Is Kenya's blockchain and AI dream dead?
What you need to know:
- Since the government launched the Kenyan blockchain and AI report last year, It is perhaps a good time to look back and reflect on what has been achieved so far.
- Capacity building in blockchain technologies remains a challenge, with many blockchain enthusiasts more keen on how to trade in global crypto currencies rather than to create local blockchain solutions.
- On the other hand, AI seems to have a better uptake particularly within the private sector.
- Let us hope this coming financial year, we shall realise better performance in blockchain and AI adoption, particularly from the public sector.
It is one year since the government launched the Kenyan blockchain and Artificial Intelligence report in a well-publicised event at the ministry of ICT. It is perhaps a good time to look back and reflect on what has been achieved or not over that period.
When one talks about blockchain, what comes to the mind of many is the money aspects made popular by the bitcoin crypto currency craze.
Whereas crypto currencies are the first demonstrated use case of the blockchain experiment, they represent a very small part of what is the full scope of possibilities within the blockchain space.
For some reason, Crypto currencies represents the most active communities in the blockchain space – despite the cautious circular from the Central Bank of Kenya warning commercial banks not to get involved in crypto-related activities.
Slightly related to Crypto currencies and perhaps more acceptable and clearly legal is the concept of tokenised assets.
A tokenised asset is any real-world asset that is converted into a digital value and placed onto a blockchain system for increased integrity and transparency in terms of its related record keeping and transactions.
The asset could be land, real estate, stocks, educational certificates, donations, voters’ election choice amongst other items of value that are prone to the risks of compromise instigated by the trusted party– insider threats as it were.
It is unfortunate that very little progress has been realised in the tokenised space despite its potential and obvious need and relevance since it responds to the question of corruption that continues to plague the country.
Several reasons could be behind this turn of events, but capacity building and willingness to tackle corruption or lack thereof tops the list.
Capacity building in blockchain technologies remains a challenge, with many blockchain enthusiasts more keen on how to trade in global crypto currencies rather than to create local blockchain solutions.
Nevertheless, the question remains as to whether the few blockchain solutions that have been prototyped can be taken up by decision makers who, more often than not, maybe beneficiaries of the prevailing centralised, easy-to-compromise ICT System.
On the other hand, AI seems to have a better uptake particularly within the private sector.
Be it in the financial, retail, transport, Telco or insurance sector, AI is being deployed in various forms to extract insights and predictions that are beneficial to enterprises.
Using AI algorithms, enterprises are able to mine customer data to influence business decisions such as recommending new products for customers, discounts rates to be offered for each customer and which transactions are likely to be fraudulent.
Predictive analytics, as it is called, is currently becoming the norm rather than the exception, with the more experienced enterprises moving to the next level of AI use, going by the name Prescriptive Analytics.
Whereas predictive analytics estimate the probability of a future event happening, prescriptive analytics suggests what to do in order to make sure or guarantee that a future event does happen.
Essentially, prescriptive analytics gives your business insights while predictive analytics gives your business foresight. Unfortunately, these AI developments seem to be happening only in the private sector.
I am yet to see similar level of AI use in the public sector, despite the fact that public sector sits sectors such as education, health, security, transport and agriculture.
If we were to grade the performance of blockchain and AI initiatives since the launch of the report last year, we would reluctantly give a 50 per cent performance score. We have had mixed results with a lot of room for improvement.
Let us hope this coming financial year, we shall realise better performance in blockchain and AI adoption, particularly from the public sector.
Mr Walubengo is a lecturer at Multimedia University of Kenya, Faculty of Computing and IT.
[email protected] @jwalu