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Reflex AI: Insights from six years of ethical AI in mental health

ReflexAI stands out in the technology community with over six years of specialized experience deploying generative AI tools within mental health settings. Founded by former leaders of The Trevor Project, the ReflexAI team pioneered the Crisis Contact Simulator in 2019, an innovative tool providing dynamic, AI-powered roleplays for training crisis responders. 

In 2022, cofounders Sam Dorison and John Callery-Coyne launched ReflexAI, to bring innovative training and quality assurance tools to mental health organizations across the country. The company supports large organizations including the Department of Veterans Affairs, as well as local innovators like FirstLink in North Dakota. This year, ReflexAI’s groundbreaking work earned recognition as Fast Company’s “World Changing Idea” in Data & AI.

In 2024, Hopelab joined ReflexAI as part of its investor community. Hopelab is dedicated to collaborating with organizations that harness technology to uplift young people, particularly in the LGBTQ+ and BIPOC communities. Hopelab’s partnership with ReflexAI stems from a shared commitment to creating meaningful, technology-driven outcomes, with a clear vision to expand impact over time. 

Recently, Hopelab’s Head of Research, Dr. Amy Green, and ReflexAI’s CEO, Sam Dorison, engaged in a thought-provoking discussion on the future of AI in mental health. They explored the role of AI in driving innovations grounded in clinical best practices.

Watch the full interview below.

The following conversation contains paraphrased highlights and has been edited for clarity.

  1. Importance of community voices

The discussion started on the critical topic of recognizing that individuals seeking mental health support are multidimensional and that mental health organizations should invest heavily in deeply understanding the communities they seek to serve.

Amy Green reflected on their shared experience at The Trevor Project, where the annual national survey included 25,000+ participants. “If we look at this community of LGBTQ young people as a monolith, then we miss different needs and experiences, and it is really critical that Trevor counselors are able to understand those differences to really tap into what those young people are needing and experiencing.”

Sam Dorison also emphasized ReflexAI’s work in the Veteran community. As part of this focus, ReflexAI engaged with over 500 Veterans across surveys, focus groups, and 1:1 interviews. The best practice of utilizing multiple modalities is critical because different stakeholders may engage more deeply with some modalities than others. 

  1. Nuanced personas

A major challenge in mental health training is offering realistic, diverse practice scenarios. An effective set of roleplays must reflect the wide range of complexities that mental health professionals face in their daily work. For example, participants should be exposed to varied communication styles, including the different sentence structures and terminology used by individuals of different ages, backgrounds, and experiences.

Another essential aspect of roleplays is simulating the emotional dynamics of an interaction. Whether practice occurs with a trainer or a simulation, these scenarios should reflect different patterns of opening up. Does the person begin the conversation openly or are they more hesitant? How do they react to empathy? What happens when they’re asked questions that could be perceived as judgmental? ReflexAI’s simulations are built to capture these nuances, creating a layered and realistic conversational experience.

Additionally, Sam Dorison emphasized the importance of helping trainees navigate nuanced emotions in their mental health roles. “There’s a big difference between someone being angry versus frustrated, or scared versus uncertain. Capturing those emotional subtleties in simulations is crucial to effective training.”

Amy Green echoed this sentiment, drawing from her experience as a roleplay facilitator in mental health training. “It’s difficult to fully tap into that emotional spectrum when you’re not actively experiencing those feelings. That’s where technology, like AI, can play a powerful role in recreating those nuances and enhancing the learning experience.”

  1. Critical skills within adult learning

In mental health support, research highlights the significance of common factors, often referred to as non-specific factors, which are critical in building rapport. These include skills such as active listening, complex reflection, validation, and the use of open-ended questions. A successful training program provides ample opportunities to practice these essential skills within realistic and nuanced scenarios. Meanwhile, an effective quality assurance program regularly assesses these abilities, offering constructive feedback at frequent intervals to promote continuous improvement.

Best practices in adult learning are directly applicable to mental health training. First, feedback should be immediate and actionable. Second, it should always balance both strengths and areas for growth. Reflecting on ReflexAI’s approach, Sam Dorison noted, “The moment a simulation ends, participants receive a feedback card covering multiple dimensions like protocol adherence, risk assessment, empathy, openness, and responsiveness. This leads to a much faster learning process, one that is truly focused on growth.”

Amy Green also touched on the shared experience of training among mental health practitioners. “We’ve all been in training rooms, and there’s always a certain level of anxiety. But when participants feel prepared – when they’ve practiced in a variety of contexts – they gain a sense of competence and confidence. It’s powerful not just for the training process but for the individuals taking on these roles. They walk in ready, feeling like they’ve done this before.”

  1. Ethical AI

Many organizations aspire to develop ethical AI tools but often struggle to achieve this in practice. Both ReflexAI and Hopelab have created robust frameworks that address priority areas such as data privacy, bias and equity in data sets, and transparency around how and where AI is deployed.

Amy Green discussed Hopelab’s strong commitment to ethical AI, highlighting the organization’s thought leadership and collaborative partnerships. The approach emphasizes integrating ethics throughout the entire product lifecycle, starting from the initial concept, even before development begins, and continuing through to ongoing iteration after the product is scaled. This holistic view ensures that ethics are embedded at every stage.

There are also practical ways to incorporate AI ethics across many organizations. At ReflexAI, for example, every team member undergoes AI ethics training. As Sam Dorison explained, “We believe everyone has a part to play.” This inclusive approach helps ensure that ethical considerations remain a priority across all functions and decisions.

  1. The moral case for technology in mental health

Amy Green shared a recent conversation with an ethicist that impacted her view on incorporating new technology. It can be easy to focus on the risks of using new technology, but it is also essential to consider the downsides of not using new tools. “Take ReflexAI as an example. What is the ethical implication of not allowing for greater training of counselors. You’re capped at a certain level when you think of things like turnover and trainers.”

There is also an important point that the mental health space – and the teams doing life-changing work every day – deserve access to the best tools. Sam Dorison highlighted the role of Hopelab in the years ahead. “The vision of Hopelab of innovation to serve communities really resonates. That’s why we started ReflexAI. And Hopelab has brought that to the mental health space in a really compelling way.”


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