One barrier to feeding back for many people is language. If they do not speak one of the primary languages of the country or service provider, then they miss out on vital information and opportunities to input and engage. For this reason, it was essential for Loop to be accessible to underserved populations, in multiple languages, in near real time, including languages where Machine Learning does not exist.
In our learning series we highlight what we learnt, what are our takeaways as a result of this learning and what we will continue to monitor and enquire about:
As a result of the digital revolution, machine translation of languages will have an incredible ability to bring more people into conversations and will reduce barriers to access. Every month new languages are being added and include over 100 languages already. Translation is far from perfect, but it enables access which otherwise doesn't exist. This exponentially reduces the cost and time to have things available in multiple languages, if considered at all. The opportunity this brings for Loop and the wider development and humanitarian approaches is significant and only just beginning. However, gaps still remain.
Loop has developed a flexible approach using a sliding scale system based on the effectiveness and availability of machine translation. Languages graduate from one approach to the next:
We have also built in the ability to benefit from crowdsourced improvements. Anyone can identify a poor translation, propose an improved translation or ask for a conversation thread to be translated into a non-machine translated language.
Loops continued enquiry: We will be watching to learn how well machine translations can translate context specific short feedback accurately.
Through our multiple field tests and numerous prototypes, we learnt that in many primarily oral languages, the dialects are so diverse that often a written version is not understood by all speakers.
For example, we tested Nyanja and Bemba in Zambia with local people who do not speak English confidently. Every time it was tested in a new environment, they fed back on improvements on how to write it. This became circular with no common approach for all native speakers being found.
Loops continued enquiry: We have invested in having professional translators provide much of the static translations of key documents and text. We will monitor the analytics to see how many people read this in underserved languages versus the majority languages (English, Spanish, French, Arabic etc) version in each context. This will teach us about if those who want to read a one-page guideline are only those who are also confident and literate in majority languages.
Loops learning #3: Automated reading of written text breaks down few barriers.
To help remove obstacles to literacy we also built in a ‘Read to me’ function on Loop. This is where the phone can read out any of the text with the click of a button. This function is only available on Smartphones. Many of the people we wanted to target who were not confident readers were also those who did not have a Smartphone. Thus, this still misses out much of the target population for this function.
In addition, for those who did have a Smartphone in Zambia, they were often unfamiliar with the ‘Read to me’ function and people couldn’t easily identify its presence or how to use it.
We will have a ‘Read to me’ function available on Smartphones in the languages we are able to serve.
Loops continued enquiry: We will monitor the analytics to see if some subsections of the population benefit from this function. We will also monitor the analytics to see how many people use the ‘Read to me’ function and in what languages. This will teach us where to prioritise translations and approaches to promote inclusion and informed access to feedback and engagement through Loop.
People who speak underserved languages only were primarily those who were affected by the digital divide and in addition were not confident readers and writers in any language. They face multiple barriers to feeding back and raising their voices, including:
Loop’s technology and approach reflects our design of being as local and accessible as possible, so we have now prioritised the development of Interactive Voice technology over phone (GSM). We can include interactive voice over the internet afterwards, but this does not target those people facing multiple barriers to engagement.
We have designed and are testing in Somalia, the following flows:
The technology that many of us are familiar with in our day to day lives, such as:
These can all be linked, in appropriate, safe ways, as they evolve and improve, to revolutionise the Aid sector's ability to listen to, and speak directly with, people who are currently excluded from technology at scale. The possibilities are limitless.
This could be one significant contribution to closing the digital divide.
