Catalyzing the Creation of a Data Ecosystem

Palestinians in the West Bank and Gaza are living in an extremely fragile environment:  they are under occupation, deprived of their basic human rights, have no control over their borders, movement of people and goods, land, water and even frequency resources. A population of nearly 5 million people live today in closed and shrinking ghettos, in poverty, entirely dependent economically on the occupier’s economy mostly as unskilled laborers.

Under such conditions, a technology industry - in particular one that is data and AI driven - would make a lot of sense. In fact, it would be the only viable economic survival option for the Palestinian community, not only as an industry capable of overcoming borders and movement obstacles, but also as a means to support much more effective social, developmental and human rights’ agenda that is very much in need by the society.  Unfortunately, the data and IT technical capacity is extremely limited among Palestinians. Universities and higher educational institutions have very few Data and AI programs. Those that exist are limited to computer science or related disciplines and can be characterized as older generations of data science.  There is very limited uptake of data science in humanities and developmental issues at universities or the community at large.  Policy and decision makers are largely illiterate about data and AI governance issues such as privacy, open data, responsible use of data and AI, security, etc… and the basic educational system is severely underperforming in science and math, providing a very limited pipeline of students ready for the data revolution.

Birzeit University’s Center for Continuing Education (CCE) through the support of IDRC engaged in 2015 in a first round of Open data for Development (OD4D) in partnership with the Access to Knowledge for Development center (A2K4D) at the American University of Cairo.  This built capabilities at CCE to begin developing and delivering capacity building programs in data science locally.  In 2018 CCE was granted a follow-up project with IDRC and became the OD4D MENA regional hub.  One of the main objectives of the hub was to catalyze the creation of a data ecosystem.  This was a challenging undertaking considering the “data baseline” is extremely low. There is hardly any development or projects in AI with noticeable impact and the ecosystem suffers from legislative and regulatory gaps in data governance.  

In order to have an impact, CCE had to research a creative approach that would be relevant to the local context and the limited resources.  Considering the almost non-existing data landscape in Palestine, CCE was faced with a major challenge: “where to begin”? There was very limited expertise and human capacity, very few educators who understood data in the 4^th Industrial Revolution context or with applied and practical experience. There are hardly any data companies or startups.  Datasets are either locked up or not accessible, even data that is supposed to be open.  Data providers that have large amounts of data either do not recognize the value of this data and its business or developmental potentials, or don’t have the technical skills to capitalize on this data, and there are practically no data related policies or regulations.

It was clear that the starting point had to be through a capacity development approach that would build a critical mass of data professionals with relevant skills and knowledge to understand and work with data, create data products and services, create show-cases, and eventually create and influence data and AI policies (open and non-open).  To achieve this, CCE created an applied learning journey whose outputs include: i) capacity development in data technologies for people with computer science backgrounds and for professionals from a range of humanities, business and sciences backgrounds, ii) create data startups and/or ii) create data for development projects.  The approach was to line-up feasible data project ideas that are based on real-life problems or opportunities and assign them to groups of professionals and researchers (in their capacity as trainees and developers) to implement as the final outcome of their learning journey. This was carried out in partnership with industry leaders, businesses and practitioners from different sectors.  The data expert team from CCE worked with specialists from the various disciplines (health, business, human rights, finance, education, agriculture, etc.) on idea generation for potential data projects that have a high potential for becoming data startups. It was those projects that were assigned to the trainees to implement.  The partners from the various disciplines provided high level support and mentorship to the project teams as they developed their products to ensure the fit between the data product being developed and the needs of the sector/ organization.  It is important to note that the ideation process and engagement of the partners became an important component in capacity development and education for the various sector leaders and data owners.  

The learning journey structure created a unique environment to provide the support to learn, experiment, play with data, and test models, then move into an accelerator and eventually an incubator (through the Business Hub unit). Participants acquired technical skills through the learning journey and were guided into developing the data products step by step. This demanded of them to self-learn and scaffold the acquired knowledge and skills through the projects. Technical mentors and support from practitioners specialized in the field of their product (e.g. finance, health, Human Rights, and tourism) supported the trainees build the product.  Business mentors from the B-Hub (the University’s incubator) provided them with support in taking promising data products to the market.  This process created and is creating a pool of data professionals with show-cases that are being used in the data literacy programs, awareness raising campaign, and policy dialogue and advocacy.  It is important to note that issues pertaining to responsible data that cover governance and gender were constantly emphasized throughout that data development life-cycle.