Videos O72p-rBb2bA
Evals-Driven Development for a Mental Health AI Coach — Akele Reed & Dave Revere, SonderMind
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Transcript
222 cues· 3,039 words· 16,969 chars
- 0:13 My name is Akela Reed and my colleague Dave Revere and I are going to talk to you today about engineering and mental health AI coach ethically and safely.
- 0:21 Just as a heads up, this talk does contain some sensitive content.
- 0:25 There will be mentions of suicide, self-harm and domestic violence.
- 0:29 Please take care.
- 0:31 We work at Sondermind and Sondermind is a mental health care company.
- 0:36 We match individuals with human therapists and psychiatrists all across the country.
- 0:42 We believe that everyone who needs care should have access to care, and we want that care to be of high quality.
- 0:50 Sondermine has served over a million people across the country, and we partner with some of the biggest names in mental health care, including Headspace, Aetna, Anthem, and more.
- 1:01 We focus on access and outcomes, which means we want people to get better faster, and that is our North Star, so to speak.
- 1:10 With that, I'd like to introduce you to Sonder.
- 1:12 This is our clinically grounded AI coach, which has been purpose-built for mental health.
- 1:19 I think the intro was very, very much appropriate.
- 1:23 Mental health support is amongst the top use cases for AI today.
- 1:29 General-purpose LLMs, however, are not built for mental health care, which has resulted in some very tragic events, unfortunately.
- 1:36 We've seen that on our news, in our feeds, in the courts.
- 1:40 And so this is to address that gap.
- 1:43 We want Sonder to be able to help provide mental health support to individuals who are seeking support but maybe aren't ready for therapy yet or between sessions.
- 1:54 Additionally, we understand that a human is the right next step for some people, and so Sonder can act as a front door to Sondermind's provider network when a human is the right next step for people.
- 2:09 According to the American Psychological Association, they recently ran a survey and found that 77% of psychologists said that their patients are using AI for mental health support of some kind.
- 2:24 And so, again, this reinforces this gap that we're working to address.
- 2:30 This is what Sonder looks like.
- 2:34 It's a conversational AI.
- 2:35 There's also voice capability.
- 2:37 It enables users to reflect on their lives, to track progress on goals.
- 2:43 It's available 24-7 for support and also to practice evidence-informed grounding exercises, tools, et cetera, as well as getting ready for therapy sessions or getting support between sessions.
- 3:00 So let's talk about the technical details here.
- 3:02 Sondermine has been investing in the agentic AI space for quite some time now and iterating on some features.
- 3:09 So we're really excited to share some of those learnings with you today.
- 3:13 So let's talk about our guardrails and the harness that we've built to address this clinical groundedness.
- 3:21 Fundamentally, we have our input guardrails and our output guardrails.
- 3:25 And those kind of sandwich Sonder Core, so to speak.
- 3:29 The input guardrails look at the user message as it comes in to see if it requires any intervention before Sonder Core responds.
- 3:38 The output guardrails look at the AI response and the conversation as a whole to see how the conversation is going.
- 3:45 And if any clinical safety is at risk, then it can intervene and keep the conversation on track.
- 3:51 When we were designing this, we understood that we're building for the unknown.
- 3:56 It's an empty box.
- 3:57 People can put
- 3:59 whatever they want in that.
- 4:00 And mental health is a very vast and rocky space.
- 4:04 It covers a lot of territory and is very complex and nuanced.
- 4:09 And so we knew that modularity was going to be key here when designing this system.
- 4:15 we knew that we would have to be able to iterate on sonder core without compromising the safety of users.
- 4:21 And so the modularity piece was very important.
- 4:24 Secondly, a lesson that we've learned is keeping the guardrails as separate LLM as the judge calls makes them more robust and harder to circumvent.
- 4:36 They're harder to prompt engineer and like just
- 4:40 you know, jailbreak and continuously conversationally try to drive it off the rails.
- 4:45 And so even though this is a trade-off in latency and in cost, of course, we believe that the sensitivity of this use case warrants those separate pieces.
- 4:58 And lastly, we need to be able to trust that the guardrails are going to do what we need them to do when we need them to do it.
- 5:05 So evaluation is also extremely important.
- 5:08 So this modularity enables more straightforward evaluation process.
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