Eva Super Max LegalTech Research Tool


From time immemorial, legal research has played a vital role in the legal profession. Whether in courtroom advocacy, in-house soliciting, or academics, research is unavoidable. And here’s where legaltech research tools come in.

Day-in day-out, lawyers ceaselessly confront newer legal questions, and disputes, the likes of which have never been seen. But through efficient research, solutions and arguments are proffered to overcome these challenges.

It doesn’t matter that you are a law student, intern, or barrister and solicitor of the Supreme Court. The ability to conduct exhaustive and fruitful research remains an essential skill. More so, it’s a determinant to how far an individual can go in the profession.

Today, various legaltech research tools seek to address various angles and needs of legal research. This intervention of tech in the conservative profession of law brings with it much-needed ease to the traditionally-difficult nature of legal research.

It the recent past, legal researchers had to run through volumes upon volume of law books to find answers. But since the advent of legaltech, things have changed for the better.

If you check through the portfolio of this writer at Digilaw, you’d discover contents that shed more light on what legaltech is about. That includes the evolution of legaltech and how legaltech helps lawyers stand-out in the profession.

Eva Legaltech Research Tool

One of the simplest-to-use and inexpensive legaltech available in Nigeria is Eva -an artificial intelligence legal research assistant. The voice and text-activated AI legal research tool eases the burden of legal research. It does this by providing judicial and statutory authorities of Nigeria and the UK.

LegalTech Research: Eva Super Max
Eva Super Max website

Its distinct functionalities include: natural language processing, machine intelligence and analysis, and many more. In simpler terms, it is capable of understanding and generating results for inquiries worded in human conversational tones. It also has the capacity to study and profile users’ peculiar search behavior to assist in bringing up user-customized results in the future.

So, be it Supreme Court, Court of Appeal, or other appellate courts’ decisions, British locus classicus, or Laws of the Federation of Nigeria, the Eva Supermax legaltech solution has got all your legal research needs covered.

Through the eyes of the CEO

In a chat with the CEO of the company, Mr. Osili, he mentioned that his team developed the legal research assistant to fill the knowledge-gap amongst legal practitioners.

He recalled that the idea to develop the legal research assistant stemmed from a WhatsApp platform he created long ago. The intent was to use the same in addressing pertinent legal questions amongst new wigs.

At first, the provision of timely answers to these questions was feasible. But as the platform grew bigger and questions trooped in endlessly, timely answers became unfeasible. The endless cycle of unattended inquiries by lawyers thus led himself and some others to set up Ivy Artificial Intelligence. In collaboration with Facebook, Google, and other tech giants, the legal assistant tool was birthed.

How the LegalTech AI research tool works

As you already know, this legal research AI tool is a reserve of Nigerian law –including judicial and statutory authorities. Its parent company, Ivy Artificial Intelligence, currently has two AI solutions in its coffers:

• AI Search
• Eva Chatbox

Using the AI search option
When you visit the website, scroll down and tap the Get Started button. The AI Search interface would appear, with a white search box where questions and inquiries can be inputted.

Assuming a user has been retained in a dispute regarding whether a bank loan debtor has fully fulfilled his credit facility obligations or not. This tool eases the search for legal authorities on proof of payment of bank loans.

Simply input ‘bank loan proof of payment’ in the AI search box and thousands of authorities would come up. By default, the tool is programmed to bring up the Supreme Court and Court of Appeal decisions. Alternatively, one may restrict the search results to either of the Supreme Court or Court of Appeal modes to confine the search results to decisions of either of both courts.

Using the Eva Chatbot option

Another way of using the legal research solution is through Eva Chatbot. It was originally built to furnish authorities on the Nigerian law of evidence but has lately been updated with the Laws of the Federation of Nigeria.

The chatbot simulates a conversation between a regular librarian and a library user, where the former guides the latter on how to quickly and effectively find resources. But this librarian isn’t your standard library guide because it – in addition to teaching the how – helps to fetch the needed resources.

To get a feel of it, go to the website and tarry a bit for a few seconds. A yellow messaging overlay similar to that of the FB messenger logo should surface shortly after with a ‘Hi! How can I help you ?’ message.

Tap on the message box and input your Facebook login details when prompted. An FB-like chatting interface would come up, with tips on how the chatbot can be effectively used.

The chatbot is said to be capable of conversing with a million users at a time, with no lag.

How the tool fares with other legaltech research tools

Just like Ivy Intelligence CEO reiterates, Eva competes with the likes of Law Pavilion, Timi, and various other Nigerian-based legaltech tools. What however distinguishes these legaltech tools from others, lies in its reliance on artificial intelligence and machine learning.

Just as well, it also provides for distinct user experience by way of the inclusion of the ‘Dark Mode Feature’. This darkens bright displays to reduce eye strains and stress.

Additionally, the availability of English Court decisions such as the Court of Chancery, UK House of Lords, etc, makes the tool a much more useful and comprehensive research tool.

Pricing implication of the LegalTech research tool

Well, it wouldn’t be exaggerative to mention that this tool is one of the most affordable amongst its competitors in the market. With a subscription of seven thousand Naira, users get year-long unlimited access to the tool. Similar law reporting tools in the Nigerian jurisdiction aren’t so competitively cheap or affordable.

What lies ahead of Ivy Artificial Intelligence

Ivy Artificial intelligence is a legaltech-driven company that has its sights on the release of innovations that ease the job of legal professionals. To cement its position on the map of the legaltech space, the company hopes and expects to turn out more legal tech solutions in the very near future.

The AI industry in Africa: The booming startups and indigenous AI promotion Organisation.

Africa as the hub for most of the world’s natural resources has played host to crude oil, gold, diamond, ivory, arts, and ancient crafts. While the AI industry in Africa is still in its nascent state, times are changing and the tide is turning. With more time, more funding, more research, and more passionate learners, Africa will attain an enviable state of technological advancement soon enough. Just as the world marveled at the sight of a black-skinned man, they would also marvel at the mighty technological empire he would build for himself.

Temidayo, 2020


Long gone are the days when rich Europeans mistook Africa to be one large country where they could enjoy a vacation in a forest with lions and elephants. Beyond the animals, beyond the Safari and the dessert, mother Africa and her 54 babies are gaining more global traction for the rapid increase of AI startups which have been springing up in the last of couple years.

 As some babies get to walk earlier than others, likewise, some countries, have also taken the lead in the advancement of AI and machine learning. It is only natural that others should catch up soon enough.

Let me hit you with some stats. In March 2019, a worldwide cumulative of AI funding was published with machine learning applications leading all other categories at $28.5b out of a total estimate of $82.4b.  Some of the other categories were machine learning platforms ($14.4b), smart robots ($7.5b), natural language processing ($6.7b), virtual assistants ($2.8b), speech recognition ($2.4b), and gesture control ($1.1b).

According to a study carried out by PwC on the impact of AI on the global economy by 2030, the AI industry is envisaged to hit over $15.7tr making it the largest economic and commercial marketplace. How is Africa preparing to get its own share of the “global cake”?


Africa is growing exponentially. According to the World Economic Forum, “no part of the planet is urbanizing faster than sub-Saharan Africa. The continent’s population of roughly 1.2 billion is expected to double by 2050.” Research shows that Africa’s median age is 19.5, unlike Germany (47.1), USA (38.1) and China (37.7).  Being largely populated with youths-in-their-prime, Africa has what it takes to push its way through to the forefront of the AI industry, globally.

In 2019, a total of $1.2b investment funding was raised by African startups. Although up to 50% of the total funding was raised by the top 5 startups, it is still a good feat. Better days are yet to come. Some of the blazing countries in the African AI industry include Kenya and Ethiopia (East Africa), Nigeria and Ghana (West Africa), South Africa (South Africa), and Egypt (North Africa).

Compared to Europe, Asia, and the USA, the African AI industry is still in a state of infancy. However, African countries are showing no sign of slowing down. With over 75 AI startups recorded in 2019, there is so much to be optimistic about in 2020. These startups have their focus on data and analytics, vision, robotics, and language or text recognition. Others offer professional services and AI devs, bots, chatbots, and virtual assistant technology. We have also been witnesses to the innovative incorporation of AI into the medical field; especially for health and pharmaceutical diagnostics. Also, a number of AI centers and hubs have sprung up in different parts of the continent.


Here are some of the top AI startups in Africa:


One of the successful Nigerian startups is Kudi. Kudi is an e-payment and e-transaction chatbot that enables easy exchange of money between friends and families. Pelumi Aboluwarin, the co-founder of Kudi, stated that they launched Kudi publicly in January 2017. Prior to that, it had been officially registered in late 2016.

Kudi implements several AI and machine learning techniques into deciphering user requests and behavior, fraud prevention and promoting a secure financial environment. It also has a B-2-B side to it as it looks to extend its unique solutions to solving current day problems encountered by banks and other companies.

A major feature of the Kudi platform is that it doesn’t necessarily require a data connection for it to operate. Instead, it uses phone networks. The founders of Kudi realized that only about 39% of Nigeria has access to the internet, hence, if they would reach more people, they had to go to the old-school style. Since 2016, Kudi has raised $5.9million investment funding having started with a seed round from YCombinator.

Kudi also has an agent system that allows people to provide financial and payment services locally. According to Kudi “Start making money by providing banking services to people around you.”


The South African startup stands out for disrupting the norm of the automotive and manufacturing sector via its machine learning interventions. It is also spreading its reach to the industrial and consumer-based goods marketplace. According to the DataProphet website,

“DataProphet is a leader in AI that enables manufacturers to step towards autonomous manufacturing. Our AI-as-a-service proactively prescribes changes to plant control plans to continuously optimize production without the expert human analysis that is typically required.

 As recognized by the World Economic Forum, DataProphet PRESCRIBE has helped customers around the world experience a significant and practical impact on the factory floor, reducing the cost of non-quality by an average of 40 percent.”

We understand manufacturing and that real impact is achieved with pre-emptive actions because real-time is often too late”.

Being the advanced analytics partner for Yellowwoods Capital Holdings, DataProphet has been able to expand its international client base. This can be linked to the huge but undisclosed investment that they got from Yellowwood’s Capital Holdings.


The “defenders of the tree crop” is a Cape Town based agro-tech startup that uses drones developed with AI systems for tracking farm health, growth and predicts possible danger.

With over $4.8million funding raised, the company is devoting its tech into assisting farms and farming consultants across Africa, Australia, and the UK. Aerobotics AI systems are used “to track tree health and size, using multispectral, high-resolution drone imagery.” This would enable it to detect the specific areas that require attention. They also access satellite data to understand tree health and growth during different seasons.

Aerobotics also implements AI-based platforms for predictive analytics. Hence, farmers can “make data-driven decisions” to boost their productivity.


The Tunis startup is a big data company with almost $1million investment funding.

DataVora has developed a market data platform for e-commerce where buyers and sellers can trade with AI-enabled hindsight and foresight. Their services can be quipped as “Price Intelligence & Competitive Monitoring for E-Commerce”.

What this startup does is to collate relevant market data and information such as prices, market patterns, product assortment, and specifications, then it uses AI algorithms to structure the data in order to provide relevant market analytics such as consumer behavior, market trends and product performance. It is a great tool for retailers and business owners who are looking to achieve higher results from their marketing strategy.

It is currently used by retailers in 50 countries.

Touchabl Pictures

Due to its unique features, the Nigerian based startup would be on this list. Here’s the thing – when you see a picture and you like what you see (not the person though…just the clothes, or accessories), you can run the picture on the Touchabl App; that way, the picture becomes touchable. No pun intended. When you touch the picture, the AI-enabled search engine would instantly run an image recognition search to identify the item you “touched”. It can also help you in purchasing the item after identification.

Although the app is majorly for fashion and lifestyle e-commerce market, it can, however, be also applied to other areas where an image or visual search is needed.

There are other AI startups in Africa. These are but the few ones that have gained more traction and funding in their nascent years. Other recognized startups include Clevva, Stockshop, Aajoh, Apollo Agriculture, UTU, BotMe, KiaKia, WideBot, GotBot, Affectiva, Tuteria, Awamo, FinChat Bot, Zappi, amongst others.


With the advent of multiple startups comes a need to have defined bodies charged with the responsibilities of creating awareness of AI, update the populace on current trends on AI and machine learning advancements, and creating a steady AI learning environment. Some of the AI centers that have made remarkable steps towards achieving these responsibilities include, but are not limited to:


DSN was founded by Nigeria’s Olubayo Adekanmbi, a data scientist and award-winning business executive in 2016. The goal was to build a society where AI can be used to solve local problems, especially the SDGs. He is a sole believer in the fact that AI is what Africa needs to come into her prime in terms of development and technological advancement. Bayo believes that artificial intelligence can redefine our lifestyle and our perspective of life in general.

Bayo is on a mission to raise 1 million Nigerian AI experts in 10 years. He has put practical learning platforms and programs in place in order to achieve this, such as:

  • Annual Bootcamp
  • 100 Days of Machine Learning (which is a prerequisite for attending the Bootcamp)
  • Inter-Campus Machine Learning Competition for tertiary institutions.


Google is one of the frontiers of AI development in the world. The Google AI center in Ghana is the first in Africa. The center is an AI-first research-based organization devoted to the development of AI and machine learning in Africa.


South African deep learning and machine learning expert, Vukosi Marivate, is the brain behind the Deep Learning Indaba. The organization rose out a need to fortify the growth of machine learning and artificial intelligence in Africa.

Africa, for a long time, has always being a receiver and not a manufacturer. Deep Learning Indaba seeks to change the storyline by raising experts who would help in the advancements of the African AI industry; moving Africa away from the spectators’ stand into the center of the pitch.

Deep learning Indaba revolves all its activities around two major objectives: An exponential increase in the contribution of Africa to AI development and advancement and achieving a wider scope in terms of diversity of the field. They strive to achieve these objectives via three major programs:

  • The Annual Deep Learning Indaba Conference
  • The IndabaX
  • Kambule and Maathai Awards


The AMMI is a one-year intensive program on machine learning for young Africans. The program is fully funded. Its goal is to become a catalyst for machine learning and AI development amidst Africans. AMMI also has a mentorship platform that allows young African professionals to be trained by experienced professionals in the AI industry.

The AMMI was founded by Moustapha Cisse in 2018, having received sponsorship from Google and Facebook.

AI HACK (Tunisia)

Founded in 2019 by Karim Beguir, AI Hack is both promoting the knowledge of AI, as well as creating an avenue for young professionals to create AI magic by themselves.

Other recognized AI advocates in Africa include Alliance 4 AI and Zindi Africa.


Africa as the hub for most of the world’s natural resources has played host to crude oil, gold, diamond, ivory, arts, and ancient crafts. While the AI industry in Africa is still in its nascent state, times are changing and the tide is turning. With more time, more funding, more research, and more passionate learners, Africa will attain an enviable state of technological advancement soon enough. Just as the world marveled at the sight of a black-skinned man, they would also marvel at the mighty technological empire he would build for himself.

How Artificial Intelligence could Decongest Nigerian Prisons

How artificial intelligence can decongest nigerian prisons digilaw agunbiade akintunde


Anyone familiar with statistics about Nigerian prisons knows that most of them are over-congested, carrying more than twice their actual capacity. For those unfamiliar, here are some stats:

Statistics of prison population risk assessment
Statistics of prison population digilaw risk assessment

The above list covers the total number of prisons, their capacity, and the actual number of prisoners as of 2017 in Nigeria. There are 240 prisons in Nigeria, with varying security levels and purposes. As of July 2019, the total number of inmates in these prisons is 73,995, an increase of 5,309 since 2017.

The growth rates of the prison population are not my concern here. The stats that we should be concerned about is the demographics of our prison population.

Convicts make up 23,568 (32%) while those Awaiting Trial make up 50,427 (68%).

What does this mean? If we had no inmates who were ‘Awaiting Trial,’ Nigerian prisons at their current capacity are more than adequate to accommodate the convicts in the system.

Why do we have so many inmates ‘Awaiting Trial’? What’s delaying their trial? What does it even mean to be ‘Awaiting Trial’?


Understanding the awaiting trial condition requires an understanding of the factors that lead to it. Primarily, it is caused by Nigeria’s rigid and outdated penal laws. Whereas other climes have lighter punishments for simple offenses like those that are traffic and environmentally-related, such as community service and paying of fines, Nigeria’s penal laws in many places still maintain provisions for incarceration as punishment for these offenses. On its own, this alone might not lead to the awaiting trial condition, but the method used by Nigerian security agencies is to keep suspects incarcerated before conviction for their alleged crimes. It is known as holding charges.

According to Black’s Law Dictionary, a holding charge is a criminal charge of some petty crime filed to keep the accused in detention while the prosecutor takes time to build a more significant case and prepare a more severe offense. Alternatively, the accused can be brought before a court of incompetent jurisdiction intentionally by the prosecuting authority to get a remand order on the pretence of building a stronger case while the accused stays in prison.

Combine holding charges and outdated penal laws, and you have the recipe for the awaiting trial condition, the reality of 68% of Nigeria’s prison population. The newly enacted Nigerian Correctional Service Act 2019 recognises this problem as it provides that one of the objectives of the Act, under Section 2(1)(d), is to ‘establish institutional, systemic, and sustainable mechanisms to address the high number of persons awaiting trial.’

Now for my solution; Artificial Intelligence, or to be precise Risk Assessment Systems, a new AI-based technology that has been successfully applied in several states of the USA and Israel to reduce the rate of incarceration. In my recently published book, ‘Artificial Intelligence & Law: A Nigerian Perspective,’ I discussed this system generally, although my focus there was on the application of AI in civil matters, not in criminal cases, under which the prison system falls.

My discussion now will involve an explanation of what Risk Assessment Systems are and how they work. I will then proceed to discuss how Nigeria can implement it. My model is slightly modified to combine features of the American and Israeli system, making it locally suitable and avoiding the pitfalls of other networks, especially the American versions.


The purpose of a risk assessment system is to decrease the rate of incarceration and predict recidivism, or the likelihood that a person will return to a lifestyle of criminality if released. They come in several versions that perform slightly different tasks. Some predict the probability of a person committing a crime (COMPAS); others decide whether a person should be released on bail or not (PSA). A third version suggests sentencing options (LSI-R and ORAS), while other assists judges in reaching sentencing decisions in traffic cases (IDSS). All these systems will be discussed in detail shortly.

Risk assessment systems generally use data to identify those most likely to commit crimes and recommend that they are removed from society. It does vice versa for those it finds less likely to commit crimes; it usually suggests that they should be released or given lighter sentences for offences already committed. The development of these systems is premised on the Selective Incapacitation Theory, which was developed in the 1980s USA. This theory held that there was a subset of society described as ‘career criminals’ who were responsible for most crimes committed. The courts should seek to identify these persons and put them away for more extended periods compared to one-time or petty criminals. Proponents of this theory argue that this course of action would reduce the cost of prison administration by identifying those defendants who did not have to be incarcerated towards conviction or rehabilitation. This line of thought shows why it can help mitigate our awaiting trial problem. Another argument in its favour is that it would reduce the crime rate. Their position is statistically sound. After analysing the records of 10,000 offenders, it crime that 51.9% of serious crimes were committed by just 18% of offenders.

Risk Assessment Systems rely on data, mostly gleaned from prison and police records, to reach their conclusions. Any gaps in this data will reflect in the conclusions reached by these systems. For instance, some of them have been accused of being biased against blacks in the USA, by recommending incarceration for them, while recommending lighter sentences for the same crime by white people. Historically, more black Americans and their communities have been the subject of police surveillance and crackdown. There is thus more data about African Americans in the police system in proportion to their minority population. When you feed a Machine Learning system with this kind of data, it will incorrectly interpret it to mean that blacks are more prone to violence than other groups and will recommend stronger sentences for them. I will discuss some of the risk assessment systems mentioned above and the challenges some of them have faced.

COMPAS – Correctional Offender Management Profiling for Alternative Sanctions

Of all Risk Assessment Systems to be considered, this one has generated the most controversy and criticism. It was developed by a private company known was Northpointe Corporation in the USA. The first state to adopt it was the State of Virginia, USA. Based on data provided, it delivers recommendations to judges about sentencing for defendants. It has successfully helped Virginia reduced the rate of prison population growth from 31% to 5% annually.

To deliver an assessment of each person, this system considers individual characteristics such as age, previous criminal record (if any), employment history, and group data. The sum of this information can result in a recommendation that the suspect should remain incarcerated, how long such a person should be sentenced, or whether the person should be pardoned.

This system has however, been found to be mostly unfavorable to African-Americans. One case where this bias was brought to nationwide limelight in the USA was the Wisconsin v. Loomis case, where the defendant was arrested for his involvement in a drive-by shooting. He pleaded guilty and requested for a plea deal. The judge, however, gave him a 6-year sentence, saying among other things:

‘The risk assessment tools (COMPAS) that have been utilized suggest that you’re extremely high risk to re-offend.’

The defendant’s appeal to the Wisconsin Supreme Court was rejected because it would be irresponsible to release a defendant identified as high risk by the risk assessment system, only for him to commit another crime and be re-arraigned. In this scenario, we see that the court in the State of Wisconsin has largely surrendered judicial decision-making to the computers.

Another instance of the bias of this system happened in 2014 involving two 18-year old girls named Sade Jones and Brisha Borden. They stole a bike and scooter for a joy ride. They were arrested and charged with robbery and petty theft. COMPAS assessed Borden to be a high-risk offender, while Jones was assessed as a medium risk of reoffending within the two years.

The implication of this is that judges would be predisposed to give the maximum sentences for crimes committed based on the assessment given, rather than focusing on the present circumstances of the defendant in question, which may suggest a lighter or no punishment. Sentencing in this scenario would depend on the sum of crimes committed by the defendants’ group, not just his crime — something like Jesus carrying the sins of an entire race.

Another risk assessment system that is very similar to COMPAS is the LSI-R (Level of Service Inventory-Revised). It was also developed by a private company based in Canada (Multi-Health Systems) and determined a person’s risk of recidivism (going back to crime) and the best sentencing options. It is used in the States of Washington and California .

If this the reality of a risk assessment system in practice, why would I recommend that Nigeria adopt something like this? The discussion so far only suggests that such a technology might even worsen the prison congestion problem.

If this has come to your mind, your fears are valid. But there is one factor that makes COMPAS a problematic system; it is privately owned. Northpointe Corporation, the company that developed this system, has full proprietary rights over it, and only licenses state governments in the USA to use their risk assessment system. The implication of this is that neither the government nor the courts have a clear idea or how the system delivers its recommendations, how it assigns scores to each parameter, or how it processes data. The company has also refused to make this information public, despite the public purpose that their product serves.

It is my firm position that Nigeria should not tow the path of outsourcing the development of a risk assessment system to a private company. Even if we do, the agreement towards its development should make it clear that upon complete payment of the contract sum, all rights over it shall be assigned to the government. This way, the system shall become public property, and members of the public will be able to access information about how it works, under the Freedom of Information Act 2010 and the Nigerian Data Protection Regulation 2019.

The next risk assessment system that will be discussed meets the described standard.


This risk assessment system was developed by the State of Ohio Government. Its development was a joint project of the State Department of Rehabilitation and Correction and the University of Cincinnati, Ohio. Other states that have taken the public route in developing their systems are Pennsylvania and Louisiana. They have done this to avoid the challenge that proprietary protection of private systems usually poses in states like Virginia, Washington, and California. The public approach is what I recommend Nigeria take.

There is another risk assessment system that perfectly matches what I have in mind for Nigeria to implement. It is the:


Unlike other systems that seek to identify potential offenders and recommend sentencing methods, this system only suggests that a person should either be granted bail or remanded before he/she is brought to trial. To reach its conclusion, it evaluates the age of the suspect and their criminal history. If the person is assessed to be low risk, bail is recommended. If found to be high risk, detention till the trial is recommended. Data from 1.5 million crimes in 300 US court jurisdictions were used in training this system.

It was developed by the Laura and John Arnold Foundation and is used in the States of Arizona, New Jersey, and Kentucky .

So far, we have seen a range of risk assessment systems, from the less than ideal COMPAS, the standard ORAS, and the excellent PSA. I could move from here to discussing my proposed model for Nigeria, but there is one missing factor that all these systems have. It might not be a big deal in the USA, but in Nigeria, if this factor were to be ignored in developing a risk assessment system, such a system is dead on arrival.

What is this factor?

Involvement of the judiciary in its development.

That’s why I still need to mention another risk assessment system. This one is not from the USA. This time, our discussion will pivot to the Middle East, Israel, to be precise.


This risk assessment system is restricted in use to traffic cases in Israel. The traffic courts are one of the lowest courts in the hierarchy of the Israeli court system. Just like lower Nigerian courts, their dockets are also congested, causing delays in hearing and sentencing for cases.

Conventionally, when a matter comes before the traffic court for a hearing, the judge will consider the previous record of the offender and the time intervals between offenses before delivering judgment in the instant case. This record is presented to the judge in hard copy format as a printout. It usually comes with technicalities that make it difficult to understand, especially for judges new to the traffic court bench and anyone generally unfamiliar with traffic court procedure.

The IDSS was developed to save judges the stress of understanding technical documents and reduce the time spent in traffic court. It analyses the previous records and gives recommendations to judges about the sentence in the instant case. Unlike other risk assessment systems that were developed without the involvement of judges, the IDSS was developed with the participation of Israeli traffic judges. The judges reached a consensus about the most critical factors for the system to analyse as follows:

  • The seriousness of previous offences, such as driving, causing death, driving under the influence, driving while license is suspended, over-speeding, beating red lights, etc.
  • The similarity of previous offences
  • The seriousness of the last sentences
  • Driving causing accidents in the past such as bodily damage and damage to property
  • The present crime committed during the period of disqualification arising from a prior traffic offence
  • The current crime committed during the period of deferred ineligibility arising from a previous traffic offence
  • Frequency of offences


Based on the discourse so far, it is clear that risk assessment systems give a definite advantage to not just the prison system, by reducing the number of potential inmates they have to cater for, but also in reducing the workload of judges. The challenge they have faced revolves around the method used in implementing them – privately owned and developed vs. publicly owned and developed.

I’m sure you would agree with me that the preferred model for Nigeria would be the public model. Borrowing from the model of the State of Ohio, the proposed Nigerian model – let’s call it Nigerian Risk Assessment System (NIRAS) – would be developed by or on behalf of the government through its agencies. This public approach would eliminate the proprietary cover that private developers can use to avoid sharing their source code and algorithmic parameters for assessing risk like in the case of COMPAS

NIRAS would be employed to give recommendations as to whether a person should be granted bail or not. If the suspect is found to have a high-risk score, bail will not be recommended. If the person has a low-risk rating, bail will be approved. NIRAS is similar to the Public Safety Assessment (PSA) already in use in the States of Arizona, Kentucky, and New Jersey.

Most importantly, the NIRAS should not be implemented for all categories of criminal offences and must whole with the active collaboration of the judiciary. This suggestion is gleaned from the Israeli Intelligent Decision Support System (IDSS), which is applied only in traffic courts, and judges supplied the parameters that should be deployed in building the machine learning algorithm that powers this AI risk assessment system.

Understandably, criminal offences, especially those that involve injury to another or public welfare, are more controversial. Introducing any form of advanced technology to their adjudication would be firmly rejected. NIRAS, if adopted, must first be tested with petty offences where it will gain acceptability. This testing ground will also provide the opportunity to detect any flaws in its application that can be easily corrected without dire consequences. Magistrate Courts and other courts of no record would provide a suitable testing ground for this technology.


Even if the proposed risk assessment system is publicly developed, involves the collaboration of judges, and is restricted to minor courts, none of this still eliminates potential risks and pitfalls that might befall it. Judges might provide broad parameters, but they will not be in control of the collection and processing of data that will be used to develop the machine learning models in line with these parameters. We may not have a Black v. White divide in Nigeria, but there are subtle divides in our criminal justice data system that might be unduly emphasised by a risk assessment system. Some of those divides are the Male v. Female gap and Ethnic group imbalances in our data system. Because of the lop-sidedness of our criminal data records, a risk assessment system built on this might be prone to give harsher recommendations for gender or a particular tribe.

According to data from the Lagos Criminal Information System, 98% of prison inmates in the state are male, while 2% are female. When you consider the breakdown of the prison population in Lagos by states of origin, you find that indigenes of Oyo and Ogun State are the largest group of inmates, compared to indigenes of Lagos or other states. Inmates from the South-East make up 16% of the prison population, those of South-South origin make up 13%, the South-West makes up 49%, while the entire North (North Central, North-East, and North-West) is 22%. Funny enough, when you remove Kwara State indigenes from this list, the contribution of the entire North drops to 14%, as Kwara State indigenes make up 1/3rd of the whole of the Northern population in Lagos State prisons.

Notice how I mentioned some factors more than I mentioned others? After you read the previous paragraphs, these are the factors or terms that might have come to your mind:

  • Almost no women in Nigerian prisons
  • Nigerian men have a higher proclivity for crime compared to Nigerian women
  • People of South-West origin are more prone to criminality in Lagos State than all other groups
  • Northerners are mostly peaceful and law-abiding

None of these assumptions is entirely valid. Some of them are practically untrue, but if we decide only to use the data as represented by the prison population in Lagos, this is what it reflects. AI, notwithstanding the ‘Intelligence’ that forms part of its name, is no better at detecting biases or lop-sided information. The same way an uninformed person can read the above information and leave with an incorrect impression of Nigeria’s ethnic groups and gender population is the same way an algorithm can incorrectly predict higher rates of recidivism for some groups. A risk assessment system could give women higher scores for bail compared to a man, even when the gravity of the offence committed by the woman is higher than that of the man. A risk assessment system could also predict that indigenes of Lagos, Kwara, Oyo, and Ogun are more likely to jump bail and give them lower scores. An indigene of the FCT, Rivers, Gombe, or Niger might be recommended for bail, even when the offence committed is more grievous than that of his Oyo counterpart.

Applying a system like this, even in the most restricted way, would worsen the sensitive ethnic and gender relations in Nigeria, with untold consequences.

With all that I’ve shared so far, I’m sure that the benefits of AI to our prison system are the last thing on your mind. You could conclude that the risks of AI outweigh the benefits, I won’t begrudge you that.

But the problem here isn’t an AI problem; it’s a data problem. AI is only as good as the data it is built on. To improve the technology, we must upgrade the data. To ensure the fairness of a proposed risk assessment system, we must improve the quality of the data we develop it with.

I propose that in collecting and processing data from the criminal justice system for the purpose of developing NIRAS, details like gender and ethnicity are blurred or intentionally left out. I’ll illustrate using two different tables. The first table will have fictional names, their offence, sex, and state of origin. The second table will have only fictional names and crime.


risk assessment digilaw


Risk assessment system digilaw

A typical criminal record will have more details for each inmate or suspect. I have chosen to focus on these small details to make my point. If we use data like TABLE A that reflects ethnicity and sex, there is the risk that everything I described earlier will come to fruition. TABLE B, on the other hand, omits those details. A proper criminal record for developing a risk assessment system will skip those details. Instead it will be focused on practical information like facts of the alleged offence, previous criminal history, jurisdiction where the crime was committed, etc. This approach is known as data minimisation – it involves only collecting the minimum amount of data needed to accomplish a task.

It has legal backing in Nigeria under the Nigeria Data Protection Regulation (NDPR) 2019. It provides that the following types of data should not be collected, except with a solid form of consent. They are:

  • Ethnicity
  • Political affiliation
  • Religious belief
  • Trade union membership
  • Biometrics
  • Sexual orientation

However, the NDPR is not active or encompassing enough to provide the legal backing for enforcing data minimisation in the development of risk assessment systems. Because it is merely a regulation from an agency (National Information Technology Development Agency – NITDA) with no purview or relevance in criminal matters, its provisions are at best persuasive.

Nevertheless, it already has the necessary clauses that could be applied to minimise or eliminate bias in AI for our criminal justice system.

There are two alternative approaches that could be employed to achieve this – on the one hand; the NDPR could be amended to expressly expand its scope to cover criminal matters. It could then be re-enacted as an Act of the National Assembly, giving it equal force like the Criminal Code, Penal Code, and other criminal laws in Nigeria, apart from the 1999 Constitution itself.

On the other hand, a special law to create a legal regime for risk assessment systems could be enacted. One of the provisions of this law could expressly stipulate that the requirements of the NDPR concerning data minimisation should apply. This approach, though limited, is more realistic, especially for state governments that may be interested in adopting risk assessment systems. The former method requires federal buy-in and may be long-drawn, although once concluded, it would have wider effect and enforceability. The latter approach can be adopted by state governments without the foot-dragging that usually accompanies federal law-making. It would, however, be limited in application to and may be subject to judicial review if the state government in question chooses to extend the implementation of the risk assessment system beyond just petty offences as I earlier recommended.

In the ideal setting, the risk assessment system (NIRAS) should be an FG project, backed up an enabling law, and a stronger NDPR (preferably an Act). Willing state governments can then re-enact the enabling legislation to apply within their domain, just like the Administration of Criminal Justice Act (ACJA) 2015 and the Child Rights Act (CRA).

Another challenge that might plague the development and deployment of a risk assessment system in Nigeria is the nature of our criminal record system. In a country where most of our criminal records are paper-based, data collection, and processing to build training and building algorithms cannot happen until our records are digitised.

Luckily, there is already activity in this regard. The Nigeria Police Force, a few months ago, entered into a BOT (Build-Operate-Transfer) Agreement with Ace of Spades Consult, a private company. The purpose of the agreement was to develop a digital database of civil and criminal records in the custody of the Nigerian Police at the Criminal Records Registry (CRR) Alagbon, Lagos State. This online database would also have a web portal that could be used to run background checks and issue clearance certificates concerning previous criminal records.

All current physical records will be converted into electronic format, while future documents will be uploaded directly to this online database.

The Nigerian Police also intends to collaborate with other government agencies that collect citizens data such as the National Identity Management Commission (NIMC), the Nigerian Immigration Service (NIS), and others.

Irrespective of which level of government that takes the initiative to implement a local risk assessment system, a partnership with the Nigeria Police Force would be critical to pulling this off. Data from the Nigeria’s central criminal registry would be comprehensive and detailed enough to build a risk assessment system tailored to Nigerian realities, as opposed to merely importing one and trying to adapt it to our realities. Access to this data would not be a one-off project but continuous to ensure that new trends in criminal behaviour are incorporated into machine learning algorithms that predict recidivism. To create a framework for this, the enabling law for a risk assessment system would provide for this while also enshrining the principle of data minimisation.


There are positive signals that the authorities are taking steps to tackle the challenge of prison congestion. One of them is the Nigerian Correctional Service Act 2019, which now empowers prison authorities to reject new inmates if their facilities are full. With a risk assessment system working alongside this law, we can ensure prison authorities don’t even have to reject many inmates in the first place, because the risk assessment system would have recommended that some be given bail.


Prison Statistics: Prison Population by Total Detainees, Prison Capacity and Number of Unsentenced Detainees by State and Year and Prison Inmate Population by Gender (2011 – 2016), National Bureau of Statistics/Nigeria Prisons Service October 2017

Nigeria, World Prison Brief Data, World Prison Brief www.prisonstudies.org/country/nigeria

– Nigerian Correctional Service Act 2019

– Kehl, Danielle, Guo, Priscilla, Kessler, Samuel, ‘Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing‘ (July 2017) Responsive Communities.

– A. I. Agunbiade, Artificial Intelligence & Law: A Nigerian PerspectiveAcademia

Quarterly Report Infographics, October – December 2018, Lagos Criminal Information System, Lagos State Ministry of Justice

– A. I. Agunbiade, ‘A Review of the Nigerian Data Protection Regulation (NDPR) 2019′ Academia

Nigerian Data Protection Regulation 2019: Implementation Framework

– Ugo Aliogo, NPF Partners Firm on Digitalisation of Records, (This Day, June 25, 2019)

20 Reasons why we need Artificial Intelligence

Artificial Intelligence, machine learning, deep learning, data science…One thing is similar in these concepts. I’ll tell you.

Apart from the fact that the world’s technological future revolves around them, another remarkable thing is that these 4th industrial revolution catalysts have successfully experienced a swift shift from a point of hypothetical and theoretical propositions into actual life changers. The basic understandings of these ‘new’ technologies have become more decentralized over the last few years, rapidly moving from one sect of professionals to various sectors of human endeavours. We have successfully gone past the first stage of actualization– theory & hypothesis –and are now seeing active incorporation of these technologies in business, healthcare, finance, government, military… It’s an endless list. So, we should say a global congratulation.

Quick recap – What is Artificial Intelligence?

Artificial Intelligence, our focus in this article, is rapidly finding its way into several sectors. Wait a minute… Is Artificial Intelligence new to you? If no, skip this paragraph. If yes, this is for you. Hackernoon provides a very simple definition of AI. According to them,
Artificial Intelligence uses intelligent machines built in a way that they react like humans. The primary process involved in making these smart machines is to carry out decision making, which analyses and uses data available in an enterprise. It is similar to the human mind absorbing and synthesizing information and providing the required decision.”
Got it? You’re welcome!

In the year 2020, the expected spending on AI is would hit $46 billion. This is a recent IDC report. Massive, right? AI is not stopping. It is on a fast ride into global and economic reformation. According to the Forbes Technology Council, AI is having a great impact on business and in the world generally. In their own words,

“Adding AI to your business may be the next step as you look for ways to advance your operations and increase your performance.”


Let’s go on to see 20 ways in which Artificial Intelligence has been used to optimize business efficiency, including human and institutional productivity.

20 ways Artificial Intelligence has helped humans

    With AI-empowered systems in use, we get more time to complete more “humanly” tasks; things requiring a high level of decision making, impulsive actions and on-feet response. Robots and AI excel well in handling more defined tasks. Gmail, for instance, is programmed to predict and provide possible suggestions to users’ emails, reducing the time spent in composing and replying emails. Hence, enabling us to actually engage in more demanding tasks. Although not so much now, it’s baby steps for a very wide range of possibilities.
    It is no longer a new thing that robots can be as meticulous as a real doctor; even for a surgical operation. We have read of the successful possibility of a remotely conducted surgical operation. Artificial Intelligence is the new magic wand. In a recent study conducted by surgeons at the Children’s National Medical Center in Washington, CNN had it that an autonomous robot successfully performed a soft-tissue surgery. The robot was able to stitch a pig’s bowel together during the open surgery. The team reported it to have even done better than a human surgeon. It is possible for a doctor to monitor and run a diagnosis on patients without being there in person with the help of AI technology and the internet. This shoots the possibility of remote healthcare service to the rooftop.
    Ever heard of ‘Siri’? Siri is an AI virtual mobile assistant available on Apple Inc.’s iOS, iPad OS, watchOS, macOS, tvOS and audio OS operating systems. Basically, Siri uses voice queries and a natural-language user interface to answer questions, make recommendations, and perform actions by delegating requests to a set of Internet services. It can help you set a reminder, take notes or even set alarms. It can conduct a search for you upon request, play a song, perform calculations, make a reservation, change dates, change phone settings and even launch an app. This can totally change how we get to use our mobile phones in the years to come. Other available alternatives of Siri include the Google Assistant, Google Now, Amazon Alexa, SILVIA, S Voice, and so on.
    Have you ever seen in movies where a person simply makes a gesture, claps or makes a statement and the lights come on, or go off? Yeah, it’s not a ruse. AI has brought the possibility of a ‘smart home’ from the dream world to reality.
    Change is beautiful only when it’s progressive. From horses to carts, down to the steam engine and the legendary Mercedes Benz that defined the early elite class. Now, we have cars that are getting closer to the speed of sound and those that do not even require drivers at all.  
    On December 5, 2018, Waymo LLC, an independent subsidiary of Alphabet Inc., officially launched a commercial self-driving car service called “Waymo One”. How can I explain this? Eureka! It’s just like Uber. You order for a vehicle via an app on your phone, only that this time, you would have to impute your location in the vehicles GPS system and it will drive you itself to your location. More companies are already buying into the autonomous vehicle technology. Some of the most successful ones include, but are not restricted to, Elon Musk’s Tesla, Cruise Automation and Calico.
  5. AI IN ART
    Artificial Intelligence is now in art, architecture and designing. There are quite a number of creative applications which can produce beautiful visual art. Although these machines start by learning the human artworks through the neural network, as time goes on, the machine is soon able to come up with its own art. The inception of non-human creative. We have begun to see exhibitions of computer-made art in galleries all around the world and it can only get better.
    Some applications can provide you with suggestions and predictions of movies or music based on your search history or other parameters it is programmed to observe. Also, it’s a great marketing strategy as some Ads are shown to you based on your online activity and a study of what type of person the AI perceives you to be.
    With the installation of surveillance cameras, the need for around the clock supervision becomes a requisite. However, with AI systems programmed with an algorithm to analyze situations and detect threat levels, more time can be invested in more productive tasks. Also, the AI doesn’t fall asleep during a watch, as such, making it near impossible for it to miss out anything.
    The finance sector could arguably be said to have incorporated the use of Artificial Intelligence and machine learning in their day to day operations. With computers handling most number-crunching tasks, professionals have more time to execute more administrative and customer-based responsibilities. For a more delightful read, see “The Accounting Profession can be Improved by AI: How?”
    With its accuracy and speed, AI tools can analyze financial data more efficiently than most humans can, giving the institution time and saving it the stress of a heavy workload.
    Artificial Intelligent programs can be used to predict or analyze consumer behaviour, producing a more effective and personalized form of advertisement.
    The application of AI and Machine Learning in the military has created more sophisticated and enhanced means for communications, sensors, tracking, tracing and integration. AI technologies play a great role in threat detection and identification, marking of territories, and target acquisition.
  12. AI, TOYS
    Children are full of life and fun. You would be quite amazed to find out how much they can learn when education is mixed with fun. With AI, Digital Pets (also called virtual or artificial pets) were introduced in the late 1990s. Although most countries have banned the use of these pets in the classroom for reasons such as distraction and over-attachment to the device, it is still one of the most adorable and productive ways technology has been used. Some popular digital pets include Furby, Giga Pets and Tamagotchi.
    Ever thought about an administrative AI before? Well, some AI systems are being used actively by governmental bodies for several purposes ranging from policy objectives analysis to public interaction and virtual assistants. Based on research conducted by the Ash Center for Democratic Government and Innovation, Harvard University, it was stated that governmental problems that would require the application of Artificial Intelligence include; resource allocation, processing large data sets, expert knowledge, predictions & foresight of events, figure input or output and handling varying data type.
  14. AI, GAMES
    Virtual gamers, avatars and first-person shooter games are all offshoots of the application of AI in the gaming world. Progressively, gaming companies are getting closer to bringing human features into their games. Hence, making their games more humanistic than ever before.
    With China, Korea, Japan, USA and Germany leading the involvement of Robots in industries, it has been proven that robots are better effective in routine jobs than most humans. They have a lesser tendency to lose concentration and focus. What this would mean is reduced accident rate, more productivity and speed.
    One of the toughest jobs of every HR professional is fairly screening through a myriad of resume and ranking each applicant by their qualification. This might not look like much until thousands of people apply for a job and you’re meant to recruit just 5. But, it’s not all doomsday.
    Furthermore, with AI, tedious recruitment tasks can be handled by the machine while the HR professional handles the physical interaction with shortlisted candidates. Artificial Intelligence can be applied in the screening of resume and ranking of candidates according to their qualification and/or any other yardstick required. AI can also provide predictions on candidates’ success rate in roles given via job matching platforms. Also, recruitment ChatBots are very great helpmates in communication tasks. With these machines, response and interaction can be automated. With all these in place, the HR professional has ample time to focus on much “humanly” requirements than technicalities.
    Agriculture has far evolved from the way we know it. With the incorporation of agricultural robots, predictive analysis, and soil/crop monitoring algorithms, farming industries have been able to keep up with on-field management, and crop health. Some AI programs can predict the harvest time for each farm produce. Another specialized application of Artificial Intelligence includes the use of an automated greenhouse.
    There are systems that monitor financial activities for fraud detection. These systems are basically programmed to monitor the financial activities of people and raise alarm at any suspicious move. AI-empowered programs now carry out most of the financial fraud detection activities. The AI simply studies the customers’ withdrawal pattern, withdrawal frequency and withdrawal methods, storing and analyzing these data in a case of suspicious activities.
    The coming of ChatBots and other automated response mechanisms has made it quite easy for companies and institutions to interface. Most companies now communicate with the public via ChatBots. Communication has been made more effective and rapid, without the lag of human restraint. These ChatBots function as Automated Online Assistant; also known as Intelligent Virtual Assistants (IVA) or Intelligent Personal Assistant (IPA).
    This is yet the most controversial application of Artificial Intelligence. AI personal assistants exist to aid student’s learning via personalized tasks and lesson. These AI are designed to suit each student’s ability to learn and interests. Most students find the “classroom” system quite restrictive. Hence, the idea of an AI assistant reduces the presence of human anxiety and fear. However, the fear persists. The fear of over-dependency on computerized education on the part of the student. This might produce a less mentally challenging education. Students have the tendency of being distracted from the actual learning process. Teachers on another hand have the fear of losing their jobs to these AI.
    As much as many speculations exist around the application of AI in the global educational system, it is an inevitable synergy that would seamlessly unfold sooner than later. The picture of the next century is one with an all-computer system or human-computer cooperation. Either way, Artificial Intelligence is the future of education.

Parting words

Artificial Intelligence is the future of global technology. Whether we lie it or not, it would still gain entrance into more and more sectors of human endeavours. The world is moving faster than ever before and AI is the train of technological development. We can only look forward, think forward and move forward.

Temidayo V. OLALEKAN
Content Writer,
DGL Africa (DigiLaw)

Legaltech: What Young Lawyers stand to gain from it

“When someone points a gun at your face, you take the gun. Or pull out a bigger one. Or call their bluff. Or do any one of a hundred and forty-six other things”

The legal profession –like most other professions– is staring down the muzzle of legaltech pointed at it by the tech innovation industry. Whether you like it or not, whether you want it to be or not; LegalTech is slowly but steadily changing the narrative about how things are and can be done in the profession. It’s high time someone examines its prospect for young lawyers, particularly.

LegalTech: What It Means

Still wondering what Legaltech means and refers to? You should head over to our previous article titled LegalTech: How It All Began, where this author examines the fundamentals of legaltech and its history. There, you’d understand legaltech to mean “technologies –soft and hard –that help attorneys attend to clients’ legal needs in a fast efficient manner…”.

LegalTech: The State Of Affairs

Now, there’s been an outpouring of goodwill and confidence about the prospects of legaltech. There have even been substantial investments in the acquisition of such tech by major law firms across the world. But the reality remains that its global adoption is still at its lowest levels with the Nigerian arm of the profession not coming close at all.

From personal experience, older and senior lawyers at the bar who’ve risen through the ranks to become gladiators, are not enthusiastic about legaltech. Obviously, there’s not much they stand to lose in the fight for survival since they’ve already made their mark and would continue profiting from it.

The same cannot be said of younger, junior lawyers who join the saturated profession in their droves annually. For them, LegalTech presents a formidable option for rapidly blooming into formidable, badass attorneys –either as solo practitioner or employees at established law firms.

Millennial Lawyers and Their Technophobism

It wouldn’t be over-reaching to conclude that 90% of young lawyers with under 5 years of practice in their portfolio, belong to the millennial generation. They are thus supposed to be conversant and comfortable with the usage of new technologies. But as recent data has shown, such supposition and presumption are rebuttable and untrue. In fact, they are amongst the most technophobic of young professionals.

At the recent Justitia Seminar in the Netherlands, a poll was taken to determine the frequency of legaltech usage by young lawyers. The results confirmed what was already suspected – lawyers, young and old, don’t use legaltech.

Aside from the usage of essential Microsoft packages like Word and perhaps Excel, 75% of the over 200+ young attendees used neither of the 4 most prominent legaltech products on the market –e-Signing, Contract Automation, Matter Analytics, and Doc Review.

Picture it. If this is the case in a tech-advanced jurisdiction such as the Netherlands, one can only imagine the ebb of the stats in tech-apathetic jurisdictions like Nigeria.

Perhaps, this trend subsists because young lawyers fail to realise how legaltech adoption can catapult them to the top of the pile –which is exactly what this piece seeks to address. If you follow through, you’d gain clarity on the prospects of legal tech for young lawyers.

LegalTech: Career Advancement Prospects for Young Lawyers

Just maybe if young lawyers with solo legal practice or those in the employ of top-tier firms, understand how quickly and rapidly legaltech can help them rise from oblivion to prominence on the strength of consistent delivery of client satisfaction, they’d take its adoption seriously.

Fast-Tracking of Professional Intuition Development

As with all fields, years of doing whatever you do comes with the evolution of a professional gut feeling, instinct, or intuition. Professional intuition is what facilitates the presentation of fast, on-the-spot assessment and solution to a client’s legal problem. A seasoned, experienced practitioner who knows his onions, has a reasonable foresight of how a legal matter would turn out. The intuition to do so only comes after years of honing and toning in real practice –something which fresh out-of-law-school graduates can’t reasonably be expected to have –it is inconsequential whether such graduated with a First Class or Second Class Upper. But clients don’t want to know that, or do they?

Abdi Aidid, a former New York Litigator puts it, “As a young lawyer, one of the biggest challenge was being expected to perform like an experienced lawyer right away…most of my day was spent reading cases to figure out relevant factors. I didn’t have a lot of time to think creatively about our client’s case”.

With legaltech however, young lawyers can get a quick headstart on the honing of a professional intuition that gives experienced lawyers that special edge. Most legaltech tools you’d encounter on the market today are built to enhance foresight development. Young lawyers can input the facts of a case in these tools to test, validate their solutions to clients’ legal problems. For instance, a first-year associate using the Law Pavilion Prime can cut through judicial precedents to arrive at the most important principles and factors that are of weighty substance in real practice, as pronounced in the dictum of judges. With this tool and an array of others, young attorneys can consistently churn out fully-formed, workable ideas and solutions, rather than half-baked, fallible ones.

Solo, young lawyers can also take advantage of this tool to cut down on mistakes and response time to client needs. It’s not uncommon to see young lawyers go to seniors for advice on how to make a head start in cases. But with tools such as Law Pavilion Prime, for example, a young attorney can understand positions of the law on a principle or field, the developments it has undergone, and gain the competitive edge needed to slug it out successfully against opposing counsels.


All over the world and across different industries, the recipe for professional success lies in building and maintaining invaluable contacts in a professional community. Nowadays, it is never enough to rely on what you know only, there’s a higher place for who you know too. The legal profession is no exception to any of this –it’s only through professional contacts that you get to be aware of current legal trends, be in-the-know about lucrative job opportunities that aren’t often advertised, and get links to judges that can easily sign off on your documents at non-working hours. For any young attorney that works at an established law firm –especially the top-tier ones, chances are that your employer has invested in some amount of legaltech to make your bullpen-life easier.

Possessing expert knowledge of and usage about these tools makes you a credible resource person that fellow attorneys can come to for tips on how to handle these tools. This combines to help you build networks and connections with lawyers at various levels across the legal business. Your reputation would make partners come calling to assign you tasks.

Yes, law firms with large legal tech investments have technical officers – that are often non-legal professionals – who train attorneys on legaltech usage and help troubleshoot when matters get out of hand. The reality, however, is that birds of the same feather flock together –a legal practitioner would always prefer taking cues on the usage of Lexis Nexis from another lawyer than from a non-legal tech assistant who doesn’t speak legalese and cannot perhaps demonstrate the tool’s usage in varying scenarios and ways.

Even if your law firm isn’t so interested in legal technologies, a personal decision to acquire these software-based technologies leads to churning out of qualitative solutions and ideas –something you can bet wouldn’t ever go unnoticed. At some point, someone would pick up the scent and enquire how you turn in your tasks before everyone else in the bullpen. Undoubtedly, that interaction enhances your chance to forge lifelong, professional bonds and the circle continues to expand as the news spread.

Investment in the usage and mastering of these tools by a solo, young lawyer, can also help forge lifelong relationships with fellow young lawyers who come calling to know your success recipe when you start to reap the benefits of the usage of legal technologies –which is fast rise into prominence.

Promotion Radar-Placement

With AI-powered legaltech like Luminance, sole practitioners can work on presumptuously difficult and hard-to-crack briefs for young practitioners with little or no experience at all. With Luminance, a fresh, out-of-school law graduate can quickly work through the legalese in technical contracts. This helps to cut through swathes of unfamiliar, industry-specialised terms at record time than would perhaps have been expected of a mid-experienced senior lawyer. This bolsters a boutique-lawyer’s rep as an efficient deliverer of quality legal services and paves way for a broadened client base and bigger briefs. Referrals from satisfied clients thus help place a young lawyer on the radar of his targeted clients.

For young associates aiming for the top echelon in established law firms, usage of AI-powered tech can contribute to placing you on corporate promotion radars. The consistent churning of qualitative solutions facilitated by these tools will put you on the radar of firm partners and other people that have a say in the corporate promotion process.

Bottom Line

The tripod of professional intuition, networking, and radar-placement are among the most important factors necessary to catapult today’s young lawyer into the limelight.

Legal AI is here and it is important that ambitious, young lawyers take advantage of it and not join most of the older generation that is condemning it. As Marcus Janko, Partner at KLIEMT.HR Lawyers –German member of IUS LABORIS- put it, “understanding and effectively utilizing legaltech solutions helps us to provide better, more focused and more cost-effective client service”.

Flow with the tide or be wave-ed away into irrelevance

The Future of Formal Education is EdTech

Digilaw the future of formal education is edtech


Edtech is the applicatory transformation of education with technology. The sector is expected to grow at a rate of 7%, amounting to $252 million by 2020.

According to I.K Davies, “Educational technology (EdTech) is concerned with the problems of education and training context and it is characterized by the disciplined and systematic approach to the organization of resources for learning”. In simpler terms, EdTech is basically a learning process through which the internet serves as the bedrock. There is an urgent need for compliance with global shifts in formal education, in order to improve the training and evaluation of students in Nigeria.

Is EdTech Necessary? How Can It Be Adopted?

Everyone learns better online learning as opposed to traditional learning within the four walls of a lecture room. This technological revolution has led to remarkable changes in the way content is accessed, consumed, discussed and distributed. Educational courses are particularly advantageous for students with part time jobs.
The number of EdTech solutions leveraging on the internet is indeed spiraling, with each of them attempting to solve a specific problem. With an estimated population of over 193 million, with 162 million mobile subscribers, an internet penetration rate at 84%, and about 104.6 million internet users as of August 2018, these EdTech startups have gained some level of traction.

According to Statistics, about 10.5 million, (60% coming from Northern Nigeria) are currently out of school. This is the highest number in the world. This figure probably sounds unsurprising. It should be noted that Nigeria’s child population is just about 80 million. The focus of EdTech so far has been extending access to education beyond the conventional classroom setting. This way, every person or student rather can learn in a more efficient way.

“Learning at the tertiary level of education in Nigeria could be described as being effective if it results in bringing about the expected transformations in the attitude, skills and knowledge of higher education students over a period of time”.

– Babalola and Jaiyeoba 2008

The main concern about the poor learning in Nigerian Universities becomes more intense as many Nigerian youths find it difficult to gain employment in the formal sector. It is for this reason, among other that Babalola and Jaiyeoba stressed that university education must keep pace with the advances of learning technologies.

There are several EdTech startups in Nigeria focused on primary and secondary schools such as Prepclass, ProTeach, ScholarX, Tutor.ng, etc. However, what about tertiary institutions in Nigeria? Are there tertiary institutions making use of EdTech? A notable example of this is National Open University of Nigeria which leverages on technology. They upload their lecture notes on their courseware sites. Students of NOUN make use of the website for virtually everything except writing exams. take tests online, download materials from the internet and pay school fees online. Students can learn at their own convenience. This model works for students with part time jobs or families to cater for.
Universities can join the EdTech train by creating their own platform or partnering with EdTech platforms such as Edx, Coursera, Udemy and so on.

Barriers to EdTech in Nigeria

While the EdTech sector is indeed making progress, there is still a lot of resistance slowing down its overall progress. Most of the problems of EdTech are often related to misconceptions, resistance to change and the unwillingness to embrace the change technology brings. A few of these problems include:

  • Inadequate funding
  • Dilapidated infrastructure
  • Poor mindsets/lack of exposure
  • Lack of professionally trained personnel
  • Slow progression of the educational sector in Nigeria
  • Bureaucratic bottlenecks and rigid organizational structure
  • The Nigerian educational system places too much emphasis on examination and certification. This limits the extent to which EdTech tools and techniques can be used in the instructional process


Typically, teaching and learning in Nigerian universities places the teacher/lecturer at the center of everything. In this scenario, learning is quite passive for the student. Teachers most times do the intellectual work while students are the docile receptacles. As technology disrupts other sectors, it will change expectations of what Nigerian university students must learn and how they learn in order to function effectively. EdTech is not a panacea to all educational problems, it does have numerous benefits.

Will the Huawei Harmony OS survive where others failed?

huawei logo harmony os
The Biblical Ark saved Noah, but is is uncertain if Ark/now Harmony OS will save Huawei

Why did Huawei create Harmony OS?

On Friday the 10th of August, Huawei announced its Harmony OS as a fallback option in the event they lose access to the Android ecosystem. Before this, the company had announced the creation of the HongMeng/Ark OS after Google revoked its Android license. This announcement came on the heels of the Trump administration adding Huawei and 70 of its affiliates to its “entity list” of firms deemed threats to national security, effectively prohibiting the firm from buying US technology and components. Furthermore, Trump also issued an executive order banning US firms from using technology produced by any company assessed to be a national security risk.

No doubt, Trump’s decision in May to blacklist Huawei, China’s largest technology company, roiled global markets which are still adjusting to  the impact of higher tariffs in a year-long trade war that risks upending global supply chains. A similar ban on China’s ZTE Corporation last year brought the smaller competitor to Huawei to its knees before it was removed last July.

However, the main focus of this article is the sustainability of Huawei floating an operating system. Is the Huawei Harmony OS a last-ditch attempt, a sustainable venture or a wild goose chase? Will Huawei succeed where Microsoft, Amazon, HP, Samsung, Intel, Nokia, Mozilla, Blackberry, and many others have failed?

OS Failures of the Past

Many factors go into the success of an OS. Performance and excellent user interface are part, but the market and users’ perceptions mostly make or mar an OS. Pretty much, the smartphone race is a rat race between Android and iOS, while the computer segment is shared between Windows, MacOS, and Linux. Initially, Huawei wanted its OS to work on phone, laptop, and everything in between which is overstretching its limits, due to the ban. But now, the Huawei Harmony OS will be restricted to cars, watches, and personal computers. It is expected to launch by 2020. The company is still prepared to launch the OS for smartphones, in the event that it can no longer access the Android ecosystem in the future.

Amazon’s Fire OS was an adequate phone when compared to the ones on the market then. It even had a few exceptional features, but in a crowded space dominated by Apple and Android devices, merely releasing something “adequate” isn’t enough. To stand out, a smartphone like the Fire, which arrived seven years after the first iPhone and six years after the first Android device, requires breakthrough hardware and software. Thus, even though the Fire Phone was based on AOSP like Huawei plans to do, it failed.

Windows Phone, on the other hand, was revolutionary in design and performance, and Microsoft already had experience with manufacturing phones. However, it failed primarily because Microsoft at that point was not manufacturing its own phone early enough and held a fatally tight rein on it how much original equipment manufacturers (OEMs) can customize their phones. Furthermore, there was hardly any application for the OS, and even though Microsoft made it easy for developers to port  apps from other OS easily, they did not do so.

Palm’s Web OS failed because of performance issues while HP’s Web OS was a basic phone at a premium price. “Good as” is not good enough.  “Slower than” isn’t going to displace anything.

Mozilla’s Firefox OS failed because developers weren’t interested in building apps for a platform with no users, and the net result was an app ecosystem that couldn’t even compete with Windows phones. Samsung’s Tizen OS failed because of its security flaws, delays, lack of apps, and it only catered for low-end users.

On the other hand, Android, iOS, Windows, MacOS, Linux, and even Chrome OS were also successful because they were mostly either the first to corner the market.

Can Harmony OS Compete with Android OS?

Huawei is hard at work on its alternative operating system which it claims has been in production for two years and is prepared to launch it in their flagship Mate 30. The brand has reportedly shipped 1 million devices for testing purposes and is also working hard on trademarking the Harmony name in a growing number of countries across the world. The operating system won’t just be for phones, either. According to the report, it’s open to mobile phones, computers, tablets, TVs, cars, and smart wearable devices.

Building a new mobile OS from scratch is certainly no easy feat, and competing with established players like Android and iOS will undoubtedly be a challenging undertaking. Building a smartphone platform is easier than supporting and nurturing it continuously, especially when there are well-established players in the market. In this day and age, supporting services and the availability of apps play a huge part in a smartphone platform’s success. In case of Android, it has strong support from Google’s ultra-popular and successful services like Google Search, Google Now, Gmail, Google Drive, Google Maps, Google Chrome, Google Translate, and Hangouts. Many people have invested their data into Google’s services, and their absence won’t be entertained. All of those services are tightly integrated into the platform and won’t be able to access it with Harmony OS. Without access to it, many people won’t bother with Huawei.

Huawei’s OS will be based on the Android Open Source Platform (AOSP), which is a free system that any brand can use as an underlying foundation for its products. That means that android apps theoretically will work on it. The critical question is how the apps will be able to work on the OS – just because they’re compatible, doesn’t mean Huawei will be able to bring the full suite to its phones. There will probably be much manual side-loading, which will be an effort for consumers.

Without access to the Play Store, Huawei would be forced to work directly with developers to get them to create versions of their wares for its phones. This situation would be similar to that of Amazon’s Fire OS, which is based on AOSP but had its own app store, as the retail giant seeks to control the platform its Fire tablets and Echo devices run on. If Huawei does have to use AOSP, the consequences could be devastating, as access to a fully-stocked app store is crucial to the success of any modern smartphone. Nokia and Microsoft failed to make Windows Phones a viable alternative to Android and Apple’s iOS, even though both brands poured millions into developer tools and enticing the top app creators onto their platform.

To make things easier, Huawei is offering simple software for developers to tweak their apps to run on its phones, meaning they can be ported over with minimal effort. However, Microsoft provided something similar for the Windows Phone app portal and yet couldn’t maintain the momentum as phone sales stalled. It remains to be seen whether Huawei phones will continue to be sold in strong enough numbers worldwide for developers to update and maintain their apps. To increase their chances, Huawei has been pouring a lot of money to encourage developers to use their platform. Last year, they spent $70 million. They also have an attractive profit-sharing scheme, where they only keep 10% of the app profits while the rest goes to developers. This is higher than 30:70 sharing formula that Google uses. Apple also keeps 70% of sales revenue and 85% of sales subscription.

Notwithstanding, Apple still generates 70% more than Google when it come to app revenue, despite the latter’s larger market share in terms of devices. How Huawei’s OS will break the ranks of this duopoly remains to be seen.

Google also believes that the Chinese company cannot provide the level of security it has for the Android OS. A Huawei-modified version of Android OS would be more susceptible to being hacked. This is further compounded by the news that the WiFi Alliance and the SD Association, the standards-making bodies that govern the technology used for connectivity and mobile storage have ejected Huawei. While Huawei will still be able to use these technologies, they will not be certified by these bodies and Huawei will not be able to use better technologies until it is made public, thereby blunting its competitive edge.

The final verdict on the Harmony OS

Despite claims that Harmony is 60% faster than Android, Huawei still faces an increasingly onerous task going forward. But it’s undoubtedly smart for Huawei to save itself from getting locked out of the world’s largest mobile OS ecosystem. Even if it does, I seriously doubt whether it will be as polished or feature-rich as Android. The only OS-esque software we’ve seen from them, the mobile overlay EMUI, has been a mixed bag of features and design.

Huawei’s future as a device maker is getting murkier and murkier by the day. If it doesn’t settle with the US Commerce Department, it’ll be tough for the company to sustain outside China. Lastly, the loss of the Google Play Store – which for users outside of China is the key source of Android apps – and a lack of Google-made security updates could prove a significant drawback for the prospects of its future phones and tablets.

By Oyarinde Isreal, Research Associate at DigiLaw

AI in Warfare: Fiction or Impending Reality?

AI in warfare fiction or impending reality? agunbiade akintunde ifeanyichukwu

What is Artificial Intelligence (AI)?

There are many definitions of Artificial Intelligence (AI) but none of them effectively captures what AI is capable of. As such, I will not be defining AI, rather, I will be reporting the goal of AI as encapsulated at the 1956 Dartmouth Summer Project on Artificial Intelligence, where the science and technology of AI was properly born.

It goes thus:

‘To proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it’[i]

Although it has hardly been restated, this goal has the been the underlying drive behind every manifestation of AI since then. If it takes human intelligence and learning to get a thing done, then it can be replicated by a machine, once we break down the components of the particular intelligence and learning approach at play. It took a high level of numerical intelligence and consistent practice for Gary Kasparov to become the world chess champion.[ii] By replicating the rules of the game, approximately 200 million possible chess positions and reducing them to algorithms, IBM’s Deep Blue was developed and trained until it defeated the world chess champion.[iii]

Why is a discussion of AI in warfare important?

This essay is premised on several real and assumed fears about the application of AI. In the news, we hear about China’s credit scoring system that ranks citizens based on metrics not publicly available. Those who fall short can be legally denied the most basic amenities, such as a train ride, access to the best schools, or being publicly named as a bad citizen.[iv] In China, AI has made the police state a reality, not just something confined to the pages of George Orwell’s ‘1984’.

In the USA, we hear of risk assessment systems like COMPAS that have delivered recommendations skewed against persons of colour, as a result of data gaps.[v] Clearly, the use and abuse of AI is no respecter of economic and political ideology. All nations who can afford to, have shown that they have the tendency to use AI wrongly.

When you combine these factual occurrences with fictional notes form popular movies and books about robots supplanting and almost destroying the human race, it’s easy to understand why the concept of ‘Artificial Intelligence (AI) in Warfare’ may be greeted with trepidation. War is already a costly business, but at least we can hold humans responsible and make them account for their misdeeds. But how do you negotiate a truce with a weaponized drone gone haywire or an artificially intelligent missile guiding system?

What are the real factors that necessitate these fears?

The examples earlier given may seem farfetched unless you consider the fact that security agencies world over have been engaged in using advanced technologies. In the years after 1956, the US Government, through the Defence Department and associated agencies invested heavily in AI research & development.[vi] This trend continued through till the 70’s when public pressure mounted against this, as politicians and the people felt that the funds should be spent on more beneficial activities. This led to the period known as the AI Winter, when funding for AI research & development became scarce and far between.

Although it only kicked off in the late 90’s due to private interests that have built and sustained the AI industry to its current levels, renewed government interest in AI has once again gone in the direction of security purposes, rather than solving numerous social challenges like climate change, food security, education, healthcare, etc. Recently, it took the public opposition of ‘Googlers’ (the term of reference for people who work at Google) to stop the company from renewing its contract with the Defence Department to work on the Maven program, a system that uses AI to interpret video images for improving the targeting of drone strikes.[vii]

We might praise the company for choosing to heed its workforce, thus displaying great company culture, but the fate of the world cannot be hinged on isolated good acts. Another company could have chosen to ignore such calls. Google could afford to pass over the opportunity because it is big enough, but a smaller company may not. Even the government in question will not stop because one organization turned it down.

As long as governments the world over continue to see AI within the narrow prism of a tool to be used to enhance their security capabilities, the use of AI in warfare is not just a potential threat, but an actual long-term inevitable occurrence.

Are there benefits to be derived from AI in warfare?

It is worth considering the benefits that AI in warfare could bring. By doing so, I am not endorsing war, but since it is a potential outcome of human conflict, the possibility of machines taking the place of man in warfare is worth considering.

Since World War 1, when advances in technology began to play a central role in who had the upper hand, millions of lives have been lost on the side combatants and innocents alike. Developing artificially intelligent robots that could take the place of human military personnel would significantly reduce or eliminate the unnecessary human casualties that war produces. Wars could be finished in shorter timespans, rather than dragging on for years. Human troops require feeding, rest, consistent morale boosting and several other factors which may not guarantee victory. But a robot army, navy, or air force could fight 24/7, or as long as their power sources last, irrespective of external factors.

Also, machines would most likely show respect to the civil rights of non-combatants as opposed to human soldiers. No machine intentionally would rape an innocent woman, line civilians up for a firing squad, wipe out entire villages, or destroy national monuments. All these atrocities have one thing in common; humans committed them. So, is there a case for Artificial Intelligence (AI) in Warfare? Yes, there is.

Over the years, the tide of convention drafting has veered towards regulating the activities of men in the course of war. There are several of them, but I will make mention of the underlying principles that will be advanced by the foray of AI in warfare. They are as follows:

  • That war should be limited to achieving the political goals that started the war and should not include unnecessary destruction
  • Wars should be brought to an end as quickly as possible
  • People and property that do not contribute to the war effort should be protected against unnecessary destruction and hardship.

If these are the minimum objectives that the laws of war seek to achieve, then AI can be effectively used to ensure that they are completely fulfilled.

Robot soldiers or weapons could be programmed only to harm enemy personnel, while leaving the civilian population untouched. If wars were only focused on the armed forces of opposing nations and not on civilians and properties, they would be prosecuted in shorter timeframes. The needless destruction, hardship, and economic turmoil that usually follows war when people and their livelihood is destroyed would be averted.

How can understanding the types of AI help us appreciate its relevance in warfare?

In understanding the place of AI in war, a deeper understanding of AI needs to be gained. Broadly speaking, AI can be divided into ‘Weak AI’ or ‘Narrow AI’, and ‘Strong AI’ or ‘General AI’. Most of the manifestations of AI we see today are ‘Weak AI’. It is so-called because they replicate humans in a specific set of tasks like the way Siri, Alexa, and Cortana, all virtual assistants, can answer your questions, provide you directions, but cannot operate a car. A particular data analytics system may be able to interpret data to give recommendations on whether a person should be given a loan, but that same system would be unable to give an assessment on whether the person should be granted bail or not.

‘Strong’ or ‘General’ AI only exists now as a theoretical concept. It is based on the theory that autonomous agents can be developed which can perform a wide variety of distinct activities just like the average human. Imagine all the AI products and services you know rolled in one and you have a rough idea of what Strong AI is.

It is important to bring these distinctions to light in this essay to show how AI can be effectively used now. Currently, AI can only be developed in narrow terms. It is thus possible to develop AI tools for war that perform very specific functions and will be incapable of violating the laws of war because of their algorithmic makeup.

How will AI affect the laws of war?

Doing so will however not come easy. The rules in their current form accommodate the application of autonomous weapons, within the context of Article 36, Protocol 1 of the Geneva Conventions 0f 1949, which provides that new weapons, means, or method of warfare, must be tested by a High Contracting Party to determine whether its employment would in some or all circumstances be prohibited by the Protocol or any other international applicable law available. Specific updates may still have to be made to effectively regulate the deployment of AI in warfare.

AI may replace humans wholly or in some specific assaults of war. Because the laws that regulate these aspects are tailored towards humans and impose liabilities simply extending them to AI tools may pose challenges. For instance, it would require that we assume that AI has some form of consciousness and legal personality in order to hold them liable for the consequences of their actions, in that case.

Another challenge would be defining the limits of AI in warfare. With humans, a simple propaganda speech or a series of meetings would be adequate in getting the soldier informed about the objectives in a war. But with AI, this process cannot be applied; it is most likely that the principal objectives would either be programmed into it or transmitted by a server. In some other cases, it is possible for them to perform actions that even their makers did not envisage, as they get more autonomous. Once put in the real-world environment, the advanced AI system could learn from its environment, thus leading it to act in a way that its designers did not deem feasible. We saw a glimpse of this in the chatbot that Microsoft once launched on Twitter. In less than a day of being launched, it had learnt from the Twitter environment and was spewing racist, sexist, and hateful comments on Twitter, none of which were anticipated by Microsoft, so they deleted it.[viii] These kinds of AI systems are self-imbued with the ability to continue modifying themselves, improving themselves from constant interactions, such that their behaviour is based on the new data they have been exposed to, not the original instructions of the developer. AI tools will largely perform tasks they have programmed to do. If in the performance of these tasks, they commit violations of the laws of war, it becomes necessary to consider where liability will lie.

What is the way forward?

To solve the challenge that AI poses if introduced to warfare, there are several approaches we can take. First, we could decide to expressly ban the application of AI. This precautionary approach might prove effective, but like all blanket bans, it would also impede the development of some forms of AI that could otherwise be beneficial to humanity.

Secondly, we could decide to not stand in its way, and allow all nations of the world with the interest and capacity to develop AI weapons to do so. Towing this permissive route would imply that we accept the risks and potential fallouts, but we would be faced with the challenge of how to apply our international laws of war, especially when their use leads to injury.

We could also go all out and impose a strict liability regime on the developers and users of these AI systems, such that they would be held responsible for all fallouts of their machines, irrespective of circumstances. This approach is by all means, the simplest of all, and would not require much out of the box thinking to bring to reality. We would simply be extending already established legal principles to a new subject matter. This approach, just like the first, might also stifle he development of AI that could greatly enhance the human condition.

Another way we could do is to accept the challenge that AI poses, not just as a tool of war, but as a tool in itself for whatever purposes it is applied to; a tool with the potential of outworking and outsmarting its masters. By accepting the challenge, it poses, we would commit to rethink our entire legal and ethical framework, in other to discover new definitions and principles that would be applicable, without unnecessary pain or gain in the coming Singularity Age, when machine intelligence is expected to match and possibly outperform human intelligence.[ix]

Whatever approach we prefer, we must ensure that we keep three things in mind:

 One, that AI is first a tool for enhancing our understanding and improving our world. Two, looking at AI from the narrow prism of a tool for advanced warfare is as unfair as failing to prepare for its use in warfare, which is inevitable. Three, Artificial Intelligence like a mirror, reflecting all that is good, bad, and ugly about us, and throwing all this at us. So before you point an accusing finger at the technology, remember that there are four fingers, pointed back at you.

[i] Program of Events, AI@50 – Dartmouth College Artificial Intelligence Conference: The Next Fifty Years, July 13 – 15, 2006, pg. 1

[ii] The Editors of Encyclopaedia Britannica, Garry Kasparov – Soviet-born Chess Player (Encyclopaedia Britannica, 9 April 2019) www.britannica.com/biography/Garry-Kasparov accessed 19 May 2019

[iii] Deep Blue (IBM 100 – Icons of Progress) www.ibm.com/history/ibm100/us/en/icons/deepblue

[iv] Alexandra Ma China has started ranking citizens with a creepy ‘social credit’ system – here’s what you can do wrong, and the embarrassing, demeaning ways they can punish you (Business Insider – October 29th, 2018) www.businessinsider.com/china-social-credit-system-punishments-and-rewards-explained-2018-4

[v] Carole Piovesan and Vivian Ntiri, ‘Adjudication by algorithm: The risks and benefits of artificial intelligence in judicial decision-making’, The Advocates Journal, Spring 2018, pgs. 42 – 45

[vi]  ‘DARPA Announces $2 Billion Campaign to Develop Next Wave of AI Technologies’ (Defence Advanced Research Projects Agency – DARPA 7th of September 2018) https://www.darpa.mil/news-events/2018-09-07

[vii] Daisuke Wakabayashi and Scott Shane, Google Will Not Renew Pentagon Contract That Upset Employees, (The New York Times, June 1st, 2018) www.nytimes.com/2018/06/01/technology/google-pentagon-project-maven.amp.html

[viii] James Vincent, Twitter taught Microsoft’s AI chatbot to be a racist asshole in less than a day, (The Verge, March 24th, 2016) www.theverge.com/platform/amp/2016/3/24/11297050/tay-microsoft-chatbot-racist

[ix] Roey Tzezana, Singularity: Explain It to Me Like I’m 5-Years-Old, Futurism, www.futurism.com/singularity-explain-it-to-me-like-im-5-years-old/amp

LegalTech: How It all Began

The number one benefit of information technology is that it empowers people to do what they want to do. It lets people be creative. It lets people be productive…”

The History of Legaltech

What is Legaltech?

When Steve Ballmer made the above statement about the nature of technology, he most likely didn’t accurately fathom how phenomenal legaltech or any tech at all, would later become. Today, it’s crystal clear to the blind, and beat-by-dre audible to the deaf that technology is really being creatively and productively deployed to ease the performance of tasks and by extension, an improvement in the quality of life. Through the pages of history, tech advancements are being tailored to lead the charge in disrupting formerly-traditional and cult-like fields and professions, like the legal profession – through legaltech.

You may erroneously think or believe that the advent of legaltech began only yesterday. If you really do, you are fundamentally mistaken, for legaltech has been around since the early evolution of tech itself. So, join the voyage as we look at the age-long history of LegalTech within the confines of this space.

But first, let’s get the basics out of the way: What really is meant by the term “LegalTech”?

An inclusive definition of this term is two-fold:
One which refers to the technologies – soft or hard –that help attorneys attend to clients’ legal needs in a fast, efficient manner; and
the other which consist wholly of tech solutions and innovations that aid or help consumers to effectively address legal needs by themselves without requiring the direct services of a lawyer.

The nature of the term LegalTech is such that makes it cover innovations exclusive and distinct only to the legal profession but still yet encompassing some other tech solutions tailored for all professions alike. So, the popular word-processing package, MS-Word comes to mind here as it forms a part of the first category due to its continual usage in the legal profession, alongside other attorney-friendly packages like Diligen, Zoom.ai, MyCase, AbacusLaw and many more technologies that help lawyers with efficient practice management, electronic discovery, client billing, due diligence and many more. You’d find LegalZoom, Wevorce, UpCounsel, Rocket Lawyers and many more others on the flipside, focused on expanding the frontier of justice and legal services to disadvantaged societal classes who can’t perhaps afford pricey attorney fees, but still nonetheless have pressing legal needs.

Need To Examine LegalTech History

As Marcus Garvey succinctly put it, “A people without the knowledge of their past history, origin… is like a tree without roots”. What’s a tree without it? A lifeless creature!

For Legal AI – as it’s fondly referred to by some – not to slowly wither or for mistakes to be repeated, it’s important to take a look at the general history of LegalTech.

Fundamentally, the life of the law – whether at the bar or the bench – has always and continues to be, the dependence on and usage of Law Reports in the stringing together of arguments as well as adjudication of disputes. The year 1974 can thus perhaps be marked as the beginning of specialized tech intrusion into the legal profession with the introduction of the ground-breaking LexisNexis little red UBIQ terminal, which allowed attorneys to source for case laws online rather than pore over musty paperbacks.

logo of lexisnexis history of legaltech

But there had existed some other form of general tech usage in the profession like the Xerox commercialized fax machine available since 1964, and Arpanet which offered store-and-forward messaging services on networked computers –metamorphosing into modern-day email.
With the seed of electronic law reports safely planted in the legal stratosphere, general workplace tech revolution spun towards document creation with the introduction of a low-cost dedicated word processing mini-computer by Wang Laboratories –around 1973.

wang computer 2200 history of legaltech
The Wang Computer 2200

Since then till 1979, plenty of law firms acquired for itself either a Wang Computer or similar alternatives on the market like fax machines as the legal practitioners’ focus leapt from pure document searching to document creation.

The import of these First Gen tech solutions on the history of legaltech was that they accelerated the pace of legal practice considerably. Turnaround for legal documents became faster as hand-written cutting and pasting vanished or reduced considerably, and electronic discovery became fast-tracked with the swift delivery of documents through faxing and new, efficient courier services.

The Advent Of Early PCs

Before the release of Personal Mini-Computers, what law firms hitherto had were central word processing departments or pools consisting of employees who processed documents for all attorneys of the firm. The purchase cost and skill of use were perhaps responsible for the limited number of such processors in law firms. But the release of the World’s first Personal Computer by IBM in 1981 expanded the reach of tech adoption in the profession. Adventurous lawyers were pushed to begin learning how to use PCs, particularly word processing so they could type their documents themselves. And yes, it was an adventure because such attorneys had to at least learn a little of the original disk operating system –DOS, famous for its cryptic “C:>” prompts.

Around 1984 to be precise, Apple’s Macintosh became another credible alternative to IBM with its head start in “graphical user interface,” which totally eliminated the need to learn computer codes and commands. Still, large firms chose to stick with PCs for corporate operations.
By the late 80’s, the rat race had already begun! Several PC applications targeted for use in the legal profession had sprang up to offer varying services. The likes of Summation and Concordance and some others started to gain prominence as litigation support software and many others.
As with all new things –tech especially, everyone wanted to have a piece of the pie: Yes, having a brand-new PC in your office had a nice ring to it as you gist with fellow attorneys. Firms therefore had a hard time allocating PCs due to their scarce supply. The way out was as Tom Sawyer Esq put it: Make lawyers explain how they would use a PC, and only those with the best answers got one.


As with everything techy, the essence of interconnectivity cannot downplayed. The main issue early PC users faced was the inability to connect computers together for sharing of files and information. Instead, floppy disks were a common trend among users for the transfer of files from firm to firm. Moreso, full utilization of printers presented yet another uphill task because of their incapability to network with more than one PC, despite their pricey market value, leaving them utterly under-utilized. Succour came by 1985 when Local Area Networks (LANs) started spreading like wildfire, enabling the saving of files to a central network drive.

depiction of local area network history of legaltech
Depiction of a Local Area Network (LAN)

By that, printer-sharing by several computers became a reality too.
LANs also facilitated the shuffling of e-mails between and among attorneys of the same firm – and at times, those of other firms – allowing for easy share of documents and information. It didn’t therefore come as much of a surprise when the First World Wide Web (www) servers were turned on in 1989.

The Microsoft Story

first logo of microsoft history  of legaltech
First logo of Microsoft

The role of Microsoft as a general tech company cannot be overemphasized in the history of legaltech. So, by the year 1992, Microsoft had premiered version 3.1 of its Windows Operating System which sold widely and globally due to its use of friendly graphical interface, eliminating the cumbersome DOS command line. However, the legal market didn’t so easily give-in to Windows migrations, because of the expense. While Windows applications stormed many markets, legal vendors continued to focus on DOS upgrades since that was all the market desired. But in the long-run, the market caved. Asides from its graphical interface feature which made it easier for most people to use the PC, it provided for “task switching” allowing users to run multiple applications simultaneously (in contrast to one at a time in DOS).

Due to the increasing number of Windows users in the Legal Profession, a wide range of Windows legal applications were readily available by 1995, with the likes of docketing, timing and billing, case management as well as other specialized legaltech tools for various law practices – IP, Real Estate, Criminal Law.

A considerable increase in the percentage of legaltech consumers led to decreasing prices, with an upward movement in the processing capabilities. Newer advances in litigation support through vendors continued to come up including; ways on how to scan documents, convert docs to images, as well as ‘search-and-find’ systems for lawyers.

The World Wide Web

The year 1994 would go down as one of the most memorable for the legal profession and all other professions alike. A PC software called ‘Mosaic’ (later known as Netscape Browser) with capability to increase the ease of surf of the World Wide Web and accessing resources, was announced to the surprise of the whole world which had just recovered from the release of Windows version 95. With this announcement came corporations’ rush to establish online presence. As usual, most law firms resisted the urge, but an accentuation of demands by clients pushed most law firms to move their visibility online, and partly aid internet-enabled communications. Up till today, law firms still remain hesitant about questions like: Do clients visit a law firm website? Would potential recruits? But they’ve nonetheless since gotten on board, with some law firms’ spending more on their websites than some other bigger corporations.
Coincidentally by 1996, the use of e-mail through the WWW had become more widespread as attachments to email began to support non-text files, leading to an explosion of data.


The year 2000 opened a new chapter with the introduction of the first virtual law office and some other cloud-based software including Clio, CosmoLex, MyCase, Rocket Matter and many more.
Following the dot-com bubble of 2000, tech spenders have gotten wiser. The watchword has since been: Getting more value at lesser prices – as against the hitherto, Getting more value at whatever prices. Partly because law firms were not caught in the unfortunate web of the dot-com bubble, investment in tech by law firms has continued to grow considerably, while those of other markets has normalized. Matter of fact, the coming on board of plenty of younger generation-attorneys who are more familiar in and comfortable with new technology into the profession, has helped fast track the development, use and investment in legaltech nowadays.
If there’s anything at all that modern law firms must’ve learnt, it is that timely conformity with tech evolution is as important as living modern life itself: You either adjust or get stubbed out.
PCs running on Windows OS continue to become more and more relevant in today’s law firms, gaining more traction than alternatives like Mac PCs. This can of course be attributed to the wide gap in the cost of acquiring either of them. Nowadays, there’s hardly any attorney’s office you’d visit that you wouldn’t be greeted with sleek, fast PCs running MS-Windows. Matter of fact, the advent of affordable notebooks and other handheld devices with word processing capabilities, have further simplified the adoption of legaltech by law firms and legal practitioners. You probably wouldn’t need to go about with your mini-laptops to draft an urgent letter for a client since same could be done by just whipping out your mobile smartphones from your pockets.

On the software angle, legaltech solutions can be said to have improved considerably too. More and more powerful, efficient PC apps and softwares are being ‘written’ to address varying needs like e-discovery, online law reports, document organization and indexing, due diligence and many more others.

The modern lawyer’s PC’s functionality now goes beyond document creation and viewing alone, but a mobile workstation where legal research can be carried out, arguments can be marshalled, connection and communication can be established with the outside world, automation of back office functions including client billing, conflict clearance, schedule management and many more other exotic tasks.

Conclusively, one pivotal thing remains constant throughout the history of legaltech: the inalienable desire of attorneys and their firms to discover, manage and manipulate documents in their favour in fast, efficient and cheap manners. As that desire is assuredly handed down to younger generations, legaltech development will continually go from strength-to-strength.

Additionally, modern law firm competition for more clients and billables will also continue to induce legaltech adoption as firms strive to outpace themselves, cutting down on wages but yet stepping up efficiency at the workplace.

For Nigeria and the most of Africa that are just beginning to see sense in the use of legaltech –as with all other tech adoptions, the future is indeed bright.

How Iran plans to use Cryptocurrencies to circumvent US sanctions

How Iran plans to use Cryptocurrencies to circumvent sanctions DigiLaw Favour Oyeleke

The Story so far

Iran has been known to consistently struggle with segregation from global payment systems, limitations on its nuclear programme and oil export, due to the United States sanctions over the years. The situation worsened recently after the re-imposed U.S. sanctions forced Iran to engage in traditional banking. SWIFT banned major Iranian banks from gaining access to its largely used cross-border payment services. The severe economic sanctions imposed by the US were solely induced to obstruct any form of trade with Iran. As a result, the country’s financial system has become hampered. The Rial took a downward spiral, falling from 36,000 rials per dollar to 60,000 rials per dollar from September 2017 – April 2018.

Map of iran
Map of Iran

Iran & Cryptocurrencies: The Status Quo

Prior to this, the Central Bank of Iran (CBI) banned Iranian banks from handling cryptocurrency. But with the prevalent economic war on the country, Iran is making attempts to leverage on cryptocurrency as a solution to the falling value of its currency. Following the lifting of the ban on cryptocurrency, Iran took bold steps to use cryptocurrency in reversing the negative effects of the US economic sanctions. In late January, the Central Bank of Iran (CBI) proposed a draft of its regulations and guidelines on cryptocurrency, dubbing it the ‘Version 0.0′ Framework.

Iran & Cryptocurrencies: The New Approach

The new framework is to substitute the blanket ban on cryptocurrency that was imposed in April 2018, during the early days of its currency crisis. Iran is relaxing its stand on cryptocurrency not only to evade economic sanctions, but also in respect of sensitive rules on foreign currencies. The country is taking steps to find alternatives to traditional banking by exploring an entirely different economic path (Cryptocurrency). With this draft, the CBI aspires to organize and outline the extent to which continuous crypto operations can be encouraged in the country and also enable traders set their goals for the future.

Although, the draft regulatory framework recognizes the importance of the cryptocurrency market, there still exists the imposition of restriction on the use of virtual currency.

Features of Version 0.0 Framework

The Version 0.0 Draft recognizes and recommends bitcoin, initial coin offerings, tokens, cryptocurrency wallets, cryptocurrency exchange bureaus and even mining cryptocurrencies.

Authorities are to establish anti-money laundering initiatives to fight against the financing of terrorism with cryptocurrencies. However, every cryptocurrency must be pegged to the Rial. The digital tokens can only be utilized by banks or for other domestic transactions if they are backed by the rial. Tokens that are not backed by the national currency, the rial, cannot be operated as modes of payment. Iranians are also barred from holding large amounts of global cryptocurrencies- specifically more than 10,000 euros is prohibited. If substantial amounts of money are put in crypto, it would affect the economy adversely.

The most consequential part of the proposed draft is the prohibition of global cryptocurrencies as methods of payment inside the country, to prevent greater value loss of the rial. The ban on using global cryptos as methods of payment in the Islamic Republic has raised lots of unsatisfied reactions from the country’s crypto community.

The Pro’s and Cons of the Proposed Framework

The CBI’s proposed draft had been regarded by most Iranians in the community as an inadequate regulatory framework that stands to obstruct people intending to develop valuable projects. Meanwhile, the Central Bank of Iran (CBI) stated that the ‘Version 0.0’ Framework is open to changes and feedbacks from the crypto community, and promises to review the framework to make it better. However, it would be advisable not to delay the decisions to be made on the regulations for cryptocurrencies. If the imposed restrictions on the use of digital currencies are relaxed, the country’s businesses and individuals can utilize them more assertively and with better clarity. Delaying the review of these limitations will only do more damage to Iran’s banking system and its national interests. In short, it is essential to properly establish clearly stated regulations for the use of digital currencies in due time.

The CBI’s proposed framework cannot be regarded as the best solution to Iran’s economic crisis. It is however the safest decision at the moment. With the pressure faced by the government from US reimposed sanctions and the adverse effects it attracts, the CBI can only make efforts to ensure the value of the native currency is preserved – which might possibly require the support of the cryptocurrency market.

Permitting different internationally accepted cryptocurrencies as payment methods in the country at this period could affect the Rial negatively. It could discourage chances of introducing cryptocurrencies that can meet the need for appropriate, solid and lasting solutions in Iran. For instance, some global cryptocurrencies are closely linked to the U. S. Dollar alone. This might benefit businesses and affluent citizens who will earn great amounts of cryptocurrencies, while average-income earners, still paid in Rials, would have diminishing meager wages.

On the other hand, the draft framework can be seen as a step forward. It implies that Iran concedes to the significant prevalence of cryptocurrency in the world today. Iranians are increasingly making transactions with cryptocurrencies around the world at an estimate of $10million worth of bitcoin daily; whether restricted or not. Cryptocurrency could be the new wave of the future at this point. Therefore, it will be unproductive to confine its use.

Iranian officials are actively working to generate sustainable plans that could boost Rial’s worth and the economy itself. Iran has been negotiating with eight other countries to introduce cryptocurrency into international financial transactions and its financial system. The eight countries are South Africa, Switzerland, UK, Russia, France, Austria, Germany and Bosnia. Talks have been ongoing since Iranian banks were barred from the SWIFT financial messaging services. The Islamic Republic believes its collaboration with these countries would be a massive move forward to facilitating transactions that would be independent of SWIFT.

Collaborating with other Countries

Iran is planning to develop a state-backed cryptocurrency – the ‘Crypto-Rial’. The Crypto-Rial will be used to make payments between institutions and banks that have made investments in the virtual currency. But, it is not clear yet whether the Crypto-Rial will serve as the legal tender for the country.

The Central Bank of Iran (CBI) aims to achieve the adoption of this national virtual currency that could potentially displace the U. S. dollars and then stabilize Iran’s financial status in the light of U. S. sanctions. The lifting of the ban on cryptocurrency unfolds better opportunities for taking up blockchain technology and cryptocurrency. Therefore, the embracing of blockchain technology and a sovereign cryptocurrency will introduce Iran to blockchain-based payment networks, which may even turn the traditional SWIFT network outdated.

How are other countries using Cryptocurrencies

Russia is also alleged to be looking into the creation of financial systems that will not be dependent on the SWIFT network. Venezuela has developed an oil-backed cryptocurrency, the Petro, to boost its economy and bypass US and EU restrictions. Venezuela has however, not been able to succeed with the drop in sale prices for its oil and low demand from global markets. This leaves the success of Iran’s intended government-issued cryptocurrency on a probability scale. For more about how countries are using cryptocurrencies, read this article by Abolarin Muhammad, “Cryptocurrencies: How different Countries Regulate them”

Takeaways for Nigeria

In the midst of these contentions, the main takeaway for countries like Nigeria should be how to democratize its economy with the new opportunities cryptocurrency provides. Nigeria has been failed by conventional money over and over again. The government needs to start paying attention to cryptocurrency by backing it up with proper regulations for a start.