other disciplines to take on the task. After all, psychology is the most important contributor to the fundamentals of education. Consider that basic psychology research is the source of knowledge about learning, memory, and motivation. Also, applied areas of psychology guide effective techniques for instruction, measurement, and collaboration. Beyond establishing the basics of good pedagogy, psychology's fundamental empiricism limits the rhetorical, aesthetic, and pseudoscientific excesses that might interfere with other disciplines’ responses to AI. Although some might argue against AI-focused obligations, framing the task of AI integration as a professional duty to higher education could be an effective way to motivate psychology teachers to take on the task.

Another argument for taking on the “AI obligation” is that psychology skills will be essential for future workers. Leaders in business and industry contend that the increased efficiency offered by AI will make uniquely human work skills more, not less, important (Microsoft Corporation, 2023; World Economic Forum, 2025). With AI completing repetitive and computational tasks, humans will be left to apply skills related to critical thinking, statistical reasoning, awareness of bias, and communication. They will also need to collaborate, listen, use self-awareness, and apply principles of learning and growth. These so-called “human skills” are transparent examples of psychological skills (American Psychological Association, 2023; Naufel et al., 2019). No other discipline requires its students to possess such a unique combination of abilities related to science, sociability, and the self. Because of psychology's connection to classic liberal arts skills, teachers have long framed it as a key part of a general education (Chew et al., 2022; Harper, 1954). Now, teachers should emphasize psychology as a key part of an AI-ready education.

Robinson et al. (2026) propose an integration of AI proficiencies across The Skillful Psychology Student's list of workplace skills (Naufel et al., 2019), and this leads to another point in need of special emphasis: Very few of the proposed career paths integrating AI and psychology involve helping professions such as counseling and social work. I see this as a strength. Emphasizing the varied career paths open to students who possess both AI and psychology skills can benefit the profession. Students interested in helping others will always be attracted to psychology. However, psychology can also benefit students who are interested in pure science and those who want a direct path to the workforce. Psychology programs could be more effective at recruiting students who find the subject fascinating but mistakenly think that majors in STEM, business, marketing, or communication are the only paths to a career. One method for recruiting such students may be to promote psychology as the field that integrates AI preparation with psychology skills that are applicable across varied career paths. Psychology could become a new general-purpose degree that builds resumes filled with the AI and human skills that are required in a 21st century workplace.

Points Requiring Further Development

Although Robinson et al.'s (2026) article provides a starting point for the integration of AI into the psychology major, some points require further development before enacting the plan. The plan focuses on the use of AI to accomplish work-related tasks. Learning to use AI is important, but students also need to apply traditional psychology skills in ways that will allow them to be successful in the world of AI. As previously noted, the human skills that are of increasing importance in the AI-integrated workplace—critical thinking, communication, collaboration, and self-awareness—are fundamentally related to psychology. As such, professional development for psychology undergraduates should convey the increasing value of such skills in the workplace and teach students to emphasize their ability to apply both human skills and AI skills in their work. This type of strategic skill presentation is consistent with the APA's (2023) broad undergraduate outcome to “develop direction for life after graduation” and its narrow goal to “create and maintain a resume or curriculum vitae that showcases a psychology background” (p. 21).

Before students can “showcase” their psychology background, they will need to achieve the APA's (2023) learning goals for self-regulation and problem-solving. Inevitably, overuse of AI will impede some students’ learning. A specific type of AI-hobbled student will emerge who can complete competent work outside of class but cannot verbally explain what they have done or pass closed-book tests. Such students will know how to prompt AI to complete assignments, but not how to learn from that prompting or its output.

Given the potential threats of AI to learning, students need the ability to motivate themselves to complete the preparatory work required to learn when AI offers an efficient alternative. Why read a journal article when AI can write a summary? They also need to know how to strategically engage in the desirable difficulties associated with learning when AI can eliminate the cognitive effort required to answer their questions about psychology. Why complete a practice quiz when AI can answer test questions? Put in the APA's (2023) terms, students will need to “exhibit effective self-regulation” in the realm of learning (p. 19) and “apply psychological content to solve practical problems” in their education (p. 8). Based on the tendency for students to adopt practical rather than effective learning strategies (Bjork et al., 2013; Kornell & Bjork, 2007), motivating students to learn when AI can easily do the work for them may be the most difficult challenge of AI integration. It will require setting high standards for testing student knowledge and mentoring students in the application of psychology principles to meet those standards.

Another skill psychology students need for the AI world is ethical decision-making. The APA (2023) undergraduate outcomes state that students will “employ ethical standards in research, practice, and academic contexts” (p. 13), and AI poses new ethical challenges in each of those areas. AI skills, no matter how well-developed, will not benefit students who cannot be trusted to follow the rules when applying those skills. Teaching students the ethics of AI is not synonymous with banning the use of AI. Rather, students need opportunities to apply AI within clearly set parameters. They need practice following ethical guidelines.

To demonstrate the ability to use AI ethically, students should learn to translate the transparency of open science to their learning (Boysen, 2026). When researchers lost faith in the legitimacy of psychological findings, they adopted open science practices to regain trust (Center for Open Science, 2025; Hales et al., 2019). Now that it is often unclear if student work is human- or AI-generated, open learning practices can restore faith in the legitimacy of learning (Boysen, 2026). For example, open science makes data transparent by publicly sharing it, and open learning practices make the resources students use to complete work transparent by saving and sharing copies of sources, annotations, and AI transcripts. Similarly, open science makes study protocols and materials publicly available, and open learning practices make the learning process public by documenting every stage of work (e.g., brainstorming, outlining, drafting) and completing work using files that track changes and save version histories. By adopting these open practices, students can create portfolios illustrating their ability to accomplish tasks without AI and with appropriate AI contributions.

Of all of Robinson et al.'s (2026) proposals, integration of AI into the APA's (2011) Principles for Quality Undergraduate Education is the idea most in need of development. Unlike the undergraduate learning goals (American Psychological Association, 2023) and workplace skills (Naufel et al., 2019), the Principles for Quality primarily focus on faculty activities. Examples of faculty AI integrations include establishing departmental AI policies, designing AI coursework, and offering AI-focused workshops. However, the only suggestion for how faculty develop the knowledge and skills to engage in such activities is to “participate in APA or institutional workshops.” More is needed. According to the Digital Education Council (2025) survey cited by Robinson et al. (2026), faculty perceive the main barriers to using AI as a lack of time (40%) and not knowing what they would use it for (38%). Furthermore, 40% of faculty rated themselves as having little AI knowledge, and 43% rated themselves at the intermediate level. Workshops alone will not produce faculty with the time and knowledge required to transform the psychology curriculum.

If psychologists are to lead higher education in AI integration, then the profession needs to invest in faculty training. The APA and other organizations should ensure that every national and regional conference has AI-training tracks. Then, organizations should invite excellent in-person presenters to offer online workshops. In addition, the organizations should offer structured online courses where faculty can earn AI certifications in teaching, research, and practice. A profession-wide shift in education will not occur without sufficient financial backing. Thus, AI training opportunities should be subsidized so that they are free to faculty. Moreover, grants for AI research and training will need to take precedence in the coming years. To ensure that faculty have the time for AI training, some funding will need to be available for teachers to buy out of other paid responsibilities. Investments reveal priorities, and AI integration is an opportunity for psychology to prioritize the future of education in the discipline.

Open Questions

Despite the cogency of Robinson et al.'s (2026) call to integrate AI skills into the psychology curriculum, unanswered questions remain. Robinson et al. assert that AI integration represents a “time-sensitive opportunity” for psychology, but what is the timeline? It is not clear how fast psychology educators need to move to keep up with advancements in AI technology. Psychologists can only passively observe AI developments and the subsequent integration of AI into the technology used for teaching, research, and practice. Plans for AI integration into psychology might be out of date before they can be enacted.

I will share one example of educational obsolescence caused by AI developments. Traditionally, writing an evocative case study that depicts a mental disorder is a labor-intensive task that can take hours of drafting and editing. Now, AI can generate new case studies on demand. Recognizing the educational value of student access to unlimited case studies, I created an AI bot that produced cases for students to use in testing their diagnostic abilities. Then the AI model changed. The new AI model deemed the case study bot to be a violation of its rules for offering mental health advice, and my AI work became obsolete based on changes I could not predict or control. I appealed the violation and was immediately denied, presumably by the same AI program that made the initial judgment.

I offer just one example, but imagine thousands of psychology teachers diligently working to integrate AI into their curricula and course materials, only to find that some unforeseen development in AI has made their plans obsolete. Moreover, psychology educators are competing against educational technology companies that are racing to create AI learning tools. Well-trained faculty can create AI materials to meet the needs of a new psychology curriculum, but teacher-made products are unlikely to achieve the quality, capabilities, or convenience of those created by well-funded professionals. Consider the dominance of professionally designed textbooks, videos, and courseware over educator-created materials in most psychology curricula. Haste in building AI content could result in wasted effort spent on developing materials that teachers never adopt. Overall, psychologists face an uncertain timeline that does not clearly indicate how quickly they should proceed or how much effort they should put into designing their own AI-based educational materials.

In addition to an unknown timeline, the method for implementing change is not clear. What is the mechanism for enacting a profession-wide shift in undergraduate psychology education? Robinson et al.'s (2026) premise is that change can begin with the APA's existing guides on undergraduate education (American Psychological Association, 2011, 2023; Naufel et al., 2019). This is an essential step, but it is not the only one. Another step toward change might be to organize a national summit on the integration of AI into the psychology major. Past summits of this type have focused on undergraduate education in psychology (Halpern, 2008), assessment within psychology (American Psychological Association, 2025), and the introductory psychology course (American Psychological Association, 2024). These summits produced influential resources for psychology teachers to use in curriculum planning, but did they truly produce a unified approach to psychology education? Additional steps are needed.

One limiter of the influence of the APA's undergraduate education resources is the lack of regulation behind them (American Psychological Association, 2011, 2023; Naufel et al., 2019). No mechanism ensures that psychology curricula are consistent with the resources—they are just recommendations. In contrast, psychologists have widely adopted other educational materials that are backed by more professional oversight, be it direct or indirect. At the undergraduate level, teachers follow the stipulations of the APA's Publication Manual and Ethical Principles. At the graduate level, the APA sets accreditation standards for professional programs. Among psychology teachers, following the APA's style rules, ethical principles, and accreditation standards are just accepted parts of their job. Perhaps increased professional oversight of the undergraduate curriculum is a way forward in producing a unified shift toward AI integration.

Conclusion

When teachers first started to recognize the implications of ChatGPT for education in early 2023, I advocated a cautious response. “It's too early,” I said to colleagues, “We don’t know enough about AI. We shouldn’t change our courses yet.” Today, I would say, “We don’t know enough about AI. And we must change our courses right now.” Robinson et al. (2026) give teachers a guide for the first steps in changing not only courses but the entire psychology curriculum. Integrating AI into the major will allow psychology to continue to be a leader in effective educational practices and could be a means for attracting students to the field. However, integration of AI skills should not obscure the human skills students develop in psychology. Simultaneous development of students’ scientific, humanistic, and AI skills is a lofty goal, and psychology teachers will need extensive professional development and financial support to achieve it. When and how will the goal be achieved? These are open questions, but the profession should forge ahead even if “we don’t know enough about AI.”