Psychology & AI: 9 Examples & Apps

Artificial intelligence’s (AI) successful relationship with psychology has not just appeared; it has been evolving for decades.

Joseph Weizenbaum from MIT developed the first chatbot, ELIZA, in 1966. Although relatively simple, ELIZA effectively mimicked a psychotherapist, marking a significant milestone in AI development (Weizenbaum, 1976; Mullins, 2005).

Much has happened since.

In 2022, building on earlier AI successes, OpenAI launched ChatGPT. It rapidly gained attention from the media, public, businesses, educational institutes, and health professionals for its potential to converse in any domain, including psychology and mental health (Dempere et al., 2023).

This article explores artificial intelligence’s capacity to transform our understanding of human psychology and improve our mental wellbeing.

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The Role of Artificial Intelligence in Psychology

Researchers have been working on artificial intelligence for many years with considerable success, creating systems that are increasingly “proficient in mimicking human-like communication with the end user” (Dempere et al., 2023, p. 2).

However, when OpenAI released ChatGPT at the end of 2022, it was to be a game changer, making AI accessible to millions, from interested individuals, corporations, educators, and researchers to therapists (Hua et al., 2024).

ChatGPT is one of several large language models (including Google’s Gemini) known as generative AI. It can be used to power chatbots, search engines, and applications engaged in activities as diverse as word processing, translation software, navigation, health care, and counseling (OpenAI, 2023).

Psychology, and mental health care in particular, has recognized the value and potential of AI, particularly AI-based conversational agents (assisting with diagnosis, consultations, and delivering treatment options) and AI-based decision support systems that can accurately diagnose mental disorders (Li et al., 2023; Tutun et al., 2023).

Artificial Intelligence psychology and AI-based psychology apps are becoming increasingly crucial for psychologists, therapists, and counselors to transform mental health care and promote mental wellness in their clients (Hua et al., 2024; Minerva & Giubilini, 2023).

More broadly, they reflect the ongoing integration of technology into mental health care — an evolution already evident in practices like biofeedback and neurofeedback — while introducing new, more advanced tools to support care delivery.

How can AI help mental health professionals?

While AI can support psychologists in recording data, managing record keeping, and triggering automatic follow-up actions to free up valuable time, it can also provide tailored, automatic therapy, psychological expertise and guidance, and virtual worlds and games where trauma, anxieties, and phobias can be revisited (Li et al., 2023; Minerva & Giubilini, 2023; Tutun et al., 2023; Ford et al., 2023).

AI as therapist

Conversational AI agents (CAs), or chatbots, are proving valuable in mental health care. A 2023 meta-review found that “AI-based CAs significantly reduce symptoms of depression and distress” (Li et al., 2023, p. 1).

Recent advances in AI have enabled chatbots to move away from the constraints of rule-based conversations with clients. Natural language processing, deep learning, and generative AI (such as ChatGPT and Gemini) enable more complex issues to be understood and more personalized advice and treatment to be offered (Li et al., 2023).

With the introduction and availability of such tools, it is becoming much easier for psychologists and mental health professionals to create their own AI models for either interacting with clients directly or providing support for diagnosis and treatment (Lau, 2023; Raile, 2024).

However, it is essential to note that reliance on AI tools for therapy carries risks, especially for more vulnerable clients. The results of interactions with CAs can be unpredictable, and responses could potentially have negative consequences.

Ultimately, mental health professionals must maintain oversight, become familiar with AI ethics, and remain accountable for all treatments while ensuring systems are trained on high-quality, unbiased data (Li et al., 2023; Minerva & Giubilini, 2023).

In addition to the risks associated with AI-assisted therapy, practitioners must recognize that AI is producing novel forms of distress within the general population.

The threat of job displacement and the uncertainty it creates around identity and meaning have contributed to rising levels of AI anxiety and existential anxiety among clients who may present with these concerns in session.

AI as an expert system

Expert systems were one of the first uses for AI within the medical field. While not everyone agrees that early expert systems qualify as AI, they undoubtedly assist decision-making by combining knowledge and expertise from professionals (Luxton, 2014).

Through enhancements such as adding speech recognition and natural language processing to expert systems, it is not difficult to imagine technology like Siri, Alexa, or Google Assistant offering therapist-like sessions or specialist advice at relatively low costs and without clients having to leave their homes (Tutun et al., 2023).

AI systems, sometimes referred to as decision support systems (DSS), provide other such opportunities, combining their body of expertise with personal records to monitor health conditions and spot potential contraindications for medical treatments (Tutun et al., 2023).

A 2023 review of an AI DSS found it highly successful at diagnosing mental health disorders based on answers to only 28 mental health questions without human input. They concluded that such AI systems could successfully “replace traditional paper-based examinations, decreasing the possibility of missing data and significantly reducing cost and time needed by patients and mental health professionals” (Tutun et al., 2023, p. 1272).

Virtual worlds

Computer-generated simulated worlds, known as virtual reality (VR), offer safe, cost-effective environments for patients to explore their issues, boost their mood, and even manage physical and mental pain. Through immersion, the environment can be made more real for the individual, tailoring circumstances and dialing stressors up or down (Wade, 2023).

Virtual reality therapy can be a safe way to deal with post-traumatic stress disorder, as discussed in our linked article.

While similar, augmented reality overlays the potential flexibility of VR onto the actual world. It uses the readily available processing power of tablets, smartphones, and AI to safely connect individuals with the source of their anxiety or personal coaches.

Psychiatry has been successful in using the metaverse — “a three-dimensional digital social platform accessed via augmented, virtual, and mixed reality” (Ford et al., 2023, p. 1) — in student education, measuring patient psychological responses to environmental cues and offering tailored treatments in controlled environments.

Computer games

Computer games have increased engagement among reluctant mental health patients and encouraged treatment adherence (Jordan, 2023; Abd-Alrazaq et al., 2022).

By providing a discreet and gamified option for patients, AI-enhanced games can side-step the stigma associated with mental health treatment and provide realistic situations tailored to patients’ needs.

Going forward, such AI-driven serious games are expected to increasingly form part of mental health treatment and preventive interventions (Jordan, 2023; Abd-Alrazaq et al., 2022).

The online computer game Second Life has been successfully trialed as a vehicle for virtual coaching and directed gameplay to enable the patient to practice new skills (Linden Research, 2013; Luxton, 2014).

More recently, a 2022 review confirmed the value and positive impact of video games, such as the 3D fantasy world game SPARX, on patients with depressive symptoms (Ruiz et al., 2022).

5 Examples of AI Use in Psychology

There are a growing number of tools and technologies with a significant impact on artificial intelligence in psychology and mental health treatment, including the following (Hua et al., 2024).

Detection and Computational Analysis of Psychological Signals

The Detection and Computational Analysis of Psychological Signals (2024) project uses machine learning, computer vision, and natural language processing to analyze language, physical gestures, and social signals to identify cues for human distress.

This ground-breaking technology assesses soldiers returning from combat and recognizes those who require further mental health support. In the future, it will combine data captured during face-to-face interviews with information on sleeping, eating, and online behaviors for a complete patient view (Defense Applied Research Projects Agency, 2013; USC Institute of Creative Technologies, 2024).

To learn more, check out our dedicated article on AI stress-detection  and stress-reduction tools.

Computer Science and Artificial Intelligence Laboratory

The Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology has successfully used AI to analyze digital video and identify subtle changes to an individual’s pulse rate and blood flow, undetectable to the human eye (Hardesty, 2012).

“Physiological data collected during psychotherapy opens valuable new avenues for understanding therapy processes and mechanisms that are not possible with self-report and observational measures” (Deits-Lebehn et al., 2020, p. 488).

Watson Health

Watson Health, IBM’s AI-enabled analysis tool, is now commercially available and comes loaded with medical literature to serve as both consultant and medical expert.

The incredible aim of this AI is to bring together data, technology, and expertise to stand in for or supplement professional physical and mental health care, performing diagnoses and suggesting treatments (IBM, 2020).

However, as with other AI-based psychological tools, several risks must be considered when using Watson, based on (Rana & Singh, 2023):

• Limited data on specific mental health disorders available for training AI models, potentially leading to inaccurate and unreliable diagnoses
• Lack of transparency and accountability about the potential use of AI in mental health
• Potential for algorithmic bias that could influence treatments

Despite the possible limitations of AI, Watson Health is proving valuable in understanding the incidence, prevalence, and risk factors associated with mental health disorders (Young et al., 2023).

Mental health expert systems

Mental Health Diagnostic Expert System uses advanced AI technology to encode expert knowledge of mental health disorders, which it then uses to understand patients’ needs and agree on treatment plans that suit their budgets and are appropriate alongside other health conditions (Masri & Mat Jani, 2012).

More recently, the Network Pattern Recognition AI algorithm has been trained to diagnose patients’ mental health needs based on answers to a series of questions. It has proven successful in supporting mental health professionals as they make evidence-based treatment decisions and guide policymakers on digital mental health implementations (Tutun et al., 2023).

RP-VITA

The US Food and Drug Administration has approved the RP-VITA robot to provide remote communication between health care providers and patients. Powered by AI, it monitors patients’ wellbeing remotely while accessing their medical records.

The multidisciplinary system supports psychological, neurological, cardiovascular, and critical care assessments and examinations (InTouch Health, 2020).

How to Use AI for Psychological Testing

AI technology offers valuable tools for therapy and research, combining techniques such as data mining (generating new information from deep analysis of large quantities of data) and expert analysis. It opens up the potential to diagnose existing and potential problems and test and confirm predictions and treatments (de Mello & de Souza, 2019; Kjell et al., 2023).

When used to understand the data from 707 patients with suicidal tendencies in Greater Santiago, Chile, the AI identified a series of factors associated with suicidal ideation and behavior. The findings led to a series of preventive interventions for at-risk individuals that reduced the likelihood of suicide and reinforced “psychological wellbeing, feelings of self-worth, and reasons for living” (Morales et al., 2017, p. 2).

Appropriate AI technology provides the means to piece together fragmented information, build mental models, test their validity, and suggest treatments (de Mello & de Souza, 2019).

Generative AI moves mental health assessment away from the limitations of rating scales and toward the natural language of the patient (Kjell et al., 2023).

Using Artificial Intelligence in Cognitive Psychology

Cognitive psychology attempts to understand cognition’s complexity through research, testing, and building models of how the human mind handles and processes complex information during attention, memory, and perception (Zivony, 2019).

While computational modeling and AI have subtle differences, they are both valuable approaches for understanding the nature of intelligent thinking and providing insights into the growing field of cognitive psychology.

Although the brain may be described as a highly complex neural network and connectionist models have successfully modeled human-like processes (such as face recognition), the jury is still out regarding whether such models explain human cognition (Eysenck & Keane, 2015).

However, deep neural networks, inspired by cognitive psychology theories and methods, have had some success in explaining how children learn labels for objects and offer a great example of the benefits of combining knowledge and expertise from multiple disciplines (Ritter et al., 2017).

Cognitive psychology and connectionism have therefore played a vital role in ongoing algorithmic developments that led to advances in generative AI (AI Ed Researcher, 2023).

Top 4 AI-Based Psychology Apps

While the use of artificial intelligence in psychology remains a relatively new field, the ubiquity of smartphone technology means that many of us have hardware within easy reach to run the increasing number of AI-inspired psychology apps.

A sample is given below.

Mindspa

Mindspa is a self-therapy app offering science-based tools to help users overcome anxiety, relationship difficulties, low self-esteem, and more.

Designed by expert psychologists specializing in CBT, EMDR, Gestalt, and mindfulness, its free features include a therapeutic diary, emergency chatbot, and hundreds of coping tools. Paid programs offer 7–40 lessons each and are available in multiple languages.

Find the app in the Google Play Store.
Find the app in the Apple App Store.

WYSA

WYSA is a research-validated chatbot supporting individuals experiencing anxiety, depression, and stress.

It begins by asking the user what challenges they face then uses AI to talk them through their moods, assess energy levels, and organize their thoughts.

Find the app in the Google Play Store.
Find the app in the Apple App Store.

Youper

Youper provides a personalized emotional health assistant to help treat stress, anxiety, and depression and has been validated by researchers at Stanford University.

The app uses techniques from several therapies, including CBT and mindfulness, to monitor and improve mental health through a series of brief conversations.

Find the app in the Google Play Store.
Find the app in the Apple App Store.

Replika

Replika is an AI-powered chatbot that provides an emotional connection and virtual friendship to support people going through depression, anxiety, or troublesome times.

Find the app in the Google Play Store.
Find the app in the Apple App Store.

4 Artificial Intelligence and Psychology Degrees

Many face-to-face and in-person degrees teach the latest in either artificial intelligence or psychology; however, few integrate the two disciplines.

The following programs are ones we have identified that include elements of both.

Cognitive science BSc, Carnegie Mellon University, Pennsylvania, United States

This interdisciplinary degree combines artificial intelligence, psychology, neuroscience, and philosophy with the shared goal of understanding intelligence.

Cognitive science in education, MA and PhD, Columbia University, New York, United States

Students explore the cognitive mechanisms that underpin learning and thinking at a master’s and doctorate level and learn the skills required to improve educational practices and develop innovative methods.

Computational neuroscience, cognition, and AI, MSc, University of Nottingham, United Kingdom

This interdisciplinary program combines aspects of psychology, mathematics, and computer science to better understand human and artificial intelligence in psychology.

Artificial intelligence, master’s degree, Vrije Universiteit Amsterdam, The Netherlands

This master’s degree explores hybrid intelligence, where AI systems and humans collaborate. It strongly focuses on natural language processing techniques and reasoning for health applications.

A Take-Home Message

AI-assisted therapy offers a promising approach to support and sometimes replace selected practices involved in psychological research and mental health assessment and treatment (Fiske et al., 2019; Ford et al., 2023).

The arrival of generative AI (including ChatGPT) and subsequent technological advances have opened the eyes of mental health practitioners and psychological researchers to using advanced models to support the diagnosis and treatment of their clients and save time and resources (Ford et al., 2023; Minerva & Giubilini, 2023).

The technology has the potential to provide new types of treatment, including virtual and augmented reality and games, and the ability to engage with populations that are difficult to reach or motivate.

Such innovative approaches can also free psychologists and mental health professionals’ time and resources to focus on urgent or more specialist care (Hamdoun et al., 2023).

However, there are inevitable ethical issues. At present, there is limited guidance on the development of such tools or how to integrate them with the work of health professionals, their existing technology and tools, and regulatory frameworks (Minerva & Giubilini, 2023).

Other considerations when implementing AI solutions include understanding and agreeing on the level of human supervision required before, during, and after engaging with clients. At a minimum, assessment or intervention must respect and protect patient confidentiality and autonomy.

Yet, AI offers a practical approach to researching and treating mental health on a large scale, along with providing greater knowledge and understanding of the efficacy of treatments (Minerva & Giubilini, 2023).

We hope you enjoyed reading this article. Don’t forget to download our five positive psychology tools for free.

ED: Updated February 2024