There is no better time in developing markets and the current industrial revolution than right now to contribute to the discussion of the Fourth Industrial Revolution (4IR) and the alarming PR messaging that it has, some well-intentioned misdirection and the other half split with an overflow of information of which skillset to prioritise and which technology to employ. The job losses, the new technology and the illiteracy to name a few of this incoming era can indeed create a barrier of intimidation on entry, and what adds to the complexity of the situation is that the data lies.
Exploring Data Bias
You should be familiar with the notion of data being the new currency, at least in comparison to oil as an infinite resource that can empower economies. And data, having been undocumented, raw and undigitized has always been around, it is rather the scramble for the science and technology of it, and who gets access to it first that impacts the narrative and gets an opportunity to score some points for their industry, economy or group of privilege that they belong to. It’s the data scramble, it’s the data rush. This is what’s caused, I believe, the insurmountable backlash and inaccuracies, the product bias towards chatbots or products otherwise, whether its towards gender, race or access. The question that then follows up to this statement would be where the data is, and exploring the intentional bias and opportunities for solutions to the bias, and what stakeholders can do create inclusive economies.
The Impact of Bias Practices …
Machine Learning which is an application of Artificial Intelligence (AI) that studies the sciences of how machines can automatically learn and improve from experience by learning from themselves, is learning from the bias of the producers of the algorithms, and these makers of algorithms are largely white males as can be seen in an example of this through facial recognition products created by IBM, Microsoft and Face Plus Plus. That means that, so is the (informed) data, which breeds much room for prejudice.
A recent example of a sector that informed this bias is financial services, mostly with credit, and is now building the intelligence tools to either enforce or break away from this. In South Africa, usury expert Emerald van Zyl, claims that Standard Bank (including banks like First National Bank), which is Africa’s oldest bank is currently under hot fire for billing its black customers at a higher interest rate in financing. This is not the first time this occurred with Standard Bank, as in 2012 they were also charged with violating the National Credit Act where eventually customers were refunded by 2013. Now, if the machine learns these algorithms and continues to grant the same product bias, the discriminatory practices are more than likely continue.
This is kind of problem is also consistent in the health sector. In a New England Journal of Medicine article published on 15 March 2019, researchers of the Framington Heart Study showed the risk and capability of AI algorithms to demonstrate bias. The research used AI to predict the risk of cardiovascular occurrences in non-white populations and the results demonstrated bias in both over- and underestimations of risk.
People's lives are at stake through the products of 4IR. And, beyond the glitter of Sophia The Robot and the New Generation Kiosks at companies like McDonalds, there is a community that is not being intentional about being inclusive and rather duplicating structural socio inequalities that implicates another.
Data bias does only one thing, it mirrors what is socially ingrained, which means that it lies and tells a partial truth, of which is not meant for consumption by those who produce it.
Dismantling the Structural Bias
The call for inclusive economies goes beyond teaching young, black girls how to code and having strictly women only data science clubs. Practices like hiring more diverse teams leads to impactful and informed product creation and is a good contribution to mitigate prejudice algorithms and encourage more accurate data on a model. A sub-division of AI, Natural Language Programming (NLP) is a study that is concerned with the processing of computers and human natural languages, and can be used as a great example and opportunity for the necessity of the inclusive call in the sector. Translating open source of data sets in different parts of the world requires an understanding of the language being translated so that we can not only have Siri being able to understand my instructions in English but also the opportunity to preserve and digitise languages like the Khoi which are diminishing, mostly because, especially with African languages, the impartation of language happens orally. A great example of this opportunity is Ajala Studios, which a Nigerian startup that builds natural language and speech processing applications for African languages, which means that they can too synthesize speech from African languages presented as digitized text, a gap that’s mostly recognises Western accents, voices and names.
The responsibility of creating these opportunities is also a shared responsibility, especially with the public sector. Governments in both developed and developing markets need to invest more in Research and Development (R&D) and in the social concept of open innovation (engaging the public with the data) especially as the impact of this investment is quite telling. And although it is a long term investment, the return on this investment is worthwhile. Researchers from the United Kingdom (UK) and Saudi Arabia looked at 40 Asian counties and how their spend on R&D lead to the production of quality research publications across sciences and social sciences; and with more research in the UK showing the positive impact that public investment has in the increment of private sector investment and in attracting foreign direct investment. Through this R&D investment and its impact in the knowledge economy, it also presents an opportunity to lead to more computational intelligence and feeding it the missing data, and the greater economic impact through the indicator of Gross Domestic Product (GDP).
The next solution is not only costly but risky, but if there is one thing that I’ve learnt about being in the innovation space, whether the product is out to market or still in the proof of concept phase, no matter how good it looks on paper, it’s that it is never too late to take the product off market if it doesn’t serve its purpose. A great example of this is Vodacom South Africa’s failure, thrice to launch its sister Kenyan network SafariCom’s M-Pesa to the South African market. Factors like an onerous regulatory environment, the competitive advantage that the larger and established banks have with their products to low-income consumers, and some have also argued due to the mixed messaging upon launching, from introducing it as a mobile money wallet to a platform that is linked to your VISA card. This case study is also an example of the danger of wanting to copy and paste a one-size fits all product into an Africa that is not a country.
At the end of the day, it's about investing in the visibility of the communities so as to include better, impactful and innovative products and profitability for all ecosystem stakeholders a part of the operation chain.
The data samples ARE there. And unfortunately (or an opportunity), so is the bias. But all is not lost, not with the desire of visionary stakeholders to operate in a transformative world that uses the enabler of technology for sustainable good business.
On LinkedIn, I recently uploaded a post that had a graphic recording themed on the discussion of mobile banking unpacking challenges, opportunities, the pillars of the ecosystems and the key stakeholders in the markets. It was a piece of art and knowledge that was created about 4- 5 years ago, and however powerful the discussions in the room, the micro-themes still echo the non-silver bullet industry that’s catapulted Africa’s invitation to the global seat of innovation, and particularly financially inclusion. Although the hotbed of the financial inclusion conversation is mobile money in Africa, in this article we’ll explore and propose ways to continue enhancing the distribution mechanism of mobile to employ an economically inclusive society.
Exploring Mobile Money Mission
It was not so long ago when MPESA launched in Kenya, and successfully so that not only did it grant Africa the opportunity to drive the mobile money conversation and allow the unbanked to access financial products but, for some, create and enhance digital footprint, and a chance to be economically active.
Traditional banks notoriously have, for a long time created financial products that were only accessible to the middle class and above, those who were already economically empowered. In the exclusivity of these financial products, the role of startups, data (open or big) and technology became important in leapfrogging the traditional banking industry and getting credit right. The rise of the living standard in emerging markets also created an opportunity for the mobile economy to continue to thrive, whether with an Android phone or if you’re living in the townships.
Who Gets to Participate?
According to research by the PEW Research Center, in emerging economies, the population in some of the poorest communities do have access to a mobile phone, even though the ownership is not of a smartphone. What this does, is that it gives rise to Opening Demand so that the non-digitally savvy citizens may participate, and Supply Inclusion for manufactures, such as now, the new smartphone manufacturer in Africa with the Mara Phone Project.
Mobile money products bank on the vision of a society where the individuals are economically active and visible, from women owned businesses who in some economies didn’t have access to credit to spaza shop owners and the super paranoid cashless user. And in doing this, it is also giving them a digital footprint, and an identity that is tailored for edifying their lifestyles as well as their businesses and financial products.
However, the cost of this inclusion also comes with its own price for the service providers, which includes finding ways to enhance the user and experience centric for the customer.
The Cost of Digitisation, for the Supplier
The high level of customisation to operate in data-lite countries, where data is not enriched and infrastructure is needed to augment results is quite costly. At this moment, this is where the call to government to participate in the market is quite loud in knowledge sharing spaces like conferences and roundtable discussions – an opportunity to serve its citizens better, create more competitive markets and empower lessening the digital divide.
Looking at creating cheaper solutions will cost spend of engineering and predictions analytics, investing in more talent, having the processes to refine the data in order to have more value, the urgency to transform through infrastructure and the list goes on to be an enabler. The return on investment in this cost is not in just the adoption of more products, but also in customers being better informed and better buying customers.
What’s In It For Me, the Consumer?
For a customer like myself, I’m constantly looking for ways to continue leaving my credit and debit cards at home and having my own money market on my phone. The question of “What’s In It For Me?” is what’s constantly at the back of a consumer’s head, whether one has a mobile phone that’s a smart or feature phone – all phones matter.
For the smartphone user, products like Whatsapp, Google Suite, UBER, Booking.Com and BiNu or Facebook which states that 94% of its 170 million African users access the platform via mobile, and with even 100% of the Nigeria population accessing it through mobile. And for feature phone users, products like Mobile Banking, Bwenzi Lathu, JUMO, Kopah Doh or Telecommunications Services are also what make this particular phone a market of the present and future.
While we wait on the digital divide to close and for an all inclusive society, let’s be mobile and invite stakeholders to continue creating enabling ecosystems and environments to innovate for a thriving present and future mobile market.