WRITING THIS article presented a challenge because of the widespread use of the 4th Industrial Revolution catchphrase by politicians and technocrats it might be taken as criticism.
However, it is crucial for us to understand the challenges that may hinder the 4th Industrial Revolution by offering solutions to specific issues in Namibia.
In contrast to the well-understood 1st, 2nd, and 3rd industrial revolutions, the 4th is characterised by autonomy.
It enables software programmes to independently learn and execute tasks through neural network models.
Examples of these autonomous software programmes include facial recognition software predicting a person’s age and a self-driving car adept at identifying objects and making informed decisions, mirroring human capabilities.
CRITICAL ISSUES
My concern, however, lies in the lack of practicality in our approach.
The 4th Industrial Revolution demands substantial electronic data to train software models.
The critical question therefore arises: Are we collecting sufficient electronic data to feed the neural network models we may conceive?
The answer is a resounding NO.
IT systems are absent in the public space. Those that exist work in silos.
No school management systems to give visibility to important factors such as enrolment, progression, identify talented teachers, identify poor pupil performance because of socio-economic challenges, etc.
No comprehensive healthcare system, disjointed birth certificate and national ID systems to allow Namibian ID numbers (not ID cards) to be issued at birth –important aspects of uniquely identifying citizens which is a key requirement for e-governance.
REAL TIME
Additionally, there is a lack of real-time systems to track unemployment and employment or predict potential gender-based violence incidents based on reported cases over time.
Without the IT systems to collect essential data for neural network programmes, our talk of the 4th Industrial Revolution as a solution in Namibia remains mere rhetoric.
The solution therefore lies in returning to basics by developing fundamental IT systems, and breaking silos to establish a singular source of truth, eliminating redundant data-capturing processes.
It’s not a complex feat, like constructing an advanced neural network model.
Let’s embrace simplicity and practicality.
- Nabot Uushona holds a Bachelor of Science in physics and a Master of Science in electronics
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