Aaina As A Service
Providing in-person support beyond the screen
During part one of our project, we were focused on micro-interactions and feedback from the Aaina user interface. We thought about the conversation between the user and Aaina and even acted out the exchange to physicalize our reactions to Aaina when she moves, rotates, gets bigger, brighter, ect. This was invaluable in creating a positive experience for the user– but it was only when we were presented with Part 2 of the project that we started to think of Aaina as a service.
The brief: There are times when people need medical interventions for their mental wellbeing. In those cases, in-person interactions with psychiatrists are necessary. Your AI counseling service partners with psychiatrists in the referral of patients who the AI deems may need a medical intervention. Your client will be leveraging the information the system has on the client through their AI-led counseling sessions to provide a customized check-in interface and doctor-facing web portal.
To do this, we first mapped out the flow as a group on the whiteboard.
We considered the following questions:
- How would Aaina help the user transition from AI support to a real, in-person therapist? Would it happen over conversation and who would initiate?
- What language would the AI use to recommend that the user go see someone in person? What would trigger that conversation?
- How would the user engage in next steps? How hands on does the user want to be in choosing a therapist and booking an appointment?
- How can an AI and professional therapist best support each other? How might we leverage the data Aaina has been tracking to provide a better in-person service for the user? How can we both educate the user about their data and give them a choice around sharing?
- What key information does the user need to know in order to choose a therapist they feel good/confident about.
After discussing these questions as a group, we developed a service blueprint that laid out user touch points, actions, and backstage interactions for the entire service: from Aaina to in-person therapy. Creating an in-depth blueprint early on grounded our groups’ understanding in the service flow and helped us all get on the same page.
By visualizing the service as a whole, we identified an opportunity to create value flows to and from the Aaina app.
That is to say, we designed the service in a way that allowed our user, Sarah, to find value in continuing to use Aaina (the CUI) even after they deciding to see a therapist in-person. The idea is that Aaina would support the therapist visits through shared data. Sarah and her therapist would co-develop goals and an action plan, which would be sent back to Sarah’s Aaina app, where she could both track her progress and use Aaina for reflection & support.
We reflected on learnings from Molly’s seminar – specifically on how AI and human competencies compliment each other. By understanding this, we were able to map out their strengths and weaknesses in order to identify just how they could support one another.
