Land Rights, Genetics and Data – A response to fourth industrial revolution

Land Rights, Genetics and Data – A response to fourth industrial revolution

By Musa Kalenga

Let us begin with the great debate that rages on is about singularity. Singularity is the hypothetical point in the future when technological growth becomes uncontrollable and irreversible, resulting in unfathomable changes to human civilization. It is worth noting that singularity (just like electricity) will not happen all at once or over night. There will be a wave of adoption across the globe and over time it will become as pervasive and normal as electricity has become.

As we approach singularity, an important question is, at which point should we panic as Africans? In my head I have a picture. It is an extremely vivid picture of what the world will be like when there will no longer be a line between human capability and computing power as we know it. I have also reflected on many conversations with different people in commerce, technology, humanities and the sciences and I realize that when others think about the fast approaching future, many have a similar picture in their heads as I do.

To be practical about where we are as a continent, we need to reflect on some key realities that will not change. For instance, at this point, we are in the eye of the mobile storm. We live in a mobile era where these devices are extensions of our bodies. The mobile era has created an eternal bridge between the internet era and the information era. The internet is driving an explosion of data and services that feed the distribution and availability of information. We also have phenomenal social, economic and structural problems that we NEED to solve as a continent. According to the Human Development Index by the UNDP Africa is still the lowest ranking continent regarding factors like healthy long living, Quality of education and knowledge acquisition and standard of living.

There is an irony of having extremely important problems to solve at the same time as we are entering the 4th industrial revolution, the era where virtually anything is possible. This irony is that the overwhelming volume of problems to fix can create a crippling inertia about where exactly to begin. The temptation is to try and boil the ocean and solve EVERYTHING and we know this is not impossible, nor is it sustainable, so let us focus on three core problems and we can match the technology to provide a sustainable, impactful solution in the fourth industrial revolution.

Land Rights . The Berlin Conference in 1884-85 also known as the Congo conference left Africa in a state of geographic ruin and land rights were used to segregate and colonize our continent. It was a game being played around Africans and one may argue that the game continues to be played.Property rights are the most fundamental institution in any economy and society. They determine who makes decisions about valuable resources and who captures the economic gains from those decisions; they mold the distribution of income, wealth, and political influence; they set time horizons and investment incentives; and they define who will take part in markets. These attributes are well recognized among economists for spurring economic growth. Now, if we consider for a moment that since 1848 Africans have not been able to participate, what would the impact on land reform be if we were to use technology like the BlockChain ? It means that we would be able to reverse and amend a secure log of historic and present land allocations and transactions that can be traced back from a lineage perspective. Not only does this start to fix the wrongs of the past, it begins a systematic process of restoring dignity to Africans by re-allocating ancestral land.

Genetic Engineering . Africa has endured wars and human atrocities that have altered the genetic make up of many generations of Africans forever. This is true to the extent that there is even a phrase that refers to the “ African Gene ”. According to an article by Michael White , he states “Our genetic make-up is the result of history. Historical events that influenced the patterns of migration and mating among our ancestors are reflected in our DNA — in our genetic relationships with each other and in our genetic risks for disease. This means that, to understand how genes affect our biology, geneticists often find it important to tease out how historical drivers of demographic change shaped present-day genetics.” Now, for a second, just Imagine technology like CRISPR that was able to start reversing some of these genetic mutations that began in the age of slavery. Now, such an extreme solution is important, but I also acknowledge that there are other, more fundamental challenges with delivering even basic health care.

Quality Data Availability – The data gap is a systemic but crucial problem that we need to find solutions for. According to and article by Donatien Beguy (Head of Statistics and Surveys Unit (SSU), African Population and Health Research Center) “Data, and especially data of good quality, are essential for national governments and institutions to accurately plan, fund and evaluate development activities.” It is difficult to comprehend that in a continent with such a young, connected population we cannot make use of mobile devices to solve the problem of data availability. Imagine if we could create a network of Micro Data Collection Businesses the same as the vendors that sell airtime vouchers. The creation of a decentralized network of vendors collecting data on the bottom of the pyramid consumers not only solves an important gap in quality data availability, it also allows economic opportunity.

To keep finding solutions in Africa, we have to approach problem solving from First principles and if we break down a problem into smaller more specific components, it is easier to solve for the bigger problem. It will not be technology alone that will allow us to respond to the fourth industrial revolution.

It will be a combination of empathetic leaders, keen problem solvers and astute technologists that will collectively unlock value. In my very optimistic view, there is no need to run for the hills because human beings still have a critical part to play in the fourth industrial revolution. Our ability to use common sense to reason, empathy to feel and creativity to explore still makes us very valuable in the fourth industrial revolution.


Powered by Blockchain: Realizing AI’s Full Potential

Powered by Blockchain: Realizing AI’s Full Potential

Blockchain’s ability to securely expand an AI implementation’s access to data across organizations will drive a whole new set of insights and value.

Artificial Intelligence (AI) could change the world more than any other advancement since the Industrial Revolution; fundamentally reinventing how businesses compete, grow, and succeed. However, each AI system, and each algorithm within, is dependent upon training and acting upon trustworthy data to which it has access; typically limited to the organization implementing it. Simultaneously, blockchain is redefining business processes and systems of record, enabling secure and confident access to shared data between organizations and increased trust and confidence in the data. Together, AI and blockchain will enable organizations to exceed their current boundaries and gain access to significant amounts of trapped value.

Blockchain: the perfect partner for AI data
As surely as steam powered the Industrial Revolution, the ample flow of accurate data will drive artificial intelligence systems.

Leading business innovators recognize data’s central role inharnessing AI’s value, though many feel constrained by the relatively meager flows of trusted information they can currently draw upon to feed their systems. That’s why the leading technology firms have invested billions to acquire data-focused companies and their capabilities. The power of AI depends on the access to, magnitude, and quality of the data it can process.

So, while AI redefines the systems of business engagement, blockchain is recalibrating the systems of record. Together, they will remap organizational boundaries, moving them from siloed verticals with complex processes to operate efficiently across horizontals, and, in the process, releasing large amounts of currently trapped value.

Meeting the challenge; capturing the opportunity

AI systems are dramatically changing the nature of services and experiences for consumers. The current phase of the scaled use of AI has focused on the value and services individual organizations can deliver to people. This “internal application focus” results from the natural commercial emphasis of individual businesses attempting to drive profit and growth. Companies usually start with what they can do and control and the data they store in their systems. Rarely can a single organization comprehensively meet a consumer’s holistic needs, and most current AI implementation efforts reflect that limitation.

Take the example of a family relocating to a new home; one of the most basic aspects of life. Basic, yes, but simple? Not really. A myriad of organizations will focus on that single objective, including banks, insurance companies, realtors, inspectors, movers, retail firms (purchases for the new house), new school systems, utility companies, postal systems, the department of motor vehicles, tax authorities, and more. Today, virtually none of these organizations share access to the same information, and consequently, the family’s data remains fragmented and perhaps  inaccurately replicated across different players. To sort things out, the family must message data back and forth with each organization. As all these entities begin to implement AI systems, they will focus mainly on their own data or information they have permission to access and that could limit AI’s effectiveness.

Now imagine a world where, through a blockchain-based system, every party involved in the move could see the data and information pertaining to the end-to-end relocation process with appropriate permissions granted by the stakeholders— in this instance, the family. Organizations could access just the data they need, and because the information reflects blockchain’s enhanced trust levels, parties no longer need to engage in messaging and reconciliation. As organizations widely implement these kinds of models, the possibilities for AI systems will grow significantly.

In this situation, AI could become a type of consumer advocate service. A family would “own” and control their data since they alone would have full access to it. As a result, they would act as the conduit to drive that data into an AI system, which then makes recommendations and optimizes the data for their benefit.

AI systems will evaluate and optimize the elements of the moving experience across the end-to-end process, making links and connections that simply can’t be done today without severely overtaxing current fragmented data sets. For instance, an AI system could potentially access data related to the operational data for a house, including its historical utility/energy use, its insurance claim history, maintenance schedule, weather data, and combine this with the family’s behavior patterns, including hobbies and entertainment options, and use this and other information to calculate an accurate home maintenance cost profile. It could then design a service and insurance plan custom-tailored to the family’s needs.

In the future, wider access to data across an ecosystem and the advances in automated business logic via smart contracts could enable new and greater access for AI machines to traverse business ecosystems and deliver more comprehensive solutions to customers.


AI’s promise: for starters, doubling today’s economic growth rates

Artificial intelligence could double annual economic growth rates in 2035, according to an analysis of 12 developed economies by Accenture Research. It will change the nature of work, creating new, human-led relationships with machines that should increase labor productivity by up to 40 percent. And that’s just the beginning.

By helping people work smarter, AI could boost average profitability by as much as 38 percent, producing a bounty of up to US$14 trillion across 16 industries by 2035. The information and communication industry alone could deliver an extra US$4.7 trillion in gross value added in that year.

Combining multiple technologies in unique ways, artificial intelligence enables leaders to harness new entrepreneurial savvy that can rapidly sense and comprehend opportunities or threats, act on that information, and ultimately learn from the experience.

Use cases: blockchain makes AI better—faster
The combination of AI and blockchain is fueling the onset of the “Fourth Industrial Revolution“ by reinventing economics and information exchange.

As the following examples demonstrate, from healthcare to government and beyond, the potent combination of AI and blockchain is slowly but surely transforming industries and institutions worldwide.

1 Smart energy, smart buildings

Green-friendly AI and blockchain solutions can help reduce energy waste and optimize energy trading. For example, an AI system with access to a host of city-wide data sources through blockchain could be used to maintain a building, such as overseeing energy use by considering factors like the presence and number of residents, seasons, and even traffic information. To supply the energy, distributed blockchain technology will
ensure transparent and cost-effective transactions between producers and consumers, while machine learning algorithms that can hone in on transactions to estimate pricing. What’s more, blockchain combined with AI could significantly expeditereal estate-related transaction processes, which can otherwise go through too many channels before a contract is approved.

2 Public science
The “file-drawer problem” in academia occurs when researchers don’t publish “non-result” experiments. Because no record of them exists, duplicate experiments and a lack of knowledge follow, trampling scientific discourse. To resolve this problem, research institutions could store and access an index to academic research, making this experimental data available across the ecosystem. By adding data analytics to the combined data, scientists would have a much richer data set to pull from than would be feasible within a single institution. Then they could begin to identify elements and patterns, such as how many times teams have tried the same experiment or determine the probable outcome of a certain experiment, with greater certainty.

Hossein Kakavand, CEO of Luther Systems, asserts that AI will also play a bigger role in public science once “smart contracts” transacted using blockchain technology require smarter “nodes” that function semi autonomously. Smart contract simulate contractual agreements and can have wide-ranging applications—in public science and elsewhere—when academicsembrace the blockchain for knowledge transfer.

3 Supply Chain

The advancement of free trade has created increasingly complex global value chains. As goods move across production and supply networks, they cross through multiple jurisdictions, connect both advanced and emerging economies, involve multiple players and are subject to different laws and standards. This all requires a great deal of coordination, which not only adds to the complexity, it adds to the costs of these goods. The Global Alliance for Trade Facilitation, for example, estimates that roughly seven percent of the global value of trade is absorbed in documentation costs alone.

Blockchain-based digital identity promises to make the supply chain leaner, simpler, and more cost-effective. Digital identity for all actors, goods, and places in a supply chain, establishes provenance and a means of trackability throughout all touchpoints in the supply chain. Through creating digital representations of real-world assets, and tracking the relevant data of those assets as a single, shared source of information, major efficiencies and product improvements can be realized. Rather than valuable data being collected in siloes across myriad stakeholders, including manufacturer, distributor, wholesaler and retailer, data could be shared across relevant stakeholders.

Through adding artificial intelligence to the platform, that data can be fed through a variety of algorithms to improve the supply chain further. Consider the 3 A’s progression of AI, as it evolves from being an assistant to an advisor to an agent, applied to a shipment of apples. As an assistant, the AI can enhance accessing the data through a chatbot interface – one can ask and receive answers to specific questions like ‘Where are the apples now?’ or ‘What temperature are they being stored?’ As the technology and application becomes more sophisticated, the AI can be an advisor and proactively alert the employee of potential issues. If the AI has detected a high likelihood of storms, it can advise rerouting the shipping freight or if the weather is projected to spike, it can recommend additional cooling. And as the AI learns and demonstrates a high level of aptitude, it can become an agent by acting upon its recommendations, rerouting or adjusting the temperature itself.

4 Smart Devices 

As the Internet of Things progresses and our lives are integrated with smart devices, a combination of blockchain
and AI will be used to decide how these devices act, interact, and transact. Sensors will be widely prevalent to
learn and ingest real world information, with AI used to train and improve the devices understanding and actions made from the data. When a refrigerator is out of milk and needs to communicate to a corresponding device its desire to purchase milk, a blockchain platform will facilitate this interaction. And just as consumers today use reviews on websites to evaluate the quality and trustworthiness of a site, AI will be able to look through each device’s history of transactions (hosted and secured on the blockchain) to determine which devices to trust, and even characteristics such as which agent most often delivers the milk quickest.

5 Identity

Accenture is a founding member of the ID2020 Alliance, a UN-affiliated public/private partnership committed to applying the latest in innovative technologies to provide verifiable digital identities to the 1.1 billion individuals that currently cannot prove who they are with any certainty. This and similar applications of blockchain technology for identity can be combined with AI to monitor the environmental conditions in a refugee camp or community health information and produce insights to guide care and support. As AI can more quickly digest and analyze this data, more accurate and timely decisions can be made to support the at-risk groups.

6 Healthcare

In healthcare, AI is revolutionizing diagnosis and treatment planning at scale. Early progress has been made with AI systems to improve cancer treatments, as well as Google’s DeepMind building capabilities to diagnose eye diseases through analyzing medical images. Smart, personalized medicine can improve health outcomes, but people are wary about sharing such personal data. For a standard hospital visit, data is likely collected by the primary care physician, the hospital, and labs where tests are processed, and that data could be lost, entered incorrectly, or be subject to hacking. By enabling secure and controlled shared access to health data through blockchain systems, patients can reclaim ownership of their data and allow access to it on a case-by-case basis. This would allow patients to benefit from AI-enabled personal care, while knowing their data is protected and encrypted.

Blockchain: redefining trust

Blockchain is a new type of database system that maintains and records data so that multiple stakeholders can confidently and securely share access to the same data and information. As such, it is changing the nature of boundaries between organizations.

Since the invention of modern databases in the 1950s, thegoverning business model concerning them has centered on trust. For example, Party A needs to have confidence that Party B (or anyone else) hasn’t unilaterally changed any data. Consequently, companies traditionally build data systems they can fully control and operate using a “messaging” based business model. In this case, Party A sends its view of the world in a “message” to Party B, and vice versa. Only when both parties can reconcile those views will they complete the business transaction. Blockchain is changing that concept of trust in data.

Through blockchain and other types of Distributed LedgerTechnologies (DLT), companies can now access a common shared data set that they and other stakeholders know they can trust.This new definition of trust emerges from several key blockchain concepts:

Provenance: Each participant with appropriate access can view the full history of a data element—from its inception through each stage of its lifecycle—including who introduced it to the system, all pertinent events and the key parties involved.

Tamper-evident: Thanks to sophisticated math and software rules, data is extremely difficult to manipulate without everyone knowing. As a result, participants can prove to themselves that the data has not been tampered with.

Control: Participants have the ability to specify access permissions at a data element level vs. to a traditional database, data table, or row level; allowing a significant increase granularity of control.

Security: Protection and control can be implemented at the data element level instead of the database or data table levels, making it much more difficult to penetrate.

Successfully melding AI and blockchain

Two new digital technologies could create synergies unlike anything the business world has ever seen, but tapping into that power could be challenging.

Companies that recognize the power of this combination will have to manage coordinated technology implementations and more complex transformations. To navigate the challenges ahead, leaders will need to think through several key decisions.

Dealing with privacy issues. AI thrives on oceans of data, and blockchain can expand that access and ensure information’s trustworthiness, but privacy concerns could scuttle initiatives before they’re even launched. For example, one experiment focused on AI and blockchain technologies has already created controversy by using patient data without consent. What’s more, the EU’s data privacy rules, which took effect in 2018, threaten
massive fines for organizations that violate them. Working with regulators and governments to demonstrate the value AI-plus-blockchain can deliver to individuals and society at large should be a mandate.

Thinking outside of the (corporate) box. AI needs comprehensive levels of data to function optimally, but most companies restrict the amount of information available due to trust issues. While blockchain offers a way to enhance trust and security, enabling shared access to data and securing this information appropriately require significant amounts of effort and resources. That puts a premium on understanding the value at stake in AI plays and creating a workable strategy to obtain it. Two new digital technologies could create synergies unlike anything the business world has ever seen, but tapping into that power could be challenging.

Preparing for a mega-mindset shift. Most leading companies are already hard at work digitalizing their organizations, introducing things like cloud concepts and big data analytics. This “stretching” of formerly static processes, policies and procedures can certainly help prepare organizations for the transition to human-led AI, but to achieve its fullest potential, companies must investigate and plan how to integrate it and blockchain effectively and embed these technologies into your overall corporate strategy to “pivot to the new”.

Pivoting to the new is a way of framing the digital age that demands companies exist in a constant state of change. That means a new approach to organizational change that enables companies to:

  1. Transform the core business to drive up investment capacity
  2. Grow the core business to sustain the fuel for growth
  3. Scale new business to identity and scale growth areas at pace

It’s a deliberate approach that can yield big results.


Blockchain helps deliver upon the promise of AI by providing new levels of data access, trust, and security.
Several organizations are already experimenting with this combination of technologies, but initiatives largely remain in the pioneering mode. As confidence increases and companies zero in on trapped value pools, the growth of AI-plus-blockchain plays will likely explode. In this environment, leaders need to stake an early claim to the talent, resources and capabilities their companies will need to succeed in this fast-moving new business world.



Accenture is a leading global professional services company, providing a broad range of services and solutions in strategy, consulting, digital, technology and operations. Combining unmatched experience and specialized skills across more than 40 industries and all business functions—underpinned by the world’s largest delivery network—Accenture works at the intersection of business and technology to help clients improve their performance and create sustainable value for their stakeholders. With 449,000 people serving clients in more than 120 countries, Accenture drives innovation to improve the way the world works and lives. Visit us at
Tackling Climate Change Using 4IR Technology

Tackling Climate Change Using 4IR Technology

By Matjie Lillian Maboya


The recent tornado in KwaZulu Natal and the 2012-2018 drought in Cape Town are just some of the natural disasters that have made it to mainstream media, showing that climate change is undeniable. The impacts of climate change have been felt worldwide and there have been multiple climate strikes and provocative talks by the likes of Greta Thunberg that bring to light just how little progress we are currently making to combat it. Parallel to this raging stream has been the advent of the fourth industrial revolution (4IR) which has gained momentum and carries the immense potential to transform our lives and amplify our efforts to address climate change. There are already multitudes of people using advanced technology to galvanise people to act on the ground in making the planet greener such as Mr Beast who launched a sophisticated tree planting campaign that saw more than 20 million trees planted worldwide. Indeed, the possibilities arising from the confluence of climate change and 4IR are plentiful, and so are the potential setbacks in addressing socioeconomic inequality.

The sheer power of tools brought by the 4IR such as big data and greater computing power enables us to integrate different forms of data that previously seemed irrelevant or disconnected. For example, in our attempts to reduce plastic waste that has a negative impact on the environment, we can draw data from plastic bag manufacturing companies, grocery stores that sell plastic bags and plastic recycling centres to understand consumer behaviour on the life cycle of a plastic bag. Processing such data on one platform can enable us to pick up trends about the location and frequency with which a consumer buys plastic bags and when we can potentially send him/her/them a timely reminder to take reusable bags from home on a day they are most likely to go grocery shopping such as on their payday. Combining existing climate data with greater computing power and statistical analysis enables us to draw nuances through the wide range of data sources such as in this example, making it possible to serve consumers better and also engage them in tangible ways to mitigate and adapt to climate change.

Similarly, the technology can be used to hold manufacturers to account and to also wring them into tangible actions to protect the environment. While the 4IR will transform our lives in many ways, some still will remain the same for a long time. For example, while the manufacturing of electric automobiles is on the rise, the cars continue to use rubber tyres which are often not recycled or properly disposed of. The use of 4IR technology such as the internet of things can allow for car manufacturers to add microchips to track the tyres so they can be located and collected when they reach the end of their usability period. Such measures will help to reduce pollution and conserve energy through recycling.

But, 4IR technologies are not the saving grace for all climate-related issues. While they allow for advanced disaster management systems through real-time tracking of weather systems, there are limitations. For example,  IBM has recently launched faster weather forecast systems that cover the globe and has thus been a leader in this endeavour. However, in cities that are under resourced even with these warnings, the city might not have adequate resources to evacuate people in time. Unfortunately, most of our cities are not built to withstand climate change-related disasters. Flooding events are one such example that highlights areas with poor drainage and although 4IR can give us early warnings about storms, there is still significant work to be done on a municipal infrastructure development level to build and maintain drainage systems that are more resilient to water-related disasters.

For example, “Greenhouse gas emissions” and “artificial intelligence” can hardly be translated into most South African languages. This already limits the potential for more people to get involved with shaping the conversations and shifting the necessary levers to spearhead change in both fields. Moreover, technologies such as cloud computing, 3D/4D printing and machine learning all require electrical and computing infrastructure which most of the world still does not have access to. This means that the 4IR directly benefits those who are privileged enough to access these resources, leaving behind masses of those who cannot access them. Similarly, knowledge of climate change and its negative impacts are split along socio-economic lines whereby; those in low-income groups are hardest hit by environmental depletion and natural disasters, while wealthier individuals are more knowledgeable and better capacitated to adapt to climate change. 4IR technology can be a way to bridge this knowledge gap through the deployment of technology that can run faster dissemination of bite-sized information packets about each climate-related disaster in a more affordable manner than mainstream media. It starts with the small decisions such as, who gets to sit on the panels about 4IR and climate change, to the nature of the end-user for which these technologies are designed to serve. Advanced robotics and machine learning will ultimately take in the biases of the people who design them. If these people are not the world’s majority, then we will continue to build a world based on ‘the exception’ while passing it as the ‘norm’.