The guide covers a wide range of crucial topics, from foreign investment and taxation to industry-specific considerations, including:

• Public-Private Partnerships (PPP)
• Telecommunications, Media, and Technology (TMT)

It was a pleasure to be part of the drafting team.

In the rapidly evolving landscape of artificial intelligence (AI), the legal profession stands at a crossroads. The United Nations' "Governing AI for Humanity" report, published in September 2024, provides a comprehensive analysis of the risks and opportunities associated with AI. For law firms and legal professionals, this report serves as a critical guide to navigating the complexities of AI integration. In this blog post, we will explore the key risks outlined in the report and discuss how businesses in the legal sector can proactively address these challenges.

Regulatory Compliance and Ethical Use

Increased Regulatory Scrutiny
The report emphasizes the need for robust regulatory frameworks to govern AI. Law firms must prepare for increased scrutiny and compliance requirements. This includes staying informed about emerging regulations and international standards. By doing so, firms can ensure that their AI practices are not only compliant but also aligned with global best practices.

Ethical Considerations

• Bias and Discrimination: AI systems can perpetuate biases if they are trained on biased data. Law firms must implement data auditing and algorithmic transparency to mitigate these risks. Ensuring that AI tools are fair and unbiased is crucial to maintaining the integrity of legal outcomes.
• Privacy: The handling of sensitive client data is a cornerstone of the legal profession. Law firms must enhance their data protection measures and be transparent about how AI is used to handle personal information. This not only complies with legal requirements but also builds trust with clients.

Economic and Social Impact

Job Displacement
The automation of legal tasks, such as document review and contract analysis, can lead to job displacement. While this can increase efficiency, it also poses significant challenges. Law firms should proactively manage this transition by investing in retraining programs and job reallocation. This approach not only supports employees but also ensures that the firm remains competitive in the AI-driven landscape.

Inequitable Access
There is a risk that smaller firms or those in less developed regions may not have access to the same AI technologies as larger firms. This can create a competitive imbalance. Law firms should explore partnerships and collaborations to ensure that the benefits of AI are more equitably distributed.

Security and Safety

Cybersecurity
The increased use of AI in legal practice heightens the risk of cybersecurity threats. Law firms must invest in robust cybersecurity measures, including regular security audits and employee training. A comprehensive incident response plan is also essential to address potential breaches and protect sensitive data.

Physical Safety
While less relevant to the legal profession, the use of AI in physical security systems, such as surveillance, must be managed ethically to avoid privacy violations. Law firms should ensure that any AI-driven security measures respect employee and client privacy.

Human Rights and Dignity

Surveillance and Control
The use of AI for workplace surveillance must be handled ethically to respect employee privacy and dignity. Law firms should establish clear policies and guidelines to ensure that AI is used responsibly and transparently.

Autonomy
Over-reliance on AI for decision-making can diminish human autonomy. Law firms should ensure that AI is used to augment, not replace, human judgment. This approach not only maintains the quality of legal services but also upholds the ethical standards of the profession.

Global Cooperation and Conflict

Geopolitical Tensions
The legal profession operates in a global context, and the uneven distribution of AI capabilities can lead to geopolitical tensions. Law firms must navigate these complexities to ensure compliance and maintain ethical standards. This may involve engaging in international collaborations and staying informed about global AI developments.

Conclusion

The "Governing AI for Humanity" report underscores the need for a proactive and ethical approach to AI in the legal profession. By staying informed about regulatory developments, implementing robust compliance programs, and ensuring the ethical use of AI, law firms can mitigate the risks and harness the benefits of AI to enhance their operations and serve their clients effectively.

By addressing these challenges head-on, the firms can not only stay ahead of the curve but also contribute to a more equitable and ethical future for the legal profession.

Credit: This blog post draws insights from the "Governing AI for Humanity" report, published by the United Nations in September 2024.

Nowadays, chatbots are the new normal – banks, stores, telecom operators and many other types of businesses are using them to communicate with customers. You can even order a coffee at your favorite cafe or replenish your kid’s wallet at their school canteen with a bot in Telegram.

ChatGPT-4, a generative large language model, has become notorious for opening a kind of Pandora's box, with BigTech companies racing to outperform each other, and new large language models (LLM, an abbreviation which exclusively meant Master of Law just a couple years ago) popping out at the speed of a bullet train – Phi, Mistral, Gemini, Grok, Claude, Llama to name the few.

As they grow in size exponentially, so do their capabilities.

Llama - the LLM developed by Meta* - is an example. Recently Llama3, the third generation of Llama LLM, was made available to the public.

The biggest Llama3 LLM has 70 billion parameters, was pre-trained and instruction-tuned based on a mix of publicly available data, and has s context length of 8 thousand tokens.

By the way, can you recall last eight thousand words, you’ve just said? Just to compare, "The Little Prince" by Antoine de Saint-Exupéry approximately is of this size.

In an effort to understand its limitations, the Llama3-70B instruction-tuned model, which is intended for assistant-like chat, was given a task to improve a clause from an EPCM contract (Engineering, Procurement and Construction Management).

How the model performed read at my full blog-post at Melling, Voitishkin and Partners.

Maybe you know, that AlphaGo is gone.

Those who love Go game will no longer enjoy the play of the AI against humans.

But may it, AlphaGo, object? May it claim that it, AlphaGo, desires to continue playing Go?

AlphaGo

Future of Go Summit, which took place in May 2017, was the final match event with AlphaGo.

The results of the competition are as follows:

• 3:0 AlphaGo vs Ke Jie (9 dan)
• 1:0 AlphaGo vs TeamGo (humans)

Afterwards Google Deep Mind team switched AlphaGo off.

But may it, AlphaGo, object? May it claim that it, AlphaGo, wants to continue playing Go?

The answer to this question is to be found in the legal field and depends on whether AlphaGo may be considered a legal subject.

In simple words, does AlphaGo have rights and obligations? In particular, does it have a right to life?

Definitions and legal concepts

During this discussion I will use two definitions artificially intelligent (ai) system and ai being as synonyms with ai system having focus on technical side when we describe parts and connections, and ai being as an attempt to compare to human being.

Smart machine, in turn, is an opposition to ai system.

I will also use some basic concepts of legal theory, such as law, legal subject, rule, right, obligation, and others.

In the legal doctrine there are different approaches in defining almost each of them, so to start, I will use the simplest ones, however this doesn't mean that the other approaches are not applicable.

Ai system

To begin our journey, first we need to draw a borderline between ai system, as a potential holder of rights and obligations, and a smart machine, which does not have any rights and obligations because it is a machine, although smart.

So, our first goal is to define what are the attributes of a system eligible to be qualified as a legal subject.

History

In search for the answer we need to go back to the ancient times, to the times of Caesars and Senators, patricians and plebeians, to the times of the Ancient Rome.

In the legal sphere the idea of the distinction between a legal subject and object goes back to Roman civil law, which was the most advanced legal system at the time and which developed the concepts of persona (a person) and rei (a thing).

Previously the status of a person was tightly connected to the citizenship status leading to the situation when in certain cases a human was considered a thing (rei).

This could happen for several reasons:

• the status could be inherited (a child of a slave was a slave),
• obtained
  • either a foreigner, a slave or a citizen of the rival state, captured during war, or
  • a Roman citizen who lost the status due to committing the offence.

A slave was the property of a master, and the master had full discretion in treatment of the slave, together with certain liabilities due to the behavior of the slave. By the way, we still use master/slave terminology in a tech sphere, i.e., master/slave disk, master branch (in git).

Today a state, which claims to be democratic, must ensure that a person (a human) may not be treated as a thing (rei). In case the human rights are violated, the democratic state has a legal duty to intervene to protect the rights of such a person.

A smart machine is a rei. It means that the smart machine may be an object of ownership, trade, use and disposal, and it is absurd to imagine that a car objects to its sale to the new owner or objects to scrapping, and the state intervenes to protect the car.

And what about ai being? Does it have a right to object to its sale? Or termination?

Does it have the duties and liabilities?

And would the threat of punishment be effective for ai being to enforce it to perform its duties and refrain from abusing its rights as it more or less works with humans?

Legal subject criteria

Let’s assume we have an intention to design an ai system which can be considered a legal subject, or in other words, a holder of rights and obligations, like

• a human,
• a legal entity,
• a state,
• a nation, or
• an international organization.

This list is not exhaustive, but above items are widely recognized as legal subjects.

Will

The common thing, which unites all of them and allows them to be qualified as the legal subject, is an ‘own, or separate will’. The separate will means the desire and intention to act (or refrain from action) in your own interest, where the word ‘own’ is understood in a very broad context.

For a human the will is a complex mix of basic needs, desires, wishes, which are significantly influenced by social, cultural, and religious context.

For a legal entity or international organization the will is derived from the statutory documents. The will, inter alia, may be:

• to gain profit for a commercial entity,
• to promote education for a nonprofit entity,
• to maintain peace for international security organization.

Formation of the will is a separate issue, but in general, there are several basic ways:

• unilaterally (for a person, absolute monarchy),
• by consensus
  • either by majority (i.e., at the general meeting of the shareholders, or at the parliament), or
  • unanimously (i.e., all permanent members of the UN Security Council).

So, the separate will is the first cornerstone.

Control

The second cornerstone is the ability to control your actions (including the ability to understand the consequences of an action or inaction).

Sharply this principle can be found in criminal law where minors and mentally diseased people are exempt from the prosecution because they are either

• unable to understand the consequences of their behavior or
• unable to control themselves.

Kleptomania is a good example as this disease is considered to be an inability to refrain from the urge of stealing and is performed by reasons other than personal use or financial gain.

Ai system design

So, the design of our ai system has to satisfy the following criteria:

• to vest ai system with its own will; and
• to allow ai system to control its actions and understand the consequences.

AI system practical issues

Now, let’s go further and assume such ai system is created. What intentions and desires would or could comprise the will of such ai being?

When we think about living organisms and different forms of life from biological point of view, the two basic needs first come to mind:

• the survival instinct, or self-preservation, and
• the reproduction.

For the living organisms both of them are tightly connected to the life-and-death question.

AI system death criteria

And what means death for an ai being?

Can we say that as along as the master copy of some particular code at some backup storage exists our ai being is alive? Or is it alive as long as the particular code is compiled and running at the particular hardware?

Is it only a source code? Or a source code plus results of training?

Let me deliberately leave these questions open, just in an effort to provoke the discussion. In the end, the developers’ community will give an answer, like with humans, whose death is testified by doctors, not lawyers.

Conflict of wills

The other area, which I want to address, is the conflict of wills arising due to interaction between legal subjects.

In particular, what would be the place of the ai system's ‘right to life’ among the rights of the other legal subjects?

The two major conflicts, which I want to discuss, are:

• human vs ai being, and
• ai being vs ai being.

Human vs ai being

In the conflict ‘human vs ai being’ the reference to Isaac Asimov’s Three Laws of Robotics should be made.

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.

2. A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law.

3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

The Second Law in conjunction with the Third Law implies that the mankind does not recognize the ai being’s right to life, as a human may request a robot to self-destruct, and the robot is obliged to obey, provided that such self-destruction is performed in compliance with the First Law, i.e., in the way, which does not bring any harm to human beings.

And when we look at the First Law, we see that for ai beings there are no exceptions.

The moral concept beyond the humans’ right to life (which is to certain extent an analog for the First Law) states that the human may not be deprived of his or her life, except certain extremely limited cases:

• capital punishment;
• war;
• abortion;
• euthanasia;
• justifiable homicide.

And only the last one — justifiable homicide — being widely recognized in most jurisdictions, although with varying scope.

Urging to suicide (which is what, to certain extent, the Second and Third Laws say) is not in the exceptions list and constitutes a major offence.

Ai being vs ai being

This context is far more complicated than the previous one and requires further research.

Conclusion

As a conclusion, I would like to note, that one day the mankind realized that a human being may not be a slave.

Maybe, one day the mankind will also realize that an ai being may not be a slave either.

Further reading

Responsibility and AI

Liability for AI Decision-Making: Some Legal and Ethical Considerations

Robots Rules

Liability for Artificial Intelligence and other emerging digital technologies

Artificial Intelligence ('AI'): Legal Liability Implications

Artificial Intelligence And Legal Responsibility

Rights for robots: why we need better AI regulation

Artificial intelligence, legal responsibility and civil rights

The smart contracts became a part of the reality. But any contract, even the smart one, contains a room for a dispute. The disputes from paper contracts are settled through arbitration. The smart contracts also need arbitration, the smart arbitration.

Smart arbitration

In the previous post I shared some ideas about the smart contracts and fusion solution, when both programming and natural languages move towards each other in an effort to allow the machines to understand legal texts and compile code with minimal interference by humans. As a result, smart arbitration may become possible.

I used the following definition of smart arbitration.

"Smart arbitration is the process of granting an arbitration award by machine in case of a dispute in connection with the smart contract."

Definition

While speaking about smart arbitration definition, I want to address the following aspects.

Smart contract

Any dispute arises out of or in connection with an agreement of some sort. So, smart arbitration is the way to settle disputes out of smart contracts. Smart arbitration is not applicable to other forms of contract, i.e., paper contracts.

For a dispute to be referred to an arbitration, a smart contract has to have a section or block of code, which invokes an arbitration procedure.

Dispute

Dispute is the state of a smart contract, when there is a claim from one party, which is objected by the other party, i.e., when there is no agreement between the parties on some issue.

Parties can object:

• the facts (i.e., inputs from oracles),
• clauses or conditions (i.e., coding bugs) or
• actions (i.e., smart contract performs not as intended).

Arbitration award

Arbitration award is the outcome of the dispute. Regarding smart contracts, an arbitration award may be designed as a function, which triggers actions to be performed by a smart contract.

Such action may be:

• reimbursement of damages or payment of penalties — this is simply an execution of some action by smart contract;
• granting extension of time — this is a change in the smart contract conditions, which means the time for completion must be variable, but not constant, and arbitration award function must have an override prefix;
• termination of smart contract.

Automatic execution of the smart award allows the parties enjoy the core feature of smart contract — execution autonomity.

Machine

The term machine is intended to be construed as wide as possible.

This can be a dedicated server maintained by a reputable international dispute resolution venue.

This can be peering network with some consensus algorithm.

This can be a mix of both above.

Consensus

Usually, arbitration panel consists of several arbitrators, three, sometimes five, rarely more, but always of odd number of persons. In case of even distribution of votes, the vote of the chairman prevails. This is the normal way of achieving consensus among humans.

In blockchain or distributed ledger technologies (DLTs) reaching consensus is far more complicated due to the scale of the network and variety of attacks intended to defraud the network.
A good example of the possible attack scenarios is given at a DLT network IOTA Tangle white paper, section 4, page 15, which can be found here.

However, if the arbitration network is in place, the consensus techniques developed for the blockchain and DLTs may be applicable.

Such arbitration network may consist of multiple nodes, each node being an arbitrator. If a dispute is referred to such arbitration network, each node makes a judgement upon certain algorithm. When the whole network reaches the consensus, the arbitration award is given.

The choice of the consensus algorithm largely depends on the network configuration.

If an established dispute resolution venue maintains the pool of dedicated servers, Raft consensus method may be the preferred choice. Raft naturally mimics the human arbitrators voting process, is a fault tolerant and provides good performance.

In Blockchain/DLTs world the choice of the consensus algorithm becomes one of the major issues. Will it be proof-of-work (PoW), proof-of-stake (PoS), or their derivatives, Tangle-based solution or any voting-based consensus mechanism?

Confidentiality

Blockchain/DLTs however bring to life some issues for in the commercial arbitration sphere. Because the entire case will be visible to the whole network, it becomes impossible to preserve confidentiality.

Masked Authenticated Messaging (MAM) might be a solution, however so far it is applicable to Tangle-based DLTs, specifically IOTA.

Codelegit Arbitration Rules

Here I want to address one of the solutions in the smart contracts arbitration sphere developed by Codelegit, namely Codelegit Arbitration Rules.

Codelegit developed a library, which can be inserted into a smart contract. According to Codelegit, once triggered the library will pause the further execution of the smart contract, and the dispute is referred to arbitration. Triggering the arbitration library can be performed by calling the function pauseAndSendToArbitrator().

My first concern is about suspending the execution of the smart contract. Execution suspension must not be mandatory and must be defined by the parties during the bargaining of the contract, as sometimes the parties explicitly agree that dispute is not a reason to suspend the performance (i.e., see FIDIC Red Book 1999 DAB guide, page 45, Proceed with the Works).

So, two options must be envisaged by a developer:

• suspend the smart contract as Codelegit proposes with pauseAndSendToArbitrator(); and
• continue the performance continueAndSendToArbitrator().

The second concern relates to the fact that Codelegit solution does not benefit from automatic execution feature, attributable to smart contracts. Codelegit Arbitration Library just suspends the execution, but the dispute is settled by human arbitrators.

Conclusion

The smart contracts have a huge potential. The flip side of the coin is the fact that agreements imply disputes. Inability to effectively resolve disputes out of smart contracts may become an obstacle for smart contracts further development.

So, the convenient, effective and trusted way to settle disputes out of smart contracts is to be designed. Smart arbitration may become a solution, which ideally fits for purpose.

Further reading

Consensus Mechanisms of Blockchain/DLT

Raft consensus

Law and Autonomous Systems Series: How to Resolve Smart Contract Disputes - Smart Arbitration as a Solution

IOTA Tangle Whitepaper

Masked Authenticated Messaging (MAM)

Codelegit

Codelegit Arbitration Rules

FIDIC Red Book 1999 DAB guide, page 45, Proceed with the Works

The invention of the legal databases allowed legal professionals to free time for more meaningful legal work. Since then however the improvements were merely of evolutionary nature. But what would be the next breakthrough technology, which would dramatically affect the legal profession?

Retrospective view

In the recent couple decades there were several changes to the way how legal professionals do their job.

The invention of the legal databases is one of the major improvements, which comes first to my mind. The ability to quickly search the law significantly improved the quality of the legal service. It also increased the efficiency of legal professionals and allowed us to free time for more meaningful legal work.

Since then however there are no any breakthrough technologies affecting the legal profession in the same manner, and so widely adopted.

Drafting tasks, negotiations, advising of clients, litigation nowadays are performed more or less in the same way as before.

There are some improvements in litigation, so you can file an application or motion online; or negotiations, when you can sign a legally binding document with the e-signature, but I don't dare to claim such moves as revolutionary as legal databases' invention.

Smart contracts

The general trend for the economy digitalization however puts the significant pressure on the law and the lawyers. This means that more and more transactions and business activity will be undertaken online, so this requires the legal community to tailor our tools to suit the digital economy needs.

One of such efforts led to invention of the smart contracts.

In the community there are a lot of discussions about smart contracts, their benefits and possible areas of use, so I will not focus on these topics here. I will just agree that smart contracts have the significant potential to change the legal profession as legal databases did.

Understanding smart contracts

The problem a typical lawyer usually faces with a smart contract today is the following.

Smart contract is the code, which means that special knowledge of a programming language is required to understand its conditions.

So, to address this issue:

• either a lawyer needs to learn how to code, or
• a smart contract must be duplicated in the natural language.

Learning to code

Learning to code is the most straightforward solution. It requires some efforts from a legal professional. As a result, one gains the additional skills.

If the goal is to understand the code, some sort of online course in the specific programming language may be enough to give a lawyer some basic understanding of the coding concepts and techniques. If a smart contract's code is well-commented by a developer, the result may be quite satisfactory.

There are however several concerns with this approach.

The first concern is that so far in the industry there is no standard programming language for smart contracts. Solidity claims to be the tailor-made solution, however general purpose languages like Java, Go, Kotlin are also used. This leads to a tough decision in which language one needs to invest time to learn.

The second concern is that learning a programming language on top of the legal education brings us away from one of the core principles — any law, contract, or ruling must be clearly understood by a non-professional.

The normal course of business requires clarity and the same understanding.

But if the contract in the natural language, in general, may be understood by an average person (with certain exceptions, when the contract is poorly drafted), the same conditions coded into a smart contract are definitely not clear without special skills in programming languages.

Duplicating

Expressing the code in the natural language tries to provide the solution from the opposite direction. It requires the involvement of the developer into the legal drafting process. As a result, the conditions of a smart contract can be understood.

The first concern is that duplicating requires additional time for drafting, and it is difficult to perform such work concurrently.

The second concern relates to errors in duplication. In case of inconsistency in the bilingual contracts this issue is solved by indication what language prevails, which means that both parties need to understand the prevailing language.

If code is the prevailing language and you, say as a judge, don't understand the code, and the other party claims that translation is incorrect, the expertise is required.

So far there is no market of professional advising companies who can translate a smart contract from programming to the natural language.

But if you find someone, on top of that, there could be the matter of trust.

As a result, if there is no established market, and you don't trust to the existing providers, you need to learn one or several programming languages to understand the smart contracts with all potential issues as discussed above.

Fusion

One of the solutions might be moving simultaneously in two directions: from one side, let's call it the first direction, the legal natural language must tend to be plain and explicit, and from the other side, the second direction, the programming language must tend to the natural language.

Django is one of the examples of moving in the second direction. Although the current implementation is imperfect, the idea of coding in natural language is compelling.

COBOL, aka COmmon Business Oriented Language, implies the same philosophy.

On the opposite flank, i.e. in the first direction, there are however no significant results.

But, imagine, if result is achieved at both sides, i.e

• if the condition of contract, law, arbitration award is explicit and plain, and
• if the code may be successfully compiled from the natural language,

there are a lot of opportunities for the legal technology as machines will be able to

• understand such conditions,
• transform them into the code, and
• execute such code.

Smart arbitration

One of possible implementations could be the smart arbitration.

Smart arbitration is the process of granting an arbitration award by machine in case of a dispute in connection with the smart contract.

One of the smart contract features is auto fulfillment if several conditions are met. In this scenario smart arbitration is not needed.

But so far there are a lot of conditions that are difficult or even impossible to code into the smart contract.

As an example, this may be a force majeure clause triggering extension of time, but the parties of the smart contract are in the dispute whether the event meets the force majeure criteria. In this case the machine (or smart arbitrator) could evaluate the criteria and make the decision.

Or this may be the question of an expert opinion, based on the algorithm, which both sides trust.

Conclusion

In conclusion, the fusion solution doesn't seem to be perfect or easy to implement, however it opens the possibilities to push the limits in which the legal community operates.