Artificial intelligence in psychology: 9 examples and applications (2023)

The first chatbotELISA, was developed in 1966 by Joseph Weizenbaum of MIT.

Eliza Doolittle's name from the play by George Bernard ShawPygmalion, this first conversational software imitated a psychotherapist (Weizenbaum, 1976; Mullins, 2005).

Although her intelligence was limited and she simply rephrased patients' sentences into questions, Eliza proved to be incredibly persuasive.

His most famous screenplay, DOCTOR, successfully impersonates renowned psychologist Carl Rogers (ELIZA, undated).

Patient:I am unhappy
ELISA:Can you explain what made you unhappy?

Back then, it was the next step in a much longer journey toward intelligent software and artificial intelligence (AI).

This article examines recent AI developments in psychology and its future potential.

Before we go any further, we thought you might like this.Download our three positive psychology exercises for free. These science-based exercises examine the fundamentals of positive psychology, including strengths, values, and self-compassion, giving you the tools to improve the well-being of your clients, students, or employees.

The role of artificial intelligence in psychology

The term AI is widely used to describe both “technology designed to perform activities that normally require human intelligence” and the multidisciplinary field of science related to understanding and developing that technology (Luxton, 2014).

From robots to software distributed across networks, AI is a commonly used term today. And while it can mean different levels of complexity and power depending on the context and the commentator, it emulates complex human behavior or specialized intelligent functions.

More importantly, the AI ​​can learn without being explicitly told how to do it.

Psychology, specifically mental health, is one of the newer focus areas for AI. As AI expands its reach, it becomes increasingly important for psychologists, therapists, and counselors to understand the existing capacity and future potential of technology to transform mental health.

How can AI help psychiatrists?

Luxton (2014) says that AI can simulate a practitioner with capabilities beyond their human counterpart.

In fact, the following examples of advanced technology go beyond our human senses to assess patients (Luxton, 2014):

• infrared imagedetect temperature changes
• facial recognitionto confirm the identity of a patient
• optical sensorAnalyze facial expressions and winks.
• vocal analysisnotice subtle differences in language features
• Odor analysis (smell)recognize poisoning

While the AI ​​can conduct therapy sessions,E-therapySessions and reviews autonomously, you can also help human professionals before, during or after sessions.

Physical assessments such as B. increases in heart rate or changes in temperature in response to difficult questions can provide valuable and insightful additional data to the clinician.

In addition, data logging, record management, and triggering of automatic follow-up actions would free up valuable time for the human professional.

AI as an expert system

expert systemsthey were one of the first applications of AI in the field of medicine. While not everyone agrees that expert systems count as AI, they certainly support decision making by combining the knowledge and experience of professionals.

Although these systems have been around for several decades, their design has moved from predominantly rule-based logic to data mining and data mining-based decision making.fuzzy logic– Term used by cognitive scientists to deal with partial truths (Luxton, 2014).

With enhancements like adding speech recognition and natural language processing to expert systems, it's not hard to imagine technologies like Siri, Alexa, or Google Assistant offering therapist sessions or expert advice at relatively low cost, without requiring clients to leave home .

AI offers other such possibilities. Combining your wealth of experience with personal records can monitor health status and identify potential contraindications to medical treatments.

In addition, AI-enabled clinical support systems offer greater capacity, as they can process a larger volume of highly complex data than their human equivalents could, making them available anywhere around the clock. The burden on time-constrained mental health resources can be significantly reduced, and AI can bring more targeted engagement to those who need it most, when they need it most (Luxton, 2014).

virtual worlds

computer generated simulated worlds known asvirtual reality(VR) provide a safe and cost-effective environment for patients to explore their problems. Immersion allows the environment to become more real to the individual, adapting to circumstances and turning stressors on or off.

Virtual companions, including digital pets, also promote well-being while managing loneliness in accessible settings (Luxton, 2014).

virtual reality therapyIt can be a safe way to deal with PTSD and is discussed in our linked article.

expanded realityoverlaps the potential flexibility of virtual reality with the real world. It uses the readily available computing power of tablets and smartphones to securely connect people with the source of their anxiety or personal trainers.

How clients can heal by facing their fears is also mentioned in our article on exposure therapy.

computer games

Computer games successfully increased the engagement of reluctant patients and promoted adherence to therapy. By providing a playful and discreet option for patients, AI-powered games can avoid the stigma associated with mental illness treatment and provide realistic situations tailored to the needs of patients.

online computer gameSecond lifewas successfully tested as a vehicle forvirtual trainingand directed play to allow the patient to practice new skills (Linden Research, 2013; Luxton, 2014).

5 examples of the use of AI in psychology

Artificial intelligence technology that will supplement or even replace therapists, counselors, or other mental health professionals is not in the realm of science fiction or in the near future; is available now.

Recognition and computer analysis of psychological signals

oRecognition and computer analysis of psychological signalsThe project uses machine learning, computer vision, and natural language processing to analyze language, physical gestures, and social cues to detect signs of human distress.

This innovative technology screens soldiers returning from combat and identifies those who need further mental health support. In the future, it will combine data collected from face-to-face interviews with information on sleep, eating, and online behavior to provide a complete picture of the patient (Defense Applied Research Projects Agency, 2013).

Computer and artificial intelligence laboratory

oComputer and artificial intelligence laboratoryat the Massachusetts Institute of Technology has successfully used AI to analyze digital video and identify subtle changes in a person's pulse rate and blood flow that are imperceptible to the human eye.

While it is extremely valuable during therapy sessions for uncovering nonverbal cues, it can also monitor the breathing of trauma patients or endangered babies in hospitals (Hardesty, 2012).

watson health

watson health, IBM's AI-enabled analysis tool, is now commercially available and comes with medical literature to serve as a consultant and medical expert.

The incredible objective of this AI is to gather data, technology and knowledge to replace or complement physical and mental health professionals, make diagnoses and propose treatments (IBM, 2020).

RP-VITA

oRP-VITAThe robot has been approved by the US Food and Drug Administration for remote communication between healthcare professionals and patients. Remotely monitor the well-being of the patient while accessing their medical records.

The system is multidisciplinary and provides support for psychological, neurological, cardiovascular, and intensive care evaluations and investigations (InTouch Health, 2020).

Expert system in mental health diagnosis

Expert system in mental health diagnosisuses advanced artificial intelligence technology to encode experience about mental health disorders, which is then used to diagnose and suggest treatment.

AI uses a combination of fuzzy and rule-based logic to understand patients' needs and agree treatment plans that fit their budget and are appropriate alongside other health conditions (Masri & Mat Jani, 2012).

Combining the benefits of psychological expertise with AI-enabled technology has a positive impact on patient care and health. With the added benefits of being cheap and remotely available, it's likely to evolve quickly.

How to use AI for psychological testing

De Mello and de Souza (2019) explored the potential of AI tools to assist in the collection, analysis, review, and evaluation of mental health data.

AI technology offers valuable tools for therapy, combining techniques such as data mining (creation of new information from the deep analysis of large amounts of data) and expert analysis. AI unlocks the potential to diagnose existing and potential problems, test and confirm predictions and treatments.

By analyzing data from 707 suicidal patients in Greater Santiago, Chile, the AI ​​identified a number of factors associated with suicidal thoughts and behaviors.

The findings led to a variety of preventive interventions for people at risk that reduced the risk of suicide and improved "mental well-being, self-esteem, and reasons for living" (Morales et al., 2017).

In 2017, Kravets, Poplavskaya, Lempert, Salnikova, and Medintseva developed a model using fuzzy logic to emulate psychiatric diagnoses. He successfully assessed patients and tested their mental health diagnoses based on incomplete knowledge.

The right AI technology offers the ability to reconstruct fragmented information, build mental models, test their validity, and suggest treatments (de Mello & de Souza, 2019).

Use of artificial intelligence in cognitive psychology

cognitive psychologyseeks to understand the complexity of cognition through research, testing, and modeling of how the human mind handles and processes complex information during attention, memory, and perception (Zivony, 2019).

AI and cognitive psychology have similar goals: understanding the nature of intelligent behavior, and the former tries to build such processes using advanced technology.

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

computer modelinginvolves “programming computers to model or mimic aspects of human cognitive functioning” (Eysenck & Keane, 2015). The underlying processes of artificial intelligence, on the other hand, do not normally resemble the mechanisms of the human brain.

Rather than trying to create computational models that help us understand human intelligence, the AI ​​designer's goal is to produce a result that appears intelligent. Such processes need not be functionally similar to those of a human being.

However, there is a specific model that seems to bridge the gap between the two approaches.

connectionismwas originally inspired by the network of neurons that exist in the brain. “Connectionist models typically consist of interconnected networks of simple learning units” and model cognition without explicit rules (Eysenck & Keane, 2015).

Although the brain can be described as a highly complex neural network and connectionist models have successfully modeled certain human processes (such as facial recognition), it is still unclear whether these models explain human cognition.

However, deep neural networks, inspired by theories and methods of cognitive psychology, have had some success in explaining how children learn to name objects and provide a great example of the benefits of combining knowledge and experience from different disciplines ( Ritter, Barrett, Santoro, & Botwinick, 2017).

The 4 Best AI-Powered Psychology Apps

While the use of AI in psychology is still a relatively new field, the ubiquity of smartphone technology means that many of us have hardware available to run the growing number of AI-inspired psychology apps.

Here is an example:

Wobot

Woebot, winner of the Google Play Award 2019, encourages the user to think through situations using tools inspired by Cognitive Behavioral Therapy (CBT).

The mood tracker shows the positive changes that have been made over days and weeks.

Find the application inGoogle app store.
Find the application inApple App Store.

youper

Youper offers a personalized emotional health assistant to treat stress, anxiety and depression.

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

Find the application inGoogle app store.
Find the application inApple App Store.

Responder

Replica is an AI-powered chatbot that offers emotional connections and virtual friendships to help people going through depression, anxiety, or difficult times.

Find the application inGoogle app store.
Find the application inApple App Store.

tess

Tess is a web-based mental health chatbot that uses AI to provide the user with wellness coping strategies. Build resilience through text-based conversations via Facebook Messenger, SMS, and web browsers instead of an app.

Website accessmust be bought.

5 degrees in Artificial Intelligence and Psychology

Around the world, many degrees teach the latest in AI and psychology; however, few integrate both disciplines.

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

• Computational Neuroscience, Cognition and AI MSc, University of Nottingham, UK. School of Psychology.
  This is an interdisciplinary program that combines aspects of psychology, mathematics, and computer science.
• Master in Digital Health, Bournemouth University, UK. Faculty of science and technology.
  This program teaches students to personalize and promote digital health through chatbots, wearable technology, and the medical Internet of Things.
• Artificial Intelligence: Master of Cognitive Sciences, VU University of Amsterdam, The Netherlands. Science Faculty.
  This Master uses a multidisciplinary approach to learn about the mind and cognition. Researchers and collaborators come from a variety of backgrounds, including psychology, AI, mathematics, philosophy, and neuroscience.
• Bachelor of Cognitive Sciences, Carnegie Mellon University, Pennsylvania, United States.
  This interdisciplinary degree combines psychology, AI, neuroscience, and philosophy with the common goal of understanding intelligence.
• cognitive science in education, BSc, MA and PhD, Columbia University, New York, USA.
  These programs teach undergraduate, graduate, and doctoral students to explore the cognitive mechanisms that support learning and thinking. Its objective is to improve educational practices and develop innovative methods based on new technologies.

Relevant Resources from PositivePsychology.com

We have many tools and worksheets to help users gain greater awareness and understanding of emotions, intelligence, and mindset. Use them to identify and develop your own talents or those of your clients.

• watch your thoughtsto recognize what kind of faulty thinking is triggered. Faulty thinking styles can derail thought processes. Identify your thinking style and consider whether or not it is helpful.
• If you're looking for more scientific ways to help others improve their well-being, this subscription collection includes17 Validated Positive Psychology Tools for Professionals. Use them to help others thrive and prosper.

A message to take away

AI offers a promising approach to support and sometimes replace selected mental health assessment and treatment practices (Fiske, Henningsen, & Buyx, 2019).

The technology has the potential to deliver new types of treatment (including gaming, virtual and augmented reality) and engage hard-to-reach or hard-to-interact populations.

These innovative approaches can also free up time and resources for therapists and mental health professionals to focus on urgent or more specialized care (Fiske et al., 2019).

However, there are unavoidable ethical problems. Currently, there is limited guidance on how to develop such tools or how to integrate them into the work of healthcare professionals, their existing technologies and tools, and regulatory frameworks.

Other considerations when implementing AI solutions include understanding and agreeing on the amount of human supervision needed before, during, and after customer interactions. At a minimum, the assessment or intervention must respect and protect the confidentiality and autonomy of the patient.

However, if the risks of accidental or intentional abuse and ethical concerns are successfully managed, AI offers a practical approach to addressing mental health on a large scale. It also offers the opportunity to collect and analyze vast amounts of data, with the potential to increase knowledge and understanding of mental health and the efficacy of treatments (Fiske et al., 2019).

We hope you have enjoyed reading this article. I did not forget itDownload our three positive psychology exercises for free.