Artificial Intelligence (AI) such as Large Language Models, (LLMs) and Machine Learning (ML) systems, are changing the way many of us live, work, and even care for our health. With the advancement of these novel technologies, a broad new horizon has opened, full of opportunities to leverage their capabilities.
With the advancement and increasing adoption of artificial intelligence, we may see the emergence of therapeutic interventions that leverage the power of machine learning in Applied Behavioral Analysis.
But — how can AI potentially help? Exactly what is machine learning, and, can other types of artificial intelligence play a role in therapeutic interventions? Parents of special needs children may be particularly interested in emergent technologies that could impact treatment approaches in the near future.
To better understand, we’ll explore the evolving landscape of ABA (Applied Behavioral Analysis) and artificial intelligence, exploring how this infant technology may soon play an expanded role in helping secure positive outcomes through therapeutic intervention. Let’s dive in.
What is AI?
AI (Artificial Intelligence) refers to an emergent and growing subset of software and hardware systems that are able to provide meaningfully broader ranges of outputs than their traditional software counterparts, through means including reinforcement training, reasoning, learning, and language processing. The key distinction between AI and older digital systems is that AI is able to accomplish tasks that traditionally would require human logic, such as reasoning and learning.
Large Language Models are trained on large datasets that help them understand and generate language, while machine learning systems are trained to identify patterns too complex or nuanced for traditional software to identify, and visual generative AI systems are able to use training data of visual images to create new images.
How is AI Being Developed?
To better understand the landscape, it can be helpful to explore some of the artificial intelligence systems that are being developed. Large players in the tech industry, such as Microsoft, Google, and OpenAI, are developing public-use large language models — such as Google’s Bard, Microsoft’s Bing, and OpenAI’s ChatGPT.
These are widely in use already, and often applied to day-to-day tasks such as making schedules, drafting outlines, and planning. While these systems have made headlines, many other players are developing models for more specific uses. In the enterprise space, companies are leveraging machine learning to automate processes that at one time would have required more human oversight.
In the mental health field, where ethical considerations and empirical evidence of efficacy are paramount to success, we must take a careful approach to the use of these AI systems. This necessitates, in some cases, experimental exploration. Researchers have already begun to explore the promise of machine learning in applied behavioral analysis.
How Might AI Be Applied in ABA?
So, how can AI be applied in ABA? There are a few potential approaches to the implementation of AI in ABA and related therapeutic interventions. Let’s explore.
Machine Learning to Analyze Data
One of the primary potential applications for AI in ABA is using machine learning (ML) to review patient data and identify patterns. This might include reviewing patient data to predict the level of treatment intensity likely to help patients and even identifying areas that warrant more attention or intervention.
Machine Learning as a Diagnostic Tool
Machine Learning systems can be trained for use as diagnostic tools, learning, over time, to identify nuanced patterns that might point to certain diagnoses. In the domain of ABA, this may be used to identify patients for whom ABA may be a suitable path forward.
Machine Learning for Predictive Analytics
Machine learning can be used to make predictions. In the domain of ABA, this may be implemented to identify the likelihood of certain outcomes following therapeutic intervention, helping researchers and practitioners better determine which treatments may be best for certain patients.
AI-Powered Interactive Systems
Another use of AI in ABA and related therapeutic interventions may be creating interactive systems, such as chatbots that patients can interact with, providing a customizable source of interaction. These systems can be accessible around the clock, providing a means for practicing social interaction, learning, and developing communication skills. However, further research may be required in this area to ensure that chatbots don’t drive less desired outcomes, such as reinforcing maladaptive communication patterns.
Crucial Considerations – Ethics, Privacy, Human Oversight, and Efficacy
While the field of AI, broadly, stands to transform many of our approaches to mental health and ASD (Autism Spectrum Disorder), there are some crucial ethical considerations to take. As an infant technology, it’s important that we balance our approach and, often, add a high degree of human oversight, ensuring that these systems don’t make harmful mistakes.
Moreover, most forms of AI rely on immense sets of training data. It’s paramount that when developing and using these systems, the data is ethically sourced, and kept secure, and the privacy of all individuals involved is rigorously protected. This involves not only adhering to data protection regulations such as HIPAA, (The Health Insurance Portability and Accountability Act) but also ensuring ethical use and storage of private data. Similarly, patient data, when using these systems, must be carefully safeguarded.
Human oversight is critical at this moment, as AI technologies are still evolving. Practitioners and researchers must be involved in the development and implementation of these systems in order to lend their expertise, ensure the efficacy of interventions using these technologies, and exercise discretion with the best interest of their patients in mind. Rigorous testing and clinical trials will be a necessity to ensure that interventions leveraging new technologies are effective and safe.
The Bottom Line
While still in the early stages of development and implementation, AI (Artificial Intelligence), encompassing Machine Learning (ML) and Large Langue Models (LLM) stands to significantly transform the way we approach Applied Behavioral Analysis (ABA) when attempting to secure positive outcomes for patients with Autism Spectrum Disorder (ASD).
This may be through various approaches, including leveraging the analytic power of ML to identify diagnoses, or potential treatment plans and make predictions, as well as leveraging the capabilities of LLMs to create interactive, accessible systems that can be used to facilitate social learning and communication skill development, as well as other potential avenues.
Still, there are numerous ethical and practical considerations to take, such as ensuring human oversight, adhering to the highest scientific standards of research through rigorous testing and clinical trials, and carefully safeguarding personal data and ethically sourcing training data.
Ultimately, while there are a number of challenges and considerations to take into account, the use of AI in ABA may stand to change the way we approach therapeutic interventions for patients with ASD.