Humans for AI

One of the biggest challenges facing the education today is the inequality brought in due to the lack of accessibility. As the world moves towards online learning, advanced technology to make learning more sophisticated; sections of society which lack access to network are left out. 

Secondly, as we advance into the data economy and the 4th industrial revolution, Artificial intelligence and related skills are becoming crucial and the foundational part of this knowledge is rooted in middle school math skills.

Third, each student is special and needs to be profiled to provide individual attention. This is lacking in our schooling systems today which have a herd mentality. 

Providing accessibility to math skills to middle schoolers by providing personalized learning is the central idea to our solution. Connecting urban and rural teachers, mentors as Humans in the loop to make it a level playing field for the future.

As we get into the age of the fourth industrial revolution, one of the challenges we face is that new jobs are  being defined and traditional jobs been displaced, the future needs a new workforce. This workforce needs to be equipped with the right skills - with concepts related to math, data and coding which are necessary for technologies like artificial intelligence.

 The problem faced by many a people is that they find it difficult to acquire these skills in later years if their foundations in middle school are not strong.  So we engage to build this foundation and make students future ready.

The other challenge is that students in urban cities and metros have found a lot of avenues to learn these skills, however rural kids have no access to such opportunities. 

We strive to bring in these skills to the rural population, especially kids, to ensure that the future workforce is balance and diverse. 

Our solution consists of a tablet device which will be preloaded with learning videos specifically chosen for a particular student based on his/her learning profile and interest. This will be targeted to middle schoolers to develop math skills in an offline setting.

The technology used will be concepts from Artificial Intelligence and Machine Learning. Namely, the videos will be chosen on a recommender system which will be profiled and trained based on the students learning interests and the pace at which (s)he will progresses.

The student will initially be profiled by his/her own teachers ( rural areas school teachers) and a learning and assessment profile will be setup for him/her by the  homeroom teacher. The learning content model developed and modeled by the urban teachers ( with access to latest videos for learning) will have predefined student archetypes to which the student will be matched. 

The student will take up courses at his / her pace or in a rural school setting and attempt assignments - similar to an online learning setup but this will be offline as network availability will be low. The student then at defined checkpoint intervals uploads his / her work and gets his/her profile model trained. Based on the updates a new set of videos and content will be downloaded and based on his/her personal progress, the next level of assessments will be provided to him/her. This will allow him/her to have personalized learning.

Our solution serves the middle school children (11 to 14 year old) with limited or no accessibility to online learning.  It also aims to give personalization to students by using profiling and learning assessments to define student archetypes for learning.

The children of today - the workforce of tomorrow;  have accelerated  learning with abundance access to the internet and content like videos, chatbots, AR/VR tool simulations etc. However these modes of learning reach only a privileged few. Students with limited access to the internet and lack of network connectivity are not able to get access to these new and advanced modes of learning. 

Moreover, the future generation needs specific skills as they prepare themselves for the fourth industrial revolution which is going to transform jobs and our way of working. Having limited or no access to learning resources will put a large socio-economic divide between the urban and rural students - between the haves and the have-nots.

Our solution addresses the key skills of Math needed for the new data economy. Also in the age of personalization, we feel that each student has to have access to personal learning mechanisms which we hope to provide.

The problem we are trying to solve is putting a level playing field for urban and rural middle schoolers specifically for the math skills which are a foundational block at this age.

Our solution has a computer tablet loaded with offline video learning content which will be modeled and annotated by the urban teachers. The students will be profiled by the rural teachers and each student will get a personalized content for learning math. This will allow students who do not have access to network and the internet to still be able to develop math skills to the same level as the urban students.

We have selected the stage as concept, as even though from a technology perspective this solution is well tested, the model training aspect from the "Humans in the loop" involving urban and rural teachers is something we have not yet explored and currently lack the resources to do so. 

The Content and Learning Material videos will be annotated by the urban teachers and the Student Assessment Data Model will be annotated by the rural teachers. This training model is something that needs to be explored further.

Our solution is innovative to support rural children to develop required skills to be part of future workforce. 

Continues education during the time of pandemic is a problem which many urban schools and online training programs are trying to solve. However these solutions are not covering rural education system due to the limited network and lack of feasibility in the solutions to cater the needs of rural children and also availability of other resources which includes trained teachers, mentors etc.

We are targeting to solve this problem with the use of technology and limited human resources.

Three people - part time

We have been working on this technology area as a part of our day job and this project is a volunteering activity.

We have people from across the globe as a part of our organization. We currently have 6 chapters in US, UK &I, France, Singapore, India and Australia.