The problem iConsent solves

The 3 critical problems that we narrowed down for putting together UX for a typical AA consent journey are:

1. Lack of interest among users to read consents
2. Hard to navigate consents
3. Interfaces not being inclusive
   The ultimate benefit that can be driven by solving these problems is the benefit of trust. Thus this problem looms way larger than any other typical UI/UX problem.

Our solution is a UX toolkit specifically designed for consent journeys for the very diverse Indian user space. A language component, automated video generation component and accessible visual UX flows are part of this toolkit.

1. The language component translates text in UX based on a hybrid config object that combines google translation with manual config for a more casual vernacular content.
2. The video component takes in the consent artefact and spins out a 30 second video in the user’s native language to walkthrough the specifics of a consent.
   The other UI components form the flows that subconsciously nudge the user to finish reading the consent details before approval/rejection. Card views, progress bars, nudge modals, no-scroll UX are some of the pluggable components in this toolkit.

We did multiple loops of real user testing and fixes based on the feedback. In some of these tests we also validated the solutions to specific problems against the involved target group of users. The overall solution has multiple degrees of delivery (audio/video/visual) that can be extended in various other horizontals/verticals. One notable use-case is the usage of the audio background of video in automated phone calls that can reach out to users with the lowest of device/bandwidth provisions. Ultimately, the solution brings in user trust in the overall AA ecosystem.

This is a developer generic, target group specific toolkit that can be used by the AAs to form a fantastic baseline for their flows and configure it to their own design aesthetic.

Challenges we ran into

1. Indic fonts rendering in images was a mammoth task. Existing image generation tools like PIL only render Hindi properly (without breaks between letter parts). We had to put together a custom text renderer to get our video component working for 6 Indian languages (scalable for any higher number)

2. Understanding i18n international language standardization library to build the site for 6 Indian languages while keeping easily scalable for many more languages.

3. Video generation is a highly time intensive process mainly due to system write times. We had to optimize the generation using multi-threading so that the generation times are as minimal as possible. Initially we started with 40 seconds time for generating a 7 frame video and currently we stand at 8 seconds to generate the same. This can further be reduced to under 5 seconds by using streaming architectures instead of disk writes.

4. Narrowing down to the most crucial problems while also keeping the audience coverage high was very tricky. This use-case has too many possible problems and solutions. We had to talk with many peers, mentors and some real users to narrow down even before we started working on the solution. In that aspect this problem was very unique in its own way!