Artificial Intelligence and Social Work


Social Work and related professions have the potential to experience rapid change and growth in the future as technology advances and the population changes. This is especially true with artificial intelligence.

Artificial Intelligence (AI) describes a range of technologies that allow machines or computers to make decisions that are normally made by human beings.

Emotional Support Technology

Perhaps the first attempt at emotional support using a computer was the ELIZA software created by Joseph Weizenbaum in 1964. Through pattern matching the software was able to respond with empathy statements and open-ended questions to keep the conversation going.

Modern options include XiaoIce (Zhao, et. al., 2018). As the authors describe,

The primary design goal of XiaoIce is to be an AI companion with which users form long-term, emotional connections. Being able to establish such long-term relationships with human users as an open-domain social chatbot distinguishes XiaoIce from not only early social chatbots but also other recently developed conversational AI personal assistants such as Apple Siri, Amazon Alexa, Google Assistant and Microsoft Cortana.

Another example includes Replika, which recently released its source code as open-source. As these technologies get more advanced they may play a more important role in our emotional support options for people who are struggling with loneliness.

Digital Psychotherapy

Digital psychotherapy options include online and electronic therapy options. One example is Electronic CBT for Insomnia (Espie, et. al., 2018) which was a rich-media web application that participants used to receive cognitive behavioral therapy via the internet, and Whiteside et. al. (2014) which studied the program Thrive:

Thrive is similar to programs used in successful trials of Internet-delivered CBT; the Thrive interface is interactive and its curriculum is adaptive to patient input. […] Thrive includes three CBT-based modules that are based on behavioral activation, cognitive restructuring, and social skills training techniques

While these programs are currently not utilizing much artificial intelligence, in the future we may see them adapting to the client’s progress and altering the curriculum in ways that will increase efficacy or completion rates.

As CBT programs become more researched and advance we should see more of these appearing. As Whiteside notes, these programs are significantly cheaper to deliver (using a fully automated or a paraprofessional “coach” model rather than delivering full therapy) and so may represent an increasingly common option for therapists.

Decision-Making Tools

Decision-making tools are potentially the most exciting use of technology and artificial intelligence. An example of where this technology has been helpful is in child protection work in England. (Pegg & McIntyre, 2018)

We may see AI being used in the future to help us integrate the hundreds of variables found in child protection assessments and files to increase our success rates and improve risk assessments. Certainly, we can’t replace humans in this incredibly careful work (just like in suicide risk assessment) but we can use these tools to augment our understanding of child protection and decrease the lag between learning things in research and applying them in practice.


Artificial intelligence has the potential to improve our lives by providing more emotional support to those who are lonely, providing digital psychotherapy and decision-support tools to improve child protection and other social work fields.


Espie, C.A., Kyle, S.D., Williams, C., Ong, J.C., Douglas, N.J., Hames, P., Brown, J.S.L. (2012) JAMA Psychiatry. Retrieved from

Pegg, D. & McIntyre, N. (2018) Child abuse algorithms: from science fiction to cost-cutting reality. Retrieved from

Weizenbaum, Joseph (1976). Computer Power and Human Reason: From Judgment to Calculation. New York: W.H. Freeman and Company. pp. 2, 3, 6, 182, 189. ISBN 0-7167-0464-1.

Whiteside, U., Richards, J., Steinfeld, B., Simon, G., Caka, S., Tachibana, C., Stuckey, S., … Ludman, E. (2014). Online cognitive behavioral therapy for depressed primary care patients: a pilot feasibility project. The Permanente journal18(2), 21-7.

Zhou, L., Gao, J., Li, D. & Heung-Yeung, S. (2018) The Design and Implementation of XiaoIce, an Empathetic Social Chatbot. Journal of Human and Computer Interaction.

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Cognitive Behavioral Analysis System of Psychotherapy (CBASP)


CBASP is a form of psychotherapy first described in 1984 by James McCullough and expanded on in his full-length book Treatment for Chronic Depression: Cognitive Behavioral Analysis System of Psychotherapy (CBASP) published in 2000. Although its name sounds similar, it should not be confused with Cognitive Behavioural Therapy (CBT) or similar forms of therapy.

The goal of CBASP is to “teach the patient to focus on the consequences of behaviour, and to use problem solving to resolve interpersonal difficulties. (Driscoll, et. al., 2004, pg. 2)

A 2016 meta-review confirmed that CBASP is effective for the treatment of major depressive disorder, especially when combined with medication. (Negt, et. al., 2016), while a comparison of CBASP versus treatment-as-useful — other evidence-based therapies for depression — in Wiersma et. al. (2014) found that CBASP was at least as effective as the other treatments from 8 weeks up to 32 weeks but performed better by 52 weeks, suggesting it kept clients better, for longer.

Principles of CBASP

McCullough believes that depression is caused by “learned Pavlovian fears of interpersonal encounters, and maintained by a refractory pattern of Skinnerian interpersonal avoidance.” (McCullough, 2006) Essentially what this means is that clients develop a fear of relationships based on previous bad experiences that leads them to isolation and a disconnect from their environment.

CBASP involves the client completing paperwork called the Coping Survey Questionnaire (CSQ) in between each session. These CSQ forms are used to document stressful or challenging interactions with other people by exploring what happened, how the client reacted, and what the client wanted to happen. Then the CSQs are reviewed in therapy in a process known as Situational Analysis (SA).

According to Driscoll, et. al., (2004, pg. 4) analyzing one CSQ will likely take a full session in the beginning of treatment, but as a client masters the elements of the CSQ and the SA steps (described in more detail below) they will find themselves able to cover several CSQs in one session.

Coping Survey Questionnaire (CSQ) for use in CBASP

Five Steps of Situational Analysis

The five steps of Situational Analysis mirror the items on the CSQ.

Step 1. Describe the situation

In the first step, the client is expected to describe in 3 to 4 paragraphs a specific situation that occurred without editorializing or providing extraneous detail. The goal is for the therapist to be able to understand all of the interactions that occurred in that single instance.

Step 2. State interpretation

In step 2, the client provides their interpretations about what occurred during that conversation. Many times clients will make interpretations that are broad, based on situations that are very specific. For instance, a client who receives poor customer service from a cashier may state, “He wasn’t nice to me because I’m ugly.” Asking the client to provide two or three thoughts that occurred during the interaction, or asking the client what the situation meant to them in the moment may help spur the production of interpretations.

The most effective interpretations are those that lead to the desired outcome (DO), what the client wished had happened in that situation had it occurred again.

Step 3. Identify reactions

In step 3, the client records all of their own behaviours and reactions. These include voice tone, body language, pace, and other reactions the client may have had like walking away from the situation. This allows the client to identify avenues for changing behaviours to more easily reach the desired outcome.

Step 4. Explain the desired outcome (DO)

In step 4, the client explains the Desired Outcome (DO). The therapist can ask, “What were you trying to get out of this situation?” or “How did you want things to go” in order to spur this part of the conversation. One DO should be produced for each CSQ that is completed. These DOs should be SMART (specific, measurable, attainable, realistic and timely.)

One important element related to DOs is that they have to involve the client themselves. A DO can’t involve change in another person because we don’t have control over that person. What the client does have control over is their own reactions and responses.

Step 5. Illustrate the actual outcome (AO)

The actual outcome (AO) is perhaps the easiest step, because this explores what the client actually got out of the experience. Usually this is a negative experience but it doesn’t have to be — a positive AO may be an opportunity for the client to identify what went right and how they can repeat this in the future.

After Situational Analysis

After the SA phase is complete, the client has explained the situation, what happened, how they reacted, what they wanted to happen, and how the situation ended. This is known as the elicitation phase. The next stage of the two-part process is the remediation phase.

In the remediation phase of CBASP, the interpretations and behaviours are looked at to figure out if they’re the most useful beliefs or effective responses to the situation. If they’re not (and many times they aren’t), more effective interpretations and behaviours are suggested in order to help the client better reach the DO.


Driscoll, K.A., Cukrowicz, K.C., Reardon, M.L. & Joiner, T.E. (2004) Simple Treatments for Complex Problems: A Flexible Cognitive Behavior Analysis System Approach to Psychotherapy. Mahwah, N.J.: Lawrence Elbaum Publishers

McCullough, J. P. (1984). Cognitive-behavioral analysis system of psychotherapy: An interactional treatment approach for dysthymic disorder. Psychiatry: Journal For The Study Of Interpersonal Processes, 47(3), 234-250.

McCullough, J. P. (2000). Treatment for chronic depression: Cognitive behavioral analysis system of psychotherapy. New York, NY: Guilford.

McCullough, J. P. (2006). Treating chronic depression with disciplined personal involvement: Cognitive behavioral analysis system of psychotherapy (CBASP). New York, NY: Springer.

Negt, P., Brakemeier, E., Michalak, J., Winter, L., Bleich, S., & Kahl, K. G. (2016). The treatment of chronic depression with cognitive behavioral analysis system of psychotherapy: a systematic review and meta-analysis of randomized-controlled clinical trials. Brain And Behavior, (8), doi:10.1002/brb3.486

Wiersma, J.E., Van Schaik, D.J., Hoogendorn, A.W., Dekker, J.J., Van, H.L., Schoevers, R.A., Blom, M.B., Maas, K., Smit, J.H., McCullough, J.P., Beekman, A.T. & Van Oppen, P. (2014) The effectiveness of the cognitive behavioral analysis system of psychotherapy for chronic depression: a randomized controlled trial. Psychotherapy and Psychosomatics. 83(5): 263-9. doi: 10.1159/000360795

Cite this article as: MacDonald, D.K., (2016), "Cognitive Behavioral Analysis System of Psychotherapy (CBASP)," retrieved on July 23, 2019 from

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