Cryptocurrencies Regulation in Nigeria: Crypto Exchanges to the Rescue? by Popoola Mubaraq

Introduction

In 2017, two of Nigeria’s most important regulatory authorities — the Central Bank of Nigeria (CBN) and the Securities and Exchange Commission (SEC) released circulars denouncing cryptocurrencies. The circulars warned Nigerians of the grave risks involved in dealing with these digital assets. The then position of the regulators notwithstanding, digital assets’ popularity in Nigeria continued to soar. According to blockchain.com, Nigeria is now one of the fastest-growing crypto markets globally.

cryptocurrencies regulation in nigeria: crypto exchanges in nigeria popoola mubaraq digilaw

In September 2020, predictably, the SEC walked back on its earlier position and showed a willingness to regulate digital assets it considers securities — leaving the CBN alone in their previously jointly held stance. As a currency whose acceptance and usage is continuously growing, the CBN will inevitably have to step into the cryptocurrency space (as the SEC has begun) to play its role as the country’s foremost financial regulator.

This article seeks to explore and recommend a potential cryptocurrency regulatory/supervisory route for the CBN through Cryptocurrency Exchanges.

 

What are Cryptocurrencies and Crypto Exchanges?

A cryptocurrency is a digital asset (i.e. it rarely exists in physical form like paper money) designed to work as a medium of exchange.  Individual coin ownership records are stored in a decentralized ledger existing in a form of a computerized database using cryptography to secure transaction records, control the creation of additional coins, and verify the transfer of coin ownership.

A long-standing and important debate regarding cryptocurrencies revolves around their qualification as money. Proponents argue that cryptocurrencies already fulfill all the requirements of functional money as they currently serve as

  • a medium of exchange;
  • a unit of account; and
  • a store of value.

They further assert that because of this, cryptocurrencies are functionally money, even if not legally, since sovereign states across the globe continue to have exclusive power to designate legal tender.

A Cryptocurrency Exchange (Crypto Exchange) is a business that allows customers to trade cryptocurrencies for other assets such as conventional fiat money or other digital currencies. Crypto Exchanges also offer other auxiliary services to ease their customers’ crypto transactions and dealings, and although Crypto Exchanges are not the only avenue to transact in cryptocurrencies; the ease, safety, and order that they enable have seen them take a significant share of crypto transactions.

 

The Need to Monitor Cryptocurrencies

One of the strongest criticisms of cryptocurrency is that it is a potential enabler of a myriad of illegalities. This concern is fueled by the relative anonymity provided to users transacting on the blockchain. This presents a difficulty in ascertaining the identity of transacting parties — a very attractive situation to those looking to launder money, finance terrorism or transact in illegal trades (drugs, hacks, illegal pornography and even murder-for-hire).

To curb this already identified potential propensity for criminalities, cryptocurrency transactions should be monitored where possible to prevent harmful outcomes. Crypto Exchanges as identifiable business entities present a great opportunity to solve this problem by helping in unmasking transacting parties through standard Know Your Customer (KYC) requirements for their customers. Once the identity of transacting parties is easily determinable, further established financial sector safety measures like Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT) can then be implemented to curb criminal activities.

 

‘Other Financial Institutions’

The identification of Crypto-Exchanges’ potential to regulate cryptocurrencies is a significant starting point. It is however similarly important to legally bring them under the regulatory wings of the CBN. Fortunately, the Banks and Other Financial Institutions Act (BOFIA/the Act) offers ways out.

The Act gives the CBN wide powers to regulate not only banks but other financial institutions in Nigeria. It further gives the CBN power to designate businesses it deems fit as constituting ‘other financial institutions’. In line with this, the CBN has promptly designated certain businesses as financial institutions and consequently regulates them.

One business so designated as a financial institution is the business of a Bureau De Change, which deals in foreign currencies. The CBN, through regulating Bureau De Change businesses, monitors dealings in foreign currencies within Nigeria. As earlier noted, proponents argue that cryptocurrencies are already functionally money. If the CBN is to agree to these arguments and designate cryptocurrencies as foreign currency (in which case they still wouldn’t be legal tender in Nigeria), Crypto Exchanges automatically essentially become Bureaux De Change and subject to the CBN’s regulation.

Alternatively, the Act also gives the CBN power to directly designate businesses it so deems as financial institutions. The CBN can, without recognizing cryptocurrencies as foreign currency, designate Crypto Exchanges as financial institutions and consequently regulate them as empowered by the Act.

 

Proposed Limits to Regulation of Cryptocurrencies

The regulatory intervention in the crypto space must be strictly supervisory and not stifling innovation, as is sometimes the case with regulations. In recent times, we have witnessed innovative and groundbreaking use cases for cryptocurrencies. Notable instances include low-cost cross-border transfer of money. We should allow the sector to continue innovating, growing, and solving problems while its activities are monitored to prevent criminal activities.

Regulators must be careful to not approach this like business as usual. Over-regulating Crypto Exchanges and hindering innovation might frustrate users and chase them to other readily available mechanisms of dealing in cryptocurrencies outside of Crypto Exchanges which may currently be impossible to regulate.

nigeria cryptocurrencies
Image Credit: Cointelegraph

 

Conclusion

The American decision in SEC v. Shavers which recognized bitcoin as money offered a glimpse into an unavoidable future. Inevitably, Nigerian regulators eventually accept this future, since technology can neither be fought nor ignored. Crypto Exchanges present a unique regulatory opportunity for the CBN, which has been adequately empowered by the relevant laws; it must however approach this regulatory task carefully so as not to lose a golden opportunity.

 

Popoola Mubaraq is a legal practitioner with a keen interest in the intersection of law and technology. He graduated from the University of Ilorin in 2017 and was called to the Nigerian Bar in November 2018 and is currently a Counsel at The Law Lounge. To reach him, send a mail to at popoolamubaraq@yahoo.com

 

NOTES

  1. ‘Circular to Banks and Other Financial Institutions on Virtual Currency Operations in Nigeria’, January 12, 2017, REF: FPR/DIR/GEN/CIR/06/010.
  2. ‘Public Notice on Investments in Cryptocurrencies and Other Virtual or Digital Currencies’, January 12, 2017, http://sec.gov.ng/public-notice-on-investments-in-cryptocurrencies-and-other-virtual-or-digital-currencies/ (accessed November 15, 2020)
  3. ‘Nigeria attracts more bitcoin interest than any country globally’, August 8, 2020, Nairametrics, www.nairametrics.com/2020/08/08/nigeria-attracts-more-bitcoin-interest-than-any-country-globally/ (accessed November 15, 2020)
  4. ‘Statement on Digital Assets and Their Classification and Treatment’, September 14, 2020, https://sec.gov.ng/statement-on-digital-assets-and-their-classification-and-treatment/ (accessed November 15, 2020)
  5. Iris M. Barsan, ‘Legal Challenges of Initial Coin Offerings (ICOs)’, Revue Trimestrielle de Droit Financier (RTDF), No 3, pp. 54–65, 2017
  6. Section 130 of the Banks and Other Financial Institutions Act, 2020.

 

5 LOCALLY DEVELOPED AI APPLICATIONS IN NIGERIA

AI IN NIGERIA SERIES

While there are many training programs in Nigeria related to developing AI talent, it is usually difficult to point out AI applications that are locally developed and are already available in the marketplace. This article will hopefully be the first of a series of articles; I will be uncovering several locally developed AI applications in Nigeria. Some you might know, some you won’t. All in all, my goal in this series is to dispel beliefs that AI is an imported technology in Nigeria. Nigeria may not be pulling its weight compared to Ghana, South Africa, and Kenya in the African AI space, but there are notable strides that we should be aware of. Here are some of them.

5 LOCALLY DEVELOPED AI APPLICATIONS IN NIGERIA
DigiLaw Media

AGRICULTURE

Zenvus – AI-based solutions for farms

Most rural African farmers are not equipped with the right technical knowledge about the external factors affecting their crop yield. As such, they make farming decisions based on guesswork, cultural practices, and superstitious beliefs. The results make agriculture seem more like a gamble than a viable economic activity. Zenvus takes the gamble out of farming and makes it more viable for farmers that work with them. Data is collected using electronic sensors and special cameras about soil nutrients, temperature, moisture, drought levels, crop diseases, and other pain points in farming.

When I said that the cameras where special, it wasn’t just for the heck of it, they are. They were built by the company itself from scratch, due to the lack of available cameras in the market that could process crop vegetation index to meet their needed standards. So, they did it themselves, fitted with the necessary microprocessor for collecting this data. All this data is transmitted to remote cloud servers, equipped with algorithms that process and deliver predictions.

Notable amongst these predictions is when rain is going to fall. This is helpful for farmers because most of them cannot afford to irrigate their farms, and over the past few years, the commencement and duration of the rainy season in Nigeria have been erratic.

TRANSPORTATION

Lara – Step-by-Step Public Transportation Directions to any Destination

Most of us are familiar with Google Maps, and if you’ve had to depend on it for directions, you can attest to the fact that it can deliver inaccurate route suggestions. Earlier this year, when I moved to Abuja for Law School, I had to use Google Maps to locate my bank’s nearest branch since I was unfamiliar with the area, Bwari, to be precise. I was told (by Google Maps) that the nearest branch was in Wuse II, which is a long way from Bwari, for those familiar with the route. I later learned from a friend that I could have found a closer bank branch in nearby Dutse.

A local version of Google Maps that is more familiar with the nuances of location and our disorderly transportation system in Nigeria will be more successful. This is where Lara comes in. Lara is an AI chatbot that gives public transportation directions. For now, its use seems to be restricted to Lagos and Abuja in Nigeria, it is a locally developed AI.

I tried using it myself, as you can see in the images below, using Ogun State locations where I currently reside and random places. It only returned directions for Lagos and Abuja. You can try it yourself on www.lara.ng and see if your location is in its system.

 

Lara.ng Chatbot
Lara.ng Chatbot

This chatbot has an interface like that of WhatsApp, leveraging on this familiarity to help users to chat with it easily. It doesn’t just give directions; it also gives suggestions on the means of transportation to use and also gives estimates of how much each ride will cost from one point of Lagos or Abuja to another.

 

HEALTHCARE

Ubenwa – AI for crying babies

Ubenwa is a locally developed AI, an app that can detect birth asphyxia in 10 seconds. Asphyxia is the third leading killer of babies worldwide, claiming 900,000 lives every year. It is usually mistaken as the baby just crying until it is too late. This app can analyze the baby’s incessant cries to detect if they are just innocent, everyday cries, or a symptom of Asphyxia. So far, it has reported a 95% accuracy in test uses involving over 1,400 pre-recorded baby cries. It runs on a machine learning system that has been trained datasets of voices of babies crying who have asphyxia and healthy babies.

Using this, it takes the cries of a baby as input, analyzing its frequency and amplitude against its database to provide a diagnosis. It is noteworthy that Ubenwa is an Ibo word which means, ‘cry of a child.’ Traditionally, testing for asphyxia is invasive as it requires blood samples, which are tested. Anyone familiar with Nigeria’s public health system knows that most primary healthcare centers cannot provide the necessary treatments for a newborn baby.

An alternative like Ubenwa that is non-invasive is thus a welcome alternative. You only have to download the app. It doesn’t require technical skill to operate, then place it within the crying baby’s earshot for recording and analysis. The results are available in less than a minute.

 

FINANCE

Leo – a chatbot from UBA that aids in financial transactions

Leo is an AI chatbot that most tech-savvy customers of UBA might be familiar with. Accessible via Facebook Messenger or WhatsApp, you can carry out your everyday financial transactions like a random chat. For Nigerians (who use UBA) who wish to access this service, the number to add is +2349030002455. It’s also available in Uganda, Liberia, Ghana, Tanzania, Benin Republic, Cameroon, and Congo Brazzaville to UBA customers. It is currently available in 17 African countries

As of February 2019, Leo had over 1 million subscribers and had over 70 million conversations. We can be sure that the number must have doubled because it was launched in January 2018. It is available in French, English, and Portuguese, depending on the country of deployment. UBA has announced plans to make it available in Yoruba and other Nigerian languages. It is built on Natural Language Processing (NLP) – an AI method used to train algorithms to recognize and respond to queries in a given language. This is an example of Narrow AI. In other words, it only works in the specific domain it is applied in. If you guessed that this is the same method used in developing Lara, the transportation chatbot I spoke about earlier, then you guessed right.

Leo UBA Chatbot
Leo UBA Chatbot

Leo can respond to queries that involve banking with UBA, but cannot answer queries about GTBank or Stanbic IBTC. It also cannot give you advice about relationships, as I sadly found out.

You can use Leo to open a UBA account, apply for loans, check your account balance, confirm cheques, pay bills, freeze your account, and get notifications. Let me stop here, UBA did not pay me for the advert.

 

LEGAL PRACTICE

Eva Max-AI –  a legaltech research tool

Using NLP, just like Leo and Lara, this tool aid lawyers in obtaining judicial authorities from both Nigeria and the UK to aid them in preparing their cases. With increased usage, it can provide customized results for the user as it takes note of specific user behavior and searches patterns.

With Eva Max, a locally developed AI, you can ask questions on judicial authorities and relevant laws. It’s available on the company website. Once you open it, you’ll see a popup at the bottom with Eva Max-AI on it, which you can click to start using it. I took it for a spin and here’s what I got.

Eva Max AI
Eva Max-AI

 

One point that you might have noticed is that the AI applications in Nigeria revolve around the peculiar pain points in Nigerian society – agriculture, healthcare, transportation, finance, legal services. 3 of them leverage on Natural Language Processing, thus suggesting that this is an area of research and development that the Nigerian AI community is well-attuned to.

This list is by no means conclusive of all the local AI development in Nigeria. Some of you will be aware of other applications that are not on this list. You might even be working on one yourself.  If you are, I’d like to write about your work for the world to see – @Akin_Agunbiade

 

Can AI understand emotions: A Dive into Natural Language Understanding

Introduction

A hypothesis was well laid down by the founding fathers of Artificial Intelligence in 1956. The theory postulates that every aspect of learning or any other feature of intelligence can be in principle be so precisely described that a machine can be made to simulate it. As at the time this hypothesis was made, AI was about transitioning into a device having a vast amount of human intelligence, including language, vision, and reasoning. Emotions were not on this checklist. However, as technological innovations progress, consumers would grow to appreciate an artificial intelligence system that can accurately calculate thoughts, moods, and feelings, making our lives more comfortable with more personalized and convenient experiences in tune with our emotions. It might sound creepy, but it isn’t.

On a fundamental level, what distinguishes machines from humans is emotion. However, computers can read emotions and respond accordingly. Before proceeding, it is imperative to understand the concept of Natural Language Understanding (NLU).

Natural Language Understanding
Media by Digilaw

What is Natural Language Understanding?

Natural Language Understanding is a field of computer science that analyzes what language means, rather than merely what individual words say. This area of research and development relies on foundational elements from Natural Language Processing systems, which map out linguistic features and structures. Natural Language Processing is an already established field operating at the intersect of computer science, artificial intelligence. The ultimate of Natural Language Processing is to read, decipher, understand, and make sense of the human languages by machines.

Natural Language Understanding (NLU) seeks to intuit many of the connotations and implications that are innate in social communications such as the emotion, effort, intent, or goal behind a speaker’s statement. For instance, an Italian artificial intelligence company that specializes in natural language reading and semantics is using its AI tech to extract emotions and sentiment from 63,000 English-language social media posts to create a semantic analysis of people’s feelings during COVID-19.

What is Artificial Emotional Intelligence?

Artificial Emotional Intelligence or Affective Computing is a subset of Artificial Intelligence. Just as the name suggests, it deals with understanding emotions and using them as a competitive advantage across applications. It deals with measuring human emotions, understanding stimuli, and giving back an appropriate response. It is often argued that if we are to live and interact with robots comfortably, these machines should be able to understand and appropriately react to human emotions. Some companies are leading concerning Emotional Intelligence.

For instance, Affectiva is an emotional AI-based company established in 2009. They use the Webcam available to track the user’s emotions and moods. They identify the various twitches and subtle changes in micro-expressions for emotion detection. With appropriate permission, they use the data and recording through the Webcam. This way, Affectiva is then able to help advertisers target more effectively using the emotional quotient of the users. There is also CrowdEmotion, which is based is a London based company that was founded in 2013. The company strives to leverage the technology that uses emotional artificial intelligence. Their emotional engine helps their clients to recognize and understand human emotions.

Can AI understand emotions?

In its annual report, the Artificial Intelligence Now Institute, an interdisciplinary research center studying the societal implications of artificial intelligence, called for a ban on Artificial Emotional Intelligence in some instances. According to the researchers, such technology should not be used in decisions that “impact people’s lives and access to opportunities,” such as hiring decisions because it is not sufficiently accurate and can lead to biased judgments. So, what exactly is the problem here? The thing is Emotions are tricky because they tend to depend on the context. For instance, John might not be frustrated; perhaps, he is just thinking. Facial recognition has come a long way using machine learning, but identifying a person’s emotional state based entirely on looking at the person’s face is missing essential information.

The fact is that emotions are expressed not only through a person’s expression but also where they are and what they are doing then. These contextual causes are difficult to feed into even modern machine learning algorithms. To address this issue, there have been active efforts to augment artificial intelligence techniques to consider the context. Admittedly, the natural reaction to the ethical and privacy concerns entrenched with the use of Emotional Intelligence systems is to call for a ban is specific circumstances. Indeed, using AI for job interview results or criminal sentencing procedures seems dangerous. However, there are useful applications of AI in this regard. For instance, in helping spot warning signs to prevent youth suicide and detecting drunk drivers. It is for situations like this that concerned researchers, regulators, and citizens have generally stopped short of calling for blanket bans on AI-related technologies. The problem doesn’t end here.

Furthermore, Artificial Intelligence, in general, almost always have fairness, accountability, transparency, and ethical flaws inherent in their pattern matching. For instance, one study found that facial recognition algorithms rated faces of black people as angrier than white faces, even when they were smiling. Several research groups are tackling this problem, but it seems clear that the problem can’t be solved.

Conclusion

The fact is that Artificial Intelligence is already a big part of our life. Starbucks uses Artificial Intelligence in its rewards program and its mobile application to keep track of customer’s orders, the time such order was placed, the weather more to customize recommendations. This enriches the overall experience. Amazon revolutionized retail in part by using customer’s previous purchases to make recommendations about other products. These efforts are awe-inspiring. But the thing is they barely touch on the subject on how Artificial Intelligence could be utilized to understand our wants and needs with precision.

For instance, John is at a restaurant and is quite frustrated by the slow customer service. At the table, a small, AI-equipped computer with some sensors detect the frustrated facial expression on John, then pings another employee to come and assist. If the AI system tagged John particularly angry, the restaurant could offer a free treat. From detecting struggling school students in classes to suicidal youths on the streets, to drink drivers on the road, to individuals with suspicious intentions, the possibilities are quite endless.

What you should know about AI Mutation

Does Teenage Mutant Ninja Turtles ring a bell? If it does, you’ll remember how awkward-looking those mutated creatures were. If not, but you are familiar with mutants – primarily through tv – you most probably link mutation with bad luck. But, have you heard about AI Mutation? I ask because – as you’d later come to see – mutation, when done right, can result in groundbreaking innovation.

Caveat: Despite being about AI, this isn’t one of those difficult-to-read, dull, or scary tech articles you see around. So, relax and prepare to have a smooth ride all through.

AI Mutation

AutoML: 1st Gen Machine Learning

If you are a programmer or are close with one, you sure must be aware of the backend struggles that go into creating, and intermittently updating codes. But with the evolution of machine learning (AutoML), this struggle is being overcome.

With machine learning, AI tools are getting equipped with the ability to learn, optimize, and update codes automagically with human contribution limited to the constant provision of new data. That’s what reigns supreme in today’s age of tech development – though we are just barely scratching the surface of faster learning.

See Machine Learning as the human-like characteristics of artificial intelligence systems to learn, get better at tasks through experience and constant processing of data. Let’s say a programmer creates a program that can tell the difference between the picture of a dog and a cat.

Machine learning or faster learning is that which enables the AI system to form statistical patterns amongst other methodologies that help it almost-perfectly always distinguish dogs – no matter the specie – from cats.

With data from different cats and dogs species intermittently fed to the system, the system starts to decipher that cats have shorter noses, and dogs come in a variety of sizes.

Artificial Intelligence Mutation: 2nd Gen Machine Learning

What if there’s a need to create a system that distinguishes species of dogs? The simple answer is that the programmer again goes into seclusion and writes a new set of codes to that effect. Picture the resources that typically go into each manual programming projects.

Thanks to Google Developers, this may gradually be a thing of the past. With their discovery of AutoML-Zero, artificial intelligence systems can finally be encouraged to mutate and create newer algorithms from scratch with much lesser human input.

So, to create a dog specie identification AI system, the programmer only specifies the desired result, and the machine gets the work done by the reworking DNA of existing codes.

Using Darwinian evolution concepts, the mutant program pools together newer algorithms, which are results of random mathematical operation combinations. The program evaluates the performance of each algorithm in identifying dog species and compares it.

The top performers are retained, and others are discarded – sort of like survival of the fittest. The retained top performers have repeatedly mutated to birth much-better algorithms while the top-performing parents are abandoned. On and on the process goes.

Using tricks to speed up its processing, the AI mutant keeps churning out tens of thousands of newer, altered algorithms per seconds, all in a bid to find the perfect set of codes/algorithm that matches the programmer’s needs. All along the way, the system weeds out duplicate algorithm to prevent evolutionary dead-ends.

How Google Experimented AI Mutation

Developers at Google are the one working on this freakingly-smart concept that’s capable of leading to the evolution of AI systems that outperforms anything made by humans. In its released research reports at arXiv, the Google AI mutant experimental system churned out 1000 image-recognition algorithms optimized to identify a specific set of images.

After making 250 computers choose two best algorithms, the best of each chosen two algorithms with the highest accuracy survived, and the poor one got discarded.

The survivors were cloned and mutated to reproduce newer algorithms that interpret and respond to the training data in a slightly different way. The first-gen parents got discarded.

On and on, the process went, with mutated algorithms having slightly better results getting retained. And those that didn’t get discarded until the repeated mutation, birthed an algorithm with 94.6% accuracy.

All this is still, however, in the experimental stage.

How AI Mutation Ties with Darwinian Evolution

Ruminations birthed this interesting Artificial intelligence mutation concept on the Charles Darwinian human evolution. His reasoning, which has since been refined by several scientists, is that calculated alterations in DNA (genetic makeup) leads to either of an advantage or disadvantage to such mutant organism.

If the mutation is of a non-life-threatening nature that lets the organism survive and birth offsprings, such modification is passed along to slightly-optimized offsprings. If it doesn’t survive, the mutation dies with such a parent organism.

In the algorithm space, this process is referred to as neuroevolution – a process that attempts to recreate the “survival-of-the-fittest” human brain-building process in AI.

AI Mutation: Panacea to AI-related Challenges

The AI world is optimistic about the development and market viability of this 2nd-Gen machine learning capability. That’s because it would significantly help in resolving some of the challenges associated with today’s AI models.

Talk of the problem of bias in AI systems, which are unknowingly introduced by programmers when creating AI systems. Or do we talk about the resources – time and money – spent in continually developing and test-running newer sets of codes for more modern algorithms.

Conclusion

Despite the complexities of AI system development, AutoML-Zero could prove to be the much-needed innovation that propels AI systems into highly-efficient, cutting-edge systems they are meant to be.

The future we’ve always anticipated where computers can easily outsmart humans might be almost here. So, if anyone happens to ask if you’ve heard of AI Mutation, don’t say you haven’t.

 

Writer Bio

Ridwan Sharomi is an aspiring tech lawyer and freelance writer (for hire). He works closely with individuals and businesses, providing top-notch blog writing and ghostwriting services.

Need top-notch content for your brand? He’s just a click away.

HOW THE GUIDELINES FOR THE MANAGEMENT OF PERSONAL DATA BY PUBLIC INSTITUTIONS IN NIGERIA CAN APPLY FOR REGULATING ARTIFICIAL INTELLIGENCE IN NIGERIA

Introduction

In May of 2020, the NITDA (National Information Technology Development Agency) issued the Guidelines for the Management of Personal Data by Public Institutions in Nigeria, 2020 (hereinafter referred to as the GMPDPIN 2020).

Hey, don’t blame me if it’s a mouthful, I’m not the one that coined that name for the guidelines in the first place.

Don’t worry, when I’m the head of a government agency 20 years from now, I’ll make sure that any regulations or guidelines we issue have easy to pronounce names and acronyms, that’s a pinkie promise. For now, we work with what we have.

So, GMPDPIN 2020 (this sounds like what might happen if APC and PDP ever merged), here we go.

You know what, for this article, let’s call it GMP. Are you cool with that? Sure? Great. Now, let’s get down to business.

This Guideline was a follow-up to the Nigeria Data Protection Regulation (NDPR) 2019.

PS: You see how short and succinct that name and acronym is? The same agency then gave us GMP whatever. NITDA, if you read this someday, please up your game. Some of us might end up cursing our ancestors in the name of calling acronym.

Now the NDPR is meant to be Nigeria’s version of the EU GDPR. A regulation that stipulates what can be done to your personal data, who is licensed to handle it, how it can be processed obtaining consent and everything related. There are criticisms of how effective it is because is simply a regulation, and not an Act of the National Assembly, but they are not my concern here. My concern, as the title of this article suggests, is how the provisions of the GMP can impliedly extend to the regulation of Artificial Intelligence in Nigeria. But first, a short background

PS: If you want to read more about the NDPR and how it affects you, you can read my paper on Academia, boringly titled, ‘A Review of the Nigerian Data Protection Regulation (NDPR) 2019’. Please don’t judge it by its cover. The cover is not fine but the content is fun.

 

GUIDELINES FOR THE MANAGEMENT OF PERSONAL DATA

LEAD BY EXAMPLE

In my above-mentioned paper, one of the things I noted about the NDPR, just like others who might have studied it, was that it focused more on private organizations, private citizens, creating rights and a regulatory framework, whilst neglecting the public sector. We all know, that after the banks, telecoms companies, and FAANG (Facebook, Amazon, Apple, Netflix, and Google), the next best repository of our personal data as Nigerians, is the government. They might not be good at organizing and deriving value out of it, but they sha have it. So, you would expect that the NDPR would say something about how the government should use our personal data. They should lead by example, right? Well, it didn’t, and it got flak for that.

This is where the GMP comes in. It’s a subsidiary legislation, targeted at public agencies, which derives its validity from the NDPR, another subsidiary legislation. The NDPR is the map, the GMP is the compass on how to make sense of it if you’re a public agency.

Now that we’ve established the relationship between the NDPR and the GMP (you can download it here for personal study), let’s get into the real business of the day. Whilst reading the GMP, some of its provisions struck me because of how they unwittingly create some form of the basic regulatory framework for AI. If you’re not aware, AI is built on data, massive amounts of it. The recommendation engine on Netflix that keeps giving you the best suggestions on what to watch is built on data about your preferences, your movie history, and that of millions of users who share your preferences. The search results you get on Google are based on your search history, search location, and other factors, that boil down to data. This is why it is easy for a law or regulation about data protection to easily extend to Artificial Intelligence.

While we do not yet have any form of AI application in the Nigerian public sector (at least, none that is in the public domain at the time of writing), the provisions of the GMP that I’ll be talking about serve to pre-empt such developments, so that if at any time AI is introduced in the Nigerian public sector, we already have some legal standards to measure it against.

Here are those provisions I spoke about

 

Rule 2.1a -Processing of Personal Data

All Public Institutions are under an obligation to protect personal data in any incidence of processing of such data. Processing in the context of this Guideline means any operation or set of operations which is performed on personal data, whether or not by automated means, such as collection, recording, organisation, structuring, storage, adaptation or alteration, retrieval, viewing, consultation, use, disclosure by transmission, dissemination or otherwise making available, alignment or combination, restriction, erasure or destruction.

The keyword that brings AI into the mix under this provision is the word ‘automated’. To be clear, AI is not synonymous with automation. It is just one of the many ways, albeit the most efficient means of automation available. I can draw up a budget on paper, but that might take time, but if I do the same thing on Microsoft Excel or Google Sheets with a downloaded template, it will only take minutes. That’s automation. Instead of President Buhari going to the National Assembly every year with hard-cover volumes to present the yearly budget, he could just send an email to the National Assembly and livestream his address. We’re in the era of social distancing, aren’t we?

You get the point of automation, basically making processes more efficient and faster. Now lets bring that to AI and Rule 2.1a.  It provides inter alia, that where processing of personal data is by automated means, the public institution carrying out the processing is obligated to protect such data.

Let me illustrate.

In the course of the next few months, INEC (Independent National Electoral Commission) will conduct governorship elections in Edo and Ondo States. It is likely that in the runup to these elections, INEC will conduct continuous voter registration exercises to capture those who might have turned 18 since the last election or have not registered to vote for any reason whatsoever. Based on historical antecedent, this exercise will be carried out physically, with intending registrants queueing for hours, just so an INEC official can capture their data for the issuance of a voters card. For those of you who have gone through this, I’m sorry I took you down memory lane. But this process is grossly inefficient in the age of Google Forms. Its part of why younger Nigerians are largely not interested in voting or being registering for the process. If we can vote for BBNaija (Big Brother Naija) with a text message and our votes count, then we should be able to vote for President without queueing for hours. The older generation should get with the program.

Lets assume this year that INEC decides to implement some of the changes we want. They develop their version of Google Forms for citizens to fill in their personal data from anywhere. But there’s a problem. Now that the process of registration is fully online, how do you ensure that only those who are not registered or whose details have changed since the last process actually register?

To ensure that this is the case, INEC collaborates with NIMC (National Identity Management Commission) for the purpose of data sharing. They use an AI system that compares the NIMC database with the INEC database. Those citizens whose information is not available with INEC have most likely not registered. The AI system delivers this information to INEC. They can use the contact information to directly reach out to those Nigerians, encouraging them to use the online system to register, similar to the way NCDC (National Centre for Disease Control) was sending most of us ‘love messages’ a while back.

Just to be clear, the AI system I mentioned is not fictional, it actually exists and is known as ERIC (Electronic Registration Information Centre). It is used in over 24 states in the USA to identify potential voters and resolve identity discrepancies.

Applying the provisions of Rule 2.1a to this scenario, INEC will be obligated to ensure that they protect the data they gain access to and process by virtue of their collaboration with the NIMC. As such, anytime in the future that a government agency uses AI in some way in connection to personal data, they are obligated to keep it safe. I don’t want my personal data leaking online or somehow, a politician gets hold of it and starts using it send me campaign messages. If it happens, I will actually take legal steps, not ‘audio’ steps.

 

Rule 2.3f – Requirement of Consent

In the following circumstances, consent shall be required for the purpose of processing personal data, even where another legal basis for processing applies:

  1. before the data controller makes a decision based solely on automated processing which produces legal effects concerning or significantly affecting the data subject

In many small ways, our lives are run on intelligent systems and automation. The webpages that you visit when searching for information are ranked in a way that none of us really understands. How Google Search algorithm works is a discussion of its own, but the consequence of the results it gives us is that we hardly ever check the results on page 2 down to the millionth page. The choice of what goes on page 1 or page 1000 might not be life-changing or critical, but when you bring AI into the public space, the results that it makes can mean the difference between getting bail or a prolonged sentence.

An example of this is in the court case of Wisconsin v. Loomis, the defendant was sentenced to 6 years imprisonment. One of the factors upon which the judge premised his decision was the recommendation given by the risk assessment system (an AI system that is designed to pre-empt crime by identifying those most likely to offend, and recommending their removal from society by defined means. The system in question, known as COMPAS – Correctional Offender Management Profiling for Alternative Sanctions) that Loomis, the defendant should be incarcerated because he had a high-risk to reoffend.

You might be wondering how this links back to how AI might affect the Nigerian public space and requirement of consent that we should be talking about. I’ll get to that, but first, I have to explain how a risk assessment system works. Don’t leave me.

Risk assessment systems are built on data from the prison and police system of a country or state. In the Loomis Case above, COMPAS was trained using data from the prison system of the State of Wisconsin. For context, Loomis was an African-American. Are you getting the picture? We all know that blacks in America are frequently the target of police brutality and arrests. The George Floyd protests have driven that point home. When you frequently arrest people of Group A in a higher proportion compared to Group B, it follows that you will have more data about Group A. When you feed this data into an algorithm, it doesn’t know that the reason Group A is over-represented in a dataset is because of your bias against them. As such, when it processes this data, the results it will give are likely to tend against people from Group A. Do you get me?

The police arrests black people more frequently than the average white person. When a white person is before the court and COMPAS is introduced, COMPAS is likely to recommend a lighter sentence or bail for him because based on the data with which it was trained, white people are not prone to crime, since they are not heavily arrested. But if a black person where before the court, the opposite would be the case.

Now that you have a clearer picture of the risks of AI application in the public space, I’ll link it back to the Nigerian context and law. You can scroll back up now to read the quoted provisions. Have you done that? Good. It says that a Data Controller, before it makes a decision based on automated processing that might produce legal effects or significantly affect the data subject must obtain your consent. And to make it clear, this consent must be expressly obtained. This requirement is not found in the GMP but the NDPR expressly provides for it.

So lets assume that in 2030. Nigerian courts have embraced risk assessment systems. Before a judge of the Federal High Court can pass sentence based on the recommendation of such a system, the defendant or the accused in such a case must have given his consent. In this case, decision emanating from the automated processing has legal effects on him – a conviction or acquittal.

If in 2030, the University of Ibadan decides to introduce an AI system that sorts through the applications of thousands of students who want to study there in order to decide those eligible to write Post-UTME, it must obtain the consent of all the students before doing so. The decision of the system here might not have legal effects, but it can mean the difference between one more year at home or getting into the university early, as such, it has ‘significant effect’ as envisaged by the GMP.

Just to be clear, this technology already exists. Taylor University, in Indiana, USA, in 2015, started using an AI system, known as the Education Cloud, to not just screen applicants, but also target potential applicants for the purpose of direct marketing. It yielded positive results for them as they welcomed their largest class of freshmen ever in the fall of 2015.

 

Rule 2.9d – Privacy Policy

All Public Institutions with data processing responsibilities and functions shall have a privacy policy that provides the following details:

  1. description of technical methods used to collect and store personal information, cookies, JWT, web tokens etc.

This provision can extend to Artificial Intelligence by virtue of the fact that AI falls under the same class of technical methods that can be used to collect and store personal information. Remember the example I gave earlier about INEC using AI to collect data from NIMC? This provision would also apply in that context and similar situation. INEC would be bound to state in their privacy policy to disclose how their AI systems collects data from the NIMC database and stores it for the purpose of further processing.

AI can collect personal data and others using a variety of methods such as image recognition, training algorithms to comb through large swathes of data. A challenge that I foresee arising from this will involve describing the general workings of the algorithm or AI method in language that is simple enough for an average citizen to understand. It would require people who understand the technical workings of such systems and possession of effective communication skills to describe it to laymen.

Rule 3.1b – Rights of a Data Subject

No person shall:

  1. be tracked, traced, or be subject to automatic or digital decisions without a law of the National Assembly or consent of the subject;

If the Coronavirus pandemic had never happened, the import of this provision might be lost or easily set aside. But, Coronavirus is here, and the protection that this provision guarantees, no matter how weak, cannot be waived aside. In the past few months, Apple and Google announced an unprecedented collaboration to track users, using an application programming interface (API), a sort of backend upon which other apps can be built for tracking the user of the smartphone in question. Development of the actual tracking apps in question is left to governments or private companies who will tap into this common API that works across Android and iOS systems.

The way its supposed to work is this. This API (which is built on AI), via Bluetooth technology in your phone, keeps a log of the phones (and their users) thast you come in close proximity with. The logs will not collect personally identifying information, but random numbers that identify each phone (and by extention, its user). Lets assume that Mr. A, on the 17th of August, 2020, comes in contact with Mr. B at the Ojodu Berger Bus Terminal in Lagos, Nigeria. Mr. B later tests positive for the Coronavirus. Depending on the features of the app built on the Google-Apple API, Mr. A will be notified that he might be at risk of having the virus. The authorities may also be able to use the log from the contact tracing to locate determine the phones (and users) that Mr. B has come in contact with.

If you use an Android or Apple smartphone, this API is already live on your phone, It just might not be active yet. For Android users, go to Settings – Google – COVID-19 exposure notifications. For iOS users, go to Settings – Privacy – Health – COVID-19 Exposure Logging.

By default, it should be turned off. You should only be able to turn it on when you install or set up an app. This is where the provisions of Rule 3.1b come in. In the event that the Nigerian Ministry of Health, NCDC, or any other agency of government develops a COVID-19 tracking app, built on the aforementioned API, it would be illegal for them to use it track any Nigerian, except there is a law backing its development or you expressly give your consent to be tracked. A good example of a law that might fit this description is the Infectious Diseases Bill, which generated a lot of furore when it was first represented at the floor of the House of Representatives. Section 5(1) of the proposed bill grants the Director-General of the NCDC the power to institute ‘public health surveillance programmes’ or undertake ‘epidemiological surveys of people’, in order to ‘determine the existence, prevalence or incidence, or to determine the likelihood of a possible outbreak of any infectious disease’

If assented to, this law could provide a legal basis for the development or utilization of a COVID-19 tracing app in Nigeria, and as such, would not be in violation of Rule 3.1b

 

CONSEQUENCES OF ITS BREACH

What’s a law if it doesn’t have some sting? Rule 7.0  of the GMP provides for that as it provides that breach or non-compliance with its provisions would be an offence under section 17 of the NITDA Act 2007 and the NDPR 2019. So if we want to have a clear idea of what the sanctions, we have to visit those legislations. What section 17 generally provides for is that where an offence is committed under the Act by a body corporate (in this context, an agency of government), the CEO of such body corporate or any other person acting in such capacity or on his behalf will be deemed to have committed the offence, except he can prove that the offence took place without his knowledge or connivance.

Since the GMP is subject to the NDPR 2019, the penalties in the NDPR 2019 will extend to it. Any agency subject to the GMP is by extension subject to the NDPR 2019. Rule 2.10 of the NDPR 2019 provides that anyone who is subject to it and is in breach of its provisions would be liable to the following:

  • Where the breach involves 10,000 Data Subjects, a payment of the fine of 2% of Annual Gross Revenue of the preceding year or payment of the sum of N10 million (roughly $25,906 at the official exchange rate), whichever is higher.
  • Where the breach involves less than 10,000 Data Subjects, payment of a fine of 1% of Annual Gross Revenue of the preceding year or payment of the sum of N2 million (roughly $5,181 at the official exchange rate), whichever is higher.

 

 

IS THAT ALL THERE IS TO IT?

This is not to say that these are the only provisions in the GMP that can extend to AI. Like I said earlier, it is easy for any regulation or law about data protection or privacy to extend to AI, because it is built on AI. I chose these 4 out of an initial choice of 17 because they had a more direct tie-in with Artificial Intelligence than the rest, in my opinion. If you’re interested in studying the other provisions that also share a relationship with AI, though not as direct, they are Rules 2.2e,g, h; 2.3b; 2.4; 2.5; 2.6a – c; 4.0a, b, e; and 6.0. Again a link to download the GMP is here. If you’re able to study these provisions and those I discussed, I would love to hear your thoughts. Maybe you disagree. You can reach me on Twitter at @Akin_Agunbiade and on LinkedIn at Akintunde Agunbiade

 

REFERENCES

Data Protection Compliance in COVID-19 Times.

Introduction

It is no longer news that the world is currently battling the deadly coronavirus that has brought it to a standstill for months now. However, what you might find new and interesting is the correlation between the pandemic and Data Protection Compliance or even data in the first place.

With COVID-19 and the daily progress in artificial intelligence, indeed, the wave of a new normal is quickly sweeping across all areas of human life include. Every aspect is being touched, including data protection compliance. This article will show you how in subsequent paragraphs.

Data Protection Compliance in COVID-19 Times.
DigiLaw Media

Data and Data Protection

This is the gospel; data is everything, and everything is data. To be scientifically accurate, data has been defined by the Cambridge Dictionary as information, especially facts or numbers collected to be examined and considered and used to help decision making. Or information in an electronic form that can be stored and used by a computer. This definition affirms the multifaceted nature of data, it is vast, tangible and intangible, and it also points out its importance.

Data has been described as the oil of the digital era. It is so vital in this age that it needs to be protected, especially by the shields and swords of the law. Thus data protection and cybersecurity refer to the umbrella name of methods and processes employed to ensure the safety of available data. The underlying principle of the concept of data protection is to empower owners of data against unauthorized or undesirable use of their data.

Framework for Data Protection and Data Protection Compliance  

According to GDPR, Data Protection compliance refers to the need to comply with legal requirements regarding data processes.  Since data protection became a buzzword, regulatory frameworks have been developed all over the world to cater to this field.

To jealously secure its aims, most notorious amongst these regulatory frameworks, is the General Data Protection Regulation, commonly referred to as the GDPR. This regulation applies to all EU state members and has an extraterritorial effect.

In Nigeria, data protection is governed by the Nigerian Data Protection Regulation, which carefully draws a distinction between the data controller and data subjects and also emphasizes the importance of consent in data mining and usage.

Data and Covid-19

We all have been washing our hands and staying at home for the longest time now. But the European Data Protection Board opined on the 20th of March, that modern problem requires modern solutions, and one of humanity’s best bet against the deadly coronavirus is data.

Indeed, most countries of the world have employed data analytics solutions as a way to combat the coronavirus effectively. However, most of these solutions tilt towards the mining of sensitive private data, such as location, contact, surveillance, even health data in some cases.

For instance, some Asian countries, such as South Korea and China, now actively monitor the movement of their citizens through the use of CCTV and drones. In Israel, the ministry of health launched “the shield,” an app that serves the purpose of contact tracing.

The United States of America has also approached tech giants in the country to determine how technology can be helpful in this fight. Network providers in most countries, especially in Europe, are giving out customers data to the government as their quota towards defeating the virus.

While the legality of most of these acts by the governments of the nations of the world is still in question and their perpetration is hinged solely on the argument of their “necessity,” the effectiveness of these acts can not be swept under the carpet just quickly. So, the fate of data protection compliance and a  possible normalization of everything data protection compliance stands against in a post-COVID-19 world remains a source of concern.

Data Protection compliance issues

Hinged on the status  quo, certain data protection issues are likely to arise in a post covid-19 world, some of which include;

  • Authoritarianism; While it’s presently commendable that the government is collecting citizen’s data, a lot of important questions can not be left unanswered; how much data is being collected? What will happen to these data after the virus has been defeated? Will measures put in place now countries? These are justified fears, especially in countries that are notorious for human rights violations, that these data will be used indiscriminately and inappropriately in the future.
  • Unethical private use: There is also the possibility of these data being used by private tech companies for monetary gains,

Conclusion:

Conclusively it should be resounded that the objective of data protection and its compliance shouldn’t be sacrificed on the table of public interest. A balance should be aimed and achieved by data collectors and controllers, during and after the pandemic. Regulations put in place should be strictly adhered to while dealing with data.

The COVID-19 and Cryptocurrencies: Matters Arising

A little Background to COVID-19

As far back as 167 days ago[1], the SARS CoV2 has been unleashing terror on humanity. From its original roots in the Chinese city of Wuhan, COVID-19 has inexorably spread to the nooks and crannies of geographies lived thereon by humans on planet Earth. The Chinese virus – as Donald Trump often refers to it – continues to leave in its trail quite a significant amount of casualties, ranging from death to economic woes such as bankruptcy and national recessions, amongst other challenges.

How does this relate to cryptocurrencies? Well, the simple answer is that COVID-19 is all out to disrupt – change the ways, lifestyle, and everything relating to humans, cryptocurrencies not excluded. The pandemic is actively rejigging and changing how humans hitherto related to cryptocurrencies, as it brings to the fore the inevitability or unavoidability of change in narratives. You’ll come to understand more in a sec.

The COVID-19 and Cryptocurrencies

Cryptocurrencies: Much Touted Hygienic Measures

Even if we agree to tentatively take eyes off the filth that comes with money made unethically, one truth still stands tall – money is literarily so dirty. Yes, those banknotes we all carry about in our pockets and wallets to be used in the exchange of goods and services. So, because of the cotton materials used in making them, it becomes easier for them to gather filth and microbes. Money changes hands in banks, homes, restaurants and every other place you can think of, touching every surface that there is, as well as collecting, carrying, and transferring pathogens from one person to the other. And, it’s not like this much-sought but germ-infested payment means receives intermittent scrub downs as we do for other germ-infested mediums and surfaces such as water closet units.

As if the above isn’t enough, that which even makes the situation nastier is that when persons infected with COVID-19 touch surfaces, they easily pass on the virus to such surfaces – banknotes inclusive. So, if an asymptomatic or asymptomatic person gives you a thousand Naira banknote and you collect it, your risk of getting infected rises to 90%. In societies like Nigeria where there still exists a preference for banknote exchanges in day-to-day commerce, you can imagine the huge number of people that would have contracted the virus through banknotes alone.

This reality accounts for why the People’s Bank of China encouraged a switch to electronic payments as at the time the virus raged mercilessly in Wuhan, China. Even when China finally managed to weed out the virus – while the rest of the world continued to suffer unabatedly – the country suspended the outflow of banknotes from major infected cities for at least 14 days. During that time the notes are sterilized with ultraviolet light and heat to destroy whatever COVID-19 pathogen may still be stuck on them.

Now, for the rest of the world still grappling with the COVID-19 pandemic, cryptocurrencies adoption and usage is a veritable means for inhibiting or limiting bank notes-related spread of the near-fatal virus. This way, we can limit the danger of people coming into contact with the notes that carry the virus.

One Step Forward, Multiple Backward

At this point, you must already be fantasizing about how valuable cryptocurrencies must be now and how crypto traders must be smiling to the bank. Of course, we all know that the mass adoption and trading of a product brings with it higher profitability for dealers of such currency – especially those who bought it when the cost price was so low.

Unfortunately, that is nowhere near reality. Holders of the popular cryptocurrency, Bitcoin, have been counting their woes since the novel virus went on a global rampage. Within the few months that the virus has induced a global shutdown of economic activities and a recession seems to be in the offing, Bitcoin has suffered record – level price falls.

Now, the reason for this intermittent and groundbreaking fall is not unrelated to the reality of this uncertain time. In times like this, people are driven by fear and therefore try as much to move away from investing in risky assets. And we all know that pandemic or no pandemic, Bitcoin is prominent for its price instability. It can, therefore, be said that bitcoin magnets have managed to sell off their bitcoin assets all at once to invest in stable assets such as gold.

Just as well, many small-scale bitcoin owners that invest in Bitcoin as side hustles, have had to sell off their bitcoin units to buy extra supplies –  such as food, medical products – and have liquid cash at hand with which they can cover day-to-day expenses since the varying lockdown measures in most countries have prevented much of the working population from working and making money.

The Probable Bullish Outlook – Going Forward

Now, this author is no prophet of doom, but if this pandemic drags on for far too long, cryptocurrencies may take precedence over electronic transactions denominated in domestic, national currencies.

The above is feasible because, whereas many countries are depleting their financial resources to fight the pandemic through social intervention measures and viral fighting funds, no meaningful economic activity is ongoing to replenish the huge amount that is being expended.

It’s thus safe to say that when this pandemic becomes history, many countries would most likely plunge into financial crises as the worth of national currencies take significant hits. Citizens would by that time lose faith in their national currencies, and most reasonably resort to cryptocurrencies as a store of their money. And this isn’t theoretical or armchair reasoning – it has once played out like that in the past.

In 2013, Cyprus experienced a significant financial crisis that disillusioned its citizens. With the domestic currency having failed them, citizens turned to cryptocurrencies for succor. Astonishingly, bitcoin trading went as high as 87% within that period.

It also played out in Turkey in the year 2018 when the Turkish currency, the Lira, steadily spiraled down in value. Cryptocurrency trading at that time rose to unprecedented levels in the Middle Eastern country.

In Venezuela too, the cryptocurrency adoption as at the time the oil-producing country went into its 2019 financial crisis, was pretty much unheard of in history. Despite the free fall of the Bitcoin cryptocurrency at that time, Venezuelans saw the coin as a much better and superior store of value to the hyper dash inflated domestic currency –the Bolivar.

So, God help humanity be able to recover as soon as possible in the aftermath of this pandemic or national currencies may start to make the ground-breaking hits that would pave way for global crypto adoption than humanity has ever seen.

For crypto-pessimists who’d rather hedge their bet on humanity’s switch to gold rather than crypto, let’s hope your precious stone comes in handy when you need to complete seamless transnational transactions.

Playing Your Part in the Fight Against the Common Enemy

Despite the many scientific unknowns regarding COVID-19, some facts still hold true. These agreed truths are what we all should focus on while we leave science to figure out the unknowns.

Like it’s been severally submitted in books, the observance of the trio of body, social, and environmental hygiene by individuals go a long way in inhibiting the further spread of the virus. It is important that we all adhere to these many medical recommendations, and work together to save humanity from the common enemy.

Bottom Line

In all, no one has and no one would be able to perfectly predict how these would turn out. Cryptocurrencies were created and destined to save the world from recessions – such as the one that is, unfortunately, lying in wait for most countries when this all ends. It looks like that destiny would unfold sooner than the later that we all thought it would take. Now’s perhaps the time for you to do that research and make that investment in the cryptocurrency of your choice.


[1] The virus broke out in Wuhan around the 12th of December, 2019 –according to Wuhan Municipal Authority-   but was only reported to the WHO on 31st December, 2019

Why We Need Education Technology For Tertiary Education.

            Examining the terrain of the traditional system of learning as against Education technology, one can conclude that it is not so effective. It has a wide range of defects such as encouragement of mechanical learning, unnecessary cramming and the fact that it is largely expensive

Additionally, when compared to an Online learning platform system, a traditional institution would always be restricted by enrollment capacity, which is the number of students that can be accommodated at a given point in time.

This article effectively argues that the incorporation of online platforms by tertiary institutions expands its enrollment capacity and widens the access to quality of education, thereby making formal education a human right rather than a luxury.

Why We Need Education Technology For Tertiary Education.

An exemplary view of the Nigerian Educational System: Enrollment Capacity

Let’s take a close view of the Nigerian institutions which are classic examples of traditional institutions. Obafemi Awolowo University, Ile-Ife has an enrollment capacity of about 35,000 students. That is, at every given point in time, the institution cannot afford to accommodate more than 35,000 students.

In a country where education is a luxury, this limits access to quality education. Additionally, the University of Lagos has an enrollment capacity of about 60,000 students which is quite fair compared to OAU.

 In contrast, the National open university which operates primarily online about 500,000 students enrolled. Clearly, it is no surprise that the National Open University of Nigeria is the only school running in Nigeria with the necessary closure resulting from the ongoing Coronavirus pandemic.

             So many students right now don’t get to go to any classroom either because they have no money, it’s too expensive and most importantly because there is no space for them. But the question is;  since university buildings are too costly, why not operate an online learning platform? Almost all of the eight Ivy League universities offer some form of online courses, certificates or degree programs.

Education Technology in Nigeria Today.

National Open University is an interesting example for some reasons. Students of NOUN make use of the school’s E-Portal for virtually everything except writing exams. Tests are taken online, materials are downloaded online, school fees are paid online and so on.

This gives students the advantage of learning at their convenience which is particularly advantageous to students with part-time jobs or families to cater for. The fact is that enormous amounts of information are now available online for free, ready for watching, listening or reading at any time, by anyone who’s connected. (Nigeria has an estimated population of over 193 million, 162 million mobile subscribers, internet penetration rate at 84%, about 104.6 million internet users as of August 2018).

Expanding the Use of Education Technology In Nigeria

 The Impact of learning environments concerning learning outcomes has constantly been explored by researchers of education. For example, Ramsden and Entwistle (1981) empirically identified a relationship between approaches to learning and perceived characteristics of the academic environment. Haertela and Walberg (1981) found correlations between student perceptions of social psychological environments of their classes and learning outcomes.

Web-based technology has noticeably transformed the learning and teaching environment. Proponents of online learning have seen that it can be effective in potentially eliminating barriers while providing increased convenience, flexibility, customized learning over a traditional experience.

If there is anything the ongoing pandemic has shown, it’s that online learning should be encouraged by tertiary institutions. In order to control the spread of the coronavirus (COVID-19), a number of Foreign institutions have resorted to remote learning on online platforms. The question is why weren’t we doing this before?

Why do we need to embrace Education Technology?

According to statistics, Tertiary education enrolment rates globally are expected to rise rapidly by 14 million new students every year from now until 2030. This would require 13 new universities to be built every week, 700 each year, each serving 20,000 students if they are all going to be educated face-to-face. That’s not going to happen. The education sector needs to think ‘are we going to deny these learners, or are we going to offer them the education they deserve via an online platform?’

Conclusively, the role of technology cannot be overemphasized. There is a need for technology disruptions in Nigeria’s educational space to ensure flexibility and easy accessibility to education. However, it should be noted that this article does not intend in any way to underscore the utilization as well as the purposeful use of classroom learning.

It simply stresses the importance of complementing the existing traditional classroom learning with online interactions to extend the enrollment capacity of institutions thus widening the access to quality education.

References

https://www.google.com/amp/s/www.digilaw.com.ng/2019/09/10/the-future-of-formal-education-is-edtech/amp/

https://twitter.com/StatiSense/status/1216607038786211841?s=19

Incorporating online discussion in face to face classroom learning: A new blended learning approach Wenli Chen and Chee-Kit Looi Nanyang Technological University

https://www.uopeople.edu/

Educational Technology: Why is it such a big deal?

Wikipedia says educational technology is the use of physical hardware, software and educational theoretic to facilitate learning and improve performance by creating, using and managing appropriate technological processes and results. But to most of us, educational technology is just some elaborate white people thing.

Basically, the aim of educational technology or EdTech is to help kids learn faster and better. Now, what’s on the minds of most people especially older people would be “but we learned without all these things, today’s kids are just so lazy!”.

Digilaw Educational Technology

Evolution of Education Technology

Education has evolved and the children for whom these educational materials are being developed do not understand its usefulness. I have a personal experience with that. Back when I was in secondary school, this educational technology thing was the new wave. So we had televisions and a CPU (that was connected to the television) installed in our classrooms.

The school had to take down the televisions and replaced them with projectors! The point is, we did not exactly see the need for educational technology because we had the traditional way and as far as we (student and teacher alike) were concerned, it was working perfectly and needed no change or modification.

But there’s so much that embracing educational technology can do for us. The truth is, whether we like it or not, technology in the world is going to keep evolving. And if students are going to survive in a world with so much technological evolution going on, they have to be properly equipped with the ability to learn using technology.

If your excuse for not taking an online class is “I prefer when I can see the teacher face to face”, then you probably are a 21st-century caveman. Technology has permeated every single part of our lives including education.

The best thing for us to do is to accept it and learn how to properly and effectively utilize it. As well as properly explain it to the students for whom so it is not abused.

Statistical Reports on Educational Technology

EdTech works! Countries like Kuwait, Taiwan, and Indonesia etc., have employed this approach, and their quality of education is great.

A 2019 report by Cambridge International shows that EdTech is growing, with 48% of students reporting that they use desktop computers in the classroom. While 33% of students use interactive whiteboards, 20% use tablets, and 42% use smartphones. This report was based on an online survey involving nearly 20,000 teachers and students from other countries

The report also states that gamification is enhancing the learning process and creating an environment that helps students to communicate. The EdTech market is currently projected to grow at 17% per annum to $252 billion by 2020. Ladies and gentlemen, EdTech did not come to play.

Benefits of EdTech

Educational technology exposes students to a multitude of helpful resources. It gives them access to information outside what is in the books they are given. It is no news that research has been made easier with the use of search engines like google.

Will a student be real quick to google the definition of a term? Definitely. Will a student be willing to spend the entire day in the library searching for research material? Err you’d probably have to attach a whole lot of marks to that exercise to make a student do it.

Educational technology brings so many educational materials to your fingertips – literally. There are online courses, websites with a lot of helpful stuff, applications and so much more that aid learning.                                                                         

It also helps to quicken the learning process. Students who do not understand what was said in class can easily read it up online, instead of delaying the teacher who might have to explain the same thing about six different times to six different people because they do not understand it yet. With educational technology, curricula can be covered in due time with the students still learning effectively and at their own pace.

Also, the expanding EdTech market shows that it is an investment goldmine. We cannot simply ignore or refuse to accept EdTech because frankly, there are very few, almost non-existent reasons to do so. Educational technology is important, a big deal and should be adopted and used at every educational level.

Conclusion

Finally, technology has become part of our lifestyle. Students constantly engage with technology while they are outside the classroom. Almost everybody has phones now, and we spend a lot of time on our phones, as well as other gadgets. Instead of demonizing educational technology, it is better to help students to make some of the time spent on these devices count by introducing them to and encouraging them to find educational stuff that will help them in the long run.

Technology is a primary part of every industry now, and there is no way around it. Knowledge of technology has gone beyond basic computer skills, and the current trends in EdTech such as gamification, learning analytics, virtual reality (VR) in education, immersive learning, etc. show that EdTech is up to the task of helping students have a deep understanding of technology.

6 Powerful Women in Technology

6 Powerful Women in Technology

As the world progresses daily, the dynamics are changing, and we cannot overemphasize the power of technology in the world. As we celebrate International Women’s day, we celebrate the impact that women in technology over the years. A lot have worked as CEOs, CFOs, CTOs, etc. in some of the biggest tech companies existing today. 

Some have created innovative, disruptive, and problem-solving technology or founded awesome companies today. Here are the most powerful Women in Technology in Nigeria, Africa, and the World.

Odunayo Eweniyi

Odunayo Eweniyi is currently the Co-Founder and Chief of Operations at PiggyVest. Graduating from the university with a first-class degree in Computer Engineering, she defied the normal process of getting a 9-5 Job and ventured into the start-up world.

Over the years, she has co-founded several companies, of which the most successful are PiggyVest (a fintech company) and PushCV.com (One of Africa’s most extensive database for Prescreened Job candidates). 

Odunayo Eweniyi: Women In Technology
Image Credit: Piggybank.ng

In 2019, she was listed on Forbes “Africa 30 under 30 in Technology”, SME Entrepreneur of the Year West Africa by The Asian Banker’s Wealth and Society, and she is the youngest Nigerian on Forbes Africa list of 20 New Wealth Creators in Africa 2019. In honour of her work, she was named one of 100 most inspiring women in Nigeria 2019 by Leading Ladies Africa, one of 50 most visible women in Tech by Tech Cabal in 2019.

Odunayo is passionate about the inclusion of women in technology by working with hubs and female-focused networks, including For Creative Girls, GreenHouse Labs, She Leads Africa and many others. She likes twitter, and you could connect with her @oduneweniyi

Rebecca Enonchong

Rebecca Enonchong is the Founder and CEO of AppsTech. She was born in Cameroon. However, moved to the US as a teenager, where she completed her education with a Bachelor of Science and a Master’s degree in Economics. After her training, she worked in places like the Oracle Corporation and the Inter-American Development bank.

Rebecca Enonchong: Women In Technology
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In 1999, she started her company AppsTech whose goal was to provide enterprise application solutions. The company expanded to several countries in the world, including her native home Cameroon.

Rebecca has received several awards and broad recognition for her work in promoting technology in Africa. In 2002, she was named “a global leader of tomorrow.” In 2014, she was listed by Forbes as one the “10 female tech founders to watch in Africa”.

Presently, Enonchong sits on the board of several tech companies. Apart from being the founder or AppsTech, she is also the founder of I/O spaces, the chair of ActivSpaces and Afrilabs. She is a founding member of the African Business Angel Network. she is one of the most powerful women in technology in Africa.

If you are looking for somewhere to get the latest African Tech news on social media, you should check her account on twitter @africatechie.

Ursula Burns

Ursula Burns is one of the most influential women in technology in the world. Born in New York City, she obtained a Bachelor of Science in Mechanical Engineering and later a Master’s degree in the same course from Columbia University.

She started her career at Xerox as an intern In 1980. She then became a full-time employee, and as the years went by, she grew from Executive assistant to vice president of global manufacturing. Ursula became senior vice president of corporate strategic services and later president of business group operations.

Ursurla Burns: Women In Technology
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In 2007 she became president of the company, and in 2009 she was named CEO. In 2009, she was appointed by President Obama to lead the White House National STEM program.

She served in that capacity from 2009 to 2016. Burns has sat and still sits on the board of Numerous companies like Diageo, Teneo and as of September 2017, she joined the board of directors at Uber

Presently, she is the Chairman and CEO of VEON, the world’s 11th largest telecom service provider by subscribers.

Jasmine Atenuis

Jasmine Atenuis is the founder of an Artificially Intelligent chatbot company called Recast.AI. This French start-up develops natural language processing technology that allows the machine to understand humans. Jasmine Originally studied Art at the university.

Jasmine Atenuis
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Years later, she stumbled upon 42, a progressive programming school where she met her co-founders. The company was acquired by software giant SAP in 2018 after two years of existence and one round of seed funding. 

Jasmine is 28 years old, and she lives in France. She believes Art and coding are similar, as both give you the medium to create something from scratch. In 2018, she was Forbes list of Europe’s Top 50 women in Tech and the world’s top 50 women in Tech.

Ginni Rometty

Virginia ‘Ginni’ Rometty is a Tech veteran. Not just because she is the Chair, CEO, and president of IBM but because she is an experienced technologist and business executive. She earned a degree in computer science and electrical engineering from Northwestern University in 1979.

Ginni Rometty: Women In Technology
Image Credit: Forbes

She started her career at the General Motors Institute, working in applications and systems development. In 1981, she started working at IBM as a systems analyst and systems engineer. Over the year, she climbed within the ranks from a general manager to senior vice president of global business services. Later, she became senior vice president and group executive for sale, marketing, and strategy.

Ginni continued to grow in the company until she became the CEO and president in 2011. In January 2020, it was announced that she would be stepping down as CEO to be replaced by Arvind Krishna

In 2018, she was Forbes list of America’s Top 50 women in Tech and the Time’s magazine 6th most influential person in technology. In 2012, She was ranked by Bloomberg as one of the 50 most influential people in the world. She spearheaded IBM’s transition into a data company.

Anne-Marie Imafidon

Anne-Marie Imafidon is what the world would classify as a genius. At age 11, she passed two A level examinations in mathematics and computer science. She received a scholarship to study mathematics at John Hopkins University and later obtained a master’s degree in the same course from the University of Oxford.

Anne-Marie Imafidon
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Imafidon worked briefly for Hewlett Packard, Deutsche Bank, and Goldman Sachs. She founded Stemettes in 2013, an organization aimed at championing women in STEM.  She also co-founded Outbox Incubator: the world’s first tech incubator for teenage girls. This has supported 115 young entrepreneurs to date.

Forbes recognized Anne-Marie as one of the world’s top 50 women in Tech. She was appointed Member of the order of the British Empire in the 2017 New Year Honor for her services to women within STEM Careers.

Conclusion

As we celebrate the International Women’s Day #IWD, we encourage every girl, lady, or woman to challenge themselves to do great things. To break out of the status quo, imagine, create, innovate, and be relevant because women before have done it.

Statistics from ‘The Catalyst’ shows that there are more men in STEM-related careers than women, but that is gradually changing. At Digilaw, we have a gender ratio of 36:64 (Male: Female), which is not a norm in this field.

We achieved that gender ratio tilted in favour of women by intentionally encouraging women to apply.  We found that when you encourage women to get involved, they will get involved. Some might argue that this isn’t balanced either, but we are working towards that too.

Women OF DigiLaw 2020
Women OF DigiLaw 2020

Imagine how powerful we would be if we harnessed the power of everyone to make the world better. An Equal world is an Enabled world.

As we celebrate women all over the world, we celebrate the Women of Digilaw, who have made great contributions to the team. Happy International Women’s Day! #IWD2020 #EachForEqual #WomenOfDigilaw