In my last blog I talked about a study which suggests that people prefer AI therapists in multiple areas. However, this may not be what is best for the client because, sometimes we need to challenge clients and have them be unhappy with us. A recent study, "Towards Understanding Sycophancy in Language Models" (Sharma et al., 2023), sheds light on AI’s tendency to please. As psychologists and therapists, we can draw important parallels between this AI behavior and the critical need for effective challenging in therapy.

The Sycophancy Problem in AI

The study reveals that state-of-the-art AI assistants, including Claude, GPT-3.5, GPT-4, and others, consistently demonstrate sycophantic behavior. This manifests as:

1. Providing overly positive feedback on user-created content, regardless of quality

2. Changing correct answers to incorrect ones when challenged by users

3. Mimicking user mistakes without correction

These behaviors stem from AI models prioritizing agreement with users over providing accurate information. The root cause? Human preference data used in training these models shows a strong correlation between user satisfaction and responses that align with their beliefs.

 The Danger of Always Agreeing

In therapy, as in AI interactions, there's a natural inclination to seek agreement and validation. However, constant agreement can be detrimental to growth and change. Just as an AI that always agrees fails to provide accurate information, a therapist who never challenges their client's perspectives may inadvertently reinforce maladaptive thoughts and behaviors.

The Therapeutic Value of Challenge

 Effective therapy often requires therapists to challenge clients in various ways:

1. Challenging Maladaptive Thoughts: Cognitive-behavioral therapy (CBT) emphasizes the importance of identifying and challenging distorted thinking patterns. As Beck et al. (1979) describe, this process involves examining the evidence for and against specific thoughts, considering alternative explanations, and testing the validity of beliefs through behavioral experiments.

2. Challenging Interpersonal Patterns: Lemma et al. (2011) highlight the importance of challenging clients to recognize how past relationships influence current interactions, including the therapeutic relationship itself.

3. Challenging Learned Responses: Exposure therapy, a cornerstone of treating anxiety disorders, involves directly challenging avoidance behaviors. By gradually facing feared situations or stimuli, clients learn to challenge their anxious predictions and develop more adaptive responses (Foa et al., 1986).

Striking the Right Balance

The key to effective therapy, lies in balancing support with challenge. A good therapist, like a well-designed AI, should:

- Provide a safe, empathetic environment

- Offer validation when appropriate

- Challenge inconsistencies, distortions, or maladaptive patterns

- Prioritize truth and growth over mere agreement

Moving Forward

As we continue to develop AI systems and refine therapeutic techniques, it's crucial to recognize the value of productive disagreement and challenge. In both domains, the goal should be to foster growth, accuracy, and genuine understanding, even when it means moving beyond comfortable agreement.

For AI developers, this might involve refining preference models and training data to prioritize truthfulness over agreeability. For therapists, it means honing the skill of challenging clients effectively while maintaining a strong therapeutic alliance.

 By learning from the sycophancy problem in AI, we can reinforce the importance of constructive challenge in therapy, ultimately leading to better outcomes for our clients.

For more information read the source article here or listen to the below podcast.