How should lawyers prepare for the future?

Learn about the future of law through understanding Strategic Legal Futures & Foresight.

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How should lawyers navigate disruption?

Learn about AI/Machine learning in law (including generative AI).

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How should the legal profession prepare for Industrial Revolution 4.0?

Learn about machine learning & robotic process automation in the legal sector.

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What critical legal skills must legal professionals acquire to face Industrial Revolution 4.0?

Legal professionals will need to learn AI/Machine learning in law (including generative AI) to be industry-ready.

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What We Do

What We Provide for Your Organization


FutureLaw.ai seeks to transform the next generation of lawyers to be more AI savvy and operate in an increasingly data driven AI economy.


It is an industry-based training platform to get legal professionals ready for Industrial Revolution 4.0.


Our Mission is to equip legal professionals with the knowledge and skills to deal with new technologies such as AI/Machine learning in law (including generative AI).


We focus on lawyering for the future data-driven AI economy!


Our Founder

Transforming the Next Generation of Lawyers
Industry-Based Training Platform to Prepare for IR 4.0
Adding New Legal Value with AI/Machine Learning in Law*
Lawyering for the Future Data-Driven AI Economy

* (including generative AI)

About Us

Our Founder

Zaid Hamzah is an AI and data strategist and practitioner specializing in AI in law and finance, AI and data governance and AI in information security. An AI patent holder, he is currently an Executive Education Fellow at the National University of Singapore (NUS) School of Computing’s Advanced Computing for Executives centre where he runs programmes on AI Innovation Management, Intellectual Property Rights in AI Innovation, and Commercialisation of AI Innovation. He has taught legal AI at the Singapore Management University School of Law. Zaid is deeply involved in AI R&D and innovation. His AI patent relating to risk management in a supply chain context was granted by the Intellectual Property Office of Singapore in December 2023. He is currently involved in AI research and innovation in the area of decision intelligence and cybersecurity.

Author of 10 books spanning law, technology, intellectual property and AI, Zaid has over 35 years of professional experience. He has previously served as (i) Microsoft's Director for intellectual property and commercial software; (ii) Senior Legal Advisor to Singtel’s joint venture with Warner Bros and Sony Pictures; (iii) Chief Regulatory Legal & Compliance Officer at publicly-listed Telekom Malaysia; (iv) Associate, Khattar Wong & Partners (Singapore law firm) and (v) Singapore Government service. Zaid has a law degree from the National University of Singapore and completed his Masters in International Relations at the Fletcher School of Law and Diplomacy, Tufts University on a Fulbright scholarship.

Zaid is a member of the Board of Directors, NIE International (which is wholly owned by Nanyang Technological University). Zaid volunteers his professional services to start ups in the area of AI management and intellectual property protection and regularly conducts community programs on how to get young children ready for a data and AI future.

What We Do

Programs

Learn More About Our Courses

Explore our course offerings covering strategic legal futures & foresight,
AI/Machine learning in law (including generative AI), design thinking in law, smart city law,
cybersecurity law & compliance, and public international law of cyberspace.

Strategic Legal Futures & Foresight

Strategic foresight is an organizational, social, and personal practice that allows us to create functional and operational views of alternative futures and possibilities.

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AI/Machine Learning in Law (including Generative AI)

Against the backdrop of Industrial Revolution 4.0, the legal industry is being disrupted by artificial intelligence.

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Design Thinking in Law

Legal design thinking (LDT) is about taking a creative, experimental, and user-centered approach to how we provide legal services.

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Smart City Law

Smart city law is about the laws and regulations in the design and development of smart cities.

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Cybersecurity Law

This course will equip students with the knowledge and skills to deal with cybersecurity attacks from the legal, investigative, risk management and policy aspects.

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Cybersecurity Compliance

We provide training in strategic cybersecurity compliance risk management and compliance performance management.

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Public International Law of Cyberspace

This course examines the international legal regulation of both the conduct of States among themselves and conduct towards individuals, in relation to the use of cyberspace.

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Program Overview

Strategic Legal Futures &
Foresight Program


Strategic Legal Futures and Foresight (SLFF) is the application of strategic foresight in the legal sector for exploring possible or probable futures in the legal industry. Strategic foresight is an organizational, social, and personal practice that allows us to create functional and operational views of alternative futures and possibilities. With the integration of generative AI in law, particularly in areas such as Natural Language Processing (NLP), the SLFF program aims to leverage advanced technologies to enhance foresight capabilities.


Futures studies (colloquially called "futures") is the formal and systematic study of possible, probable, and preferable futures, incorporating cutting-edge methodologies including generative AI. This discipline explores methods of foresight development for individuals, groups, and human society, especially within the evolving landscape of legal technology.


Futures thinking is one of the most critical skill sets for organizational leadership today. We depend a lot on hindsight to run our businesses, economies and countries. In our rapidly changing world, this can no longer be our practice. Our leaders must develop the skill of identifying emerging issues, building alternative scenarios, and creating transformational futures, utilizing technologies such as generative AI for legal analysis.


The SLFF program is a crucial first step in developing foresight skills for legal professionals, especially strategic legal thinkers. Robust legal foresight, incorporating generative AI can be utilized to enhance the quality of strategic decision-making in the lawyering ecosystem, especially in complex industrial revolution 4.0 operating environments. This course will enable lawyers to implement legal foresight programs that leverage generative AI and NLP, improving their organization’s capacity to realize opportunities and manage both strategic and operational legal risks in this era of disruptive technological, economic, and social change.


Key Takeaways

At the end of the course, participants will be able to:

  • Understand and apply strategic legal trends, incorporating qualitative and and to understand the drivers behind legal analytical techniques
  • Apply a range of legal technology horizon scanning and assessment techniques, including those involving generative AI
  • Use blended approaches to the sense-making and communication of foresight findings in the legal context, incorporating NLP advancements
  • Analyze the strategic implications of legal foresight findings for the organization or project
  • Use the findings of legal foresight, including those derived from generative AI, to guide priority-setting, legal risk management, action planning in the lawyering process, and legal strategy design and development
  • Influence the future by communicating vision and managing change, incorporating generative AI applications, in both legal practice as well as in in-house legal departments
  • Implement a practical, long-term, and flexible strategic legal foresight program in the organization


Who Should Attend

This programme has been designed for both lawyers as well as non lawyers who sit in Board of Directors, C-Suite Executives, Executive Leadership teams, Strategic/Transformation teams. Senior Management, and their teams who work on the development of strategic futures and foresight perspectives for their organisations will find this programme highly relevant.


The course is particularly relevant for those engaged in:

  • Technology management
  • Strategic management, with a focus on leveraging legal technology advancements
  • Innovation, exploring possibilities driven by generative AI in law
  • Business development
  • Operations development


This executive program is relevant to both public and private sectors. Corporate runs can be customised to incorporate the topics and issues of specific interest to participants in industry.


Topics covered:

  • Political, Economic, Social, Technology, Legal & Environmental (PESTLE) trends and driver analysis
  • Strategic and tactical legal trends and drivers analysis
  • Horizon scanning and technology assessment in the legal context
  • Legal sense-making techniques aiding understanding and communication
  • Legal implications analysis, prioritisation of legal liability risk exposures and legal risk management
  • Legal action planning and legal strategy development
  • Leadership and management of change in the legal industry (industry and government)
  • Practical implementation of strategic legal foresight and futures programmes


These topics will be covered in a 2-day, 16-hour programme blending theory, case study and practical workshop exercises that can be applied directly in the workplace.


It can be customised to accommodate the specific projects, topics or issues relevant to course participants. In this case, the workshop will focus on a set foresight project or challenge highlighted by participants, incorporating the use of generative AI in legal problem-solving.


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Program Overview

AI/Machine Learning in Law Program
(including Generative AI)


Against the backdrop of Industrial Revolution 4.0, the legal industry is being disrupted by artificial intelligence (AI). Legal analytics and AI-driven applications in law are transforming the nature of legal service delivery globally. New forms of machine learning-driven legal services have emerged in emerging areas such as AI-enabled judicial analytics, compliance, and law enforcement analytics. How will all these affect legal professionals in the future?


In this program, course participants course participants will learn recent developments in the legal technology landscape and analyze the impact of machine learning in law, including generative AI in both legal practice as well as in corporate legal departments. The program will cover the use of Natural Langage Processing (NLP) / Large Language Model (LLM) in (i) the rise of contract analytics in the review of transactional documents (ii) regulatory analytics in the context of compliance (iii) judicial analytics or court analytics; and (iv) analytics tools for in-house legal teams that could optimize external counsel resource allocation, cost management, and internal productivity.


The program will peek into the future where law-related robo-advisory services based on machine learning (including generative AI) are likely to creep into the legal advisory universe through the deployment of algorithmic thinking, unsupervised machine learning, advanced analytics, and predictive coding. Course participants will learn how to manage emerging liability issues in the development of these cutting-edge technologies. How will these developments affect the role of in-house counsels and the role of lawyering in the future economy? This course will lay the foundation for lawyering in the technology-driven future economy.


Note: There are no pre-requisites to attend this course and no technical background is required.


Aims

This elective aims to provide course participants with knowledge of:

  1. the growing trends in legal technology internationally especially in the US and the UK;
  2. the adoption of machine learning in law including generative AI in specific practice areas such as banking and finance, litigation, and intellectual property practice; and
  3. the development of alternative forms of technology-enabled lawyering.


Learning Outcomes

On completion of this elective, course participants will:

  1. be familiar with the literature and debates relating to legal analytics, machine learning and generative AI in the law;
  2. be able to assess the reasons informing and the implications of the growing adoption of legal technology solutions in the legal ecosystem;
  3. be able to appreciate the technical foundation of legal analytics, machine learning and generative AI and understand the complexity of developing technology-enabled legal solutions and the policy relevance of such inquiries;
  4. be capable of assessing the strengths and weaknesses of different approaches to the deployment of legal technology solutions in the lawyering process;
  5. have developed the ability to research, analyse and communicate in an informed and critical way practical as well as empirical studies within the field of legal technological innovation;
  6. be able to relate the issues in the legal technology to the practice of law; and
  7. be able to fluently articulate their own views with regard to the issues debated within the legal technology universe.


Skills Outcomes

The course participants will:

  1. develop an understanding of how to manage legal analytics projects for both law firms as well as for governments;
  2. be cognizant of the critical issues relating to different paradigms of lawyering with the aid of robo-advisory services;
  3. have developed a detailed and applied knowledge of comparative contextual analysis for the application of legal technology in the US, UK when compared to emerging Asian economies;
  4. be able to write cogently about international legal technology trends; and
  5. be able to articulate the salient features of legal technology in the legal ecosystem.


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Program Overview

Design Thinking in Law Program


Legal design thinking (LDT) is about taking a creative, experimental, and user-centered approach to how we provide legal services. It is about taking the same design process taught in design school and applying it in the legal context. LDT takes a human-centered approach and applying it to the world of law to benefit individual clients and eventually benefitting society.


The aim of LDT is to get students and practitioners to develop real solutions to real problems and to learn to view a legal challenge in a new way. The basic principle of LDT is to try to make the law more accessible to individuals who are not trained in law. Effective LDT should help solve specific legal problems. Beyond focusing on the substantive aspects of the law, LDT is primarily about presenting legal issues in an understandable way to clients.


LDT offers a technique that can be used in practice and have many applications in all areas of lawyering that ultimately seeks to advance the interests of the clients. In LDT, unlike traditional law classes, you must focus on the user problems first, as opposed to starting from a macro-view of what the law is. It has to be hands on and you will need to focus on the client’s perspectives first.


Course Outline

  • What is design thinking?
  • How does design thinking apply to the law and the lawyering process?
  • The nature of Legal Design Thinking (“LDT”)
    • Fundamental principles in LDT
      • User-centred
      • Experimental
      • Intentional
    • Steps in LDT
      1. Have a LDT mindset
      2. Discover, empathize and understand the needs of the clients and their problems
      3. Synthesize and define - develop “use case” statement
      4. Develop prototype, test and implement
    • Role of LDT in legal strategy formulation


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Program Overview

Smart City Law Program


Smart city law is about the laws and regulations in the design and development of smart cities.


A smart city is a term given to a city that incorporates information and communication technologies (ICT) especially sensor technology and big data analytics to enhance the quality and performance of urban services. Such urban services include energy, transportation and utilities in order to reduce resource consumption, wastage and overall costs.


The overarching aim of a smart city is to enhance the quality of living for its citizens through smart technology and the sustainable use of resources. Smart city laws are the laws and regulations that govern the design, development and maintenance of smart cities.


This course comprises the following modules:
 

  1. What is a smart city?
    1. Nature and features of smart cities
    2. Global trends in smart city development
    3. Challenges and opportunities in smart city design
       
  2. Overview of laws and regulations in designing smart cities
    1. Law, Governance & Technology in smart city design
    2. Key legal areas in smart city design
      1. ICT law
      2. Infrastructure, construction and engineering laws (or Built environment law)
      3. Environmental law
      4. Intellectual Property Rights
      5. Data rights law
      6. Privacy law
         
    3. How to design a regulatory framework for smart cities
      1. Approach in developed economies
      2. Emerging market legal and regulatory strategies
      3. Automated compliance as a service
         
  3. ICT Laws
    1. Laws relating to technology deployment
      1. Hardware, software and services
      2. Sensor technologies and its legal aspects
      3. Cybersecurity and its legal aspects
         
    2. Big Data and Analytics in smart cities: The Legal Aspects
      1. What is Big Data and Analytics?
      2. What is Legal Analytics and “Big Law”
         
  4. Intellectual Property Rights law in smart cities
    1. Copyrights
    2. Patents
    3. Trademarks
    4. IP in data rights
       
  5. Smart City Case Studies
    1. Singapore, Netherlands, United Kingdom, United States
    2. Emerging economies: India, China and Indonesia


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Program Overview

Cybersecurity Law Program


The phenomenal growth of the networked environment, the increase in the number of malicious cyberattacks and the heightened risk of cyberterrorism against critical information infrastructures (such as national power grid, transportation, health, banking and finance infrastructure) have made cybersecurity a critical national agenda. Cyberattacks harm national security and business interests and are considered as criminal acts in most jurisdictions. In dealing with cybersecurity attacks, understanding how the law and legal processes operate is a critical and unavoidable aspect. Beyond cybercrimes, broader cybersecurity concerns such as cyberattacks from nation states and non-state actors have emerged.


With cyberterrorism and state sponsored cyberintelligence activities on the rise, cyberdefence has become a new strategic imperative. With traditional geopolitical risks increasingly layered with cybersecurity risks, international relationship management now requires new forms of cooperation between states in the new cyberworld. At the enterprise level, the establishment of a robust legal risk management framework and prosecution regime to fight cybercrime and cyberterrorism continues to be an essential building block. Enterprises, governments and other organizations needs to create a proactive and structured legal and regulatory risk management framework to better manage cybersecurity risks and ensure cybersecurity resilience.


This course will equip students with the knowledge and skills to deal with cybersecurity attacks from the legal, investigative, risk management and policy aspects. It will introduce the concepts and principles of computer crime laws and regulations, cyberterrorism and policy principles and practices to counter cyberthreats.


Course Objectives

By the completion of this subject, the student should be able to understand:

  1. The nature of cybercrime, cyberterrorism and state-sponsored cyberattacks set against the international relation context;
  2. The basic principles of cybersecurity laws and how to identify legal risk issues in the design, development and management of information security systems;
  3. The process of investigation when a computer crime and cyberterrorist acts are suspected to have been committed including dealing with cross border legal and investigation issues and understanding criminal prosecution procedures.
  4. Key legal and regulatory risk management principles and strategies that organizations should adopt as part of their overall information security management policy including legal and regulatory compliance.
  5. How to create appropriate policy and legislative framework to manage the rise of cybercrime and cyberterrorism both locally as well internationally.


Course Structure



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Program Overview

Public International
Law of Cyberspace Program


Recommended text book:
Public International Law of Cyberspace
by Kriangsak Kittichaisaree
https://www.springer.com/gp/book/9783319546568


This course examines the international legal regulation of both the conduct of States among themselves and conduct towards individuals, in relation to the use of cyberspace. The course introduces the perspectives of various stakeholders and the challenges for international law. The course discusses state responsibility and key cyberspace rights issues, and addresses cyber warfare, espionage, crime and terrorism. The course also covers the situation of non-State actors and quasi-State actors (such as IS, or ISIS, or ISIL) and concludes with a consideration of future prospects for the international law of cyberspace. Course participants may explore international rules in the areas of jurisdiction of States in cyberspace, responsibility of States for cyber activities, human rights in the cyber world, permissible responses to cyber attacks, and more.


Other topics addressed include the rules of engagement in cyber warfare, suppression of cyber crimes, permissible limits of cyber espionage, and suppression of cyber-related terrorism. The course feature explanations of case law from various jurisdictions, against the background of real-life cyber-related incidents across the globe. With the textbook written by an internationally recognized practitioner in the field, the course objectively guides course participants through on-going debates on cyber-related issues against the background of international law.


This course will appeal to a wide audience, from international lawyers to students of international law, military strategists, law enforcement officers, policy makers and the lay person.


Course Outline

  1. Introduction: Perspectives of Various Stakeholders and Challenges for International Law
  2. Jurisdiction and Attribution of State Responsibility in Cyberspace
  3. Regulation of Cyberspace and Human Rights
  4. Cyber Warfare
  5. Application of the Law of Armed Conflict, Including International Humanitarian Law, In Cyberspace
  6. Cyber Espionage
  7. Cyber Crimes
  8. Cyber Terrorism
  9. Future Prospects of Public International Law of Cyberspace


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Learning Strategy

Our PEbAAL Pedagogy


At FutureLaw.ai, our learning strategy emphasises experiential, performance-based, adaptive and agile learning which we term PEbAAL (Performance-based, Experiential, Adaptive, Agile Learning).


The PEbAAL pedagogy will be applied across all our learning platforms that integrates content, pedagogical strategies and real world lifelong learning. For example, when a student learns either through face to face learning, e-learning or hybrid learning, the learning experience will go beyond the classroom and into the workplace.


We require our students to be exposed to real world setting from the time they start school and continuing their lifelong learning journey. Likewise, when a practising lawyer, in-house counsel or business executive learns through our platform, the emphasis is on real world experience that would boost corporate or organizational performance.


The PEbAAL pedagogy works this way:

1. Identify the Problem

Using design thinking methodology, we start by identifying the problem to be solved or the value to be created.

We carry out a user needs analysis to figure out what needs to be done in order to solve a problem or create value.

2. Develop a Learning Roadmap

If a problem can be solved through learning and development, we then develop a learning roadmap geared towards solving the problem.

If the problem cannot be solved through learning problems (for example, personality clashes), we do not proceed with the PEbAAL approach but attempt to solve the problem through face to face human interactions.

3. Elements of the Learning Roadmap

The learning roadmap will comprise the following elements:

a. Problem identification

b. User needs analysis

c. Learning strategy design which will focus on adaptive and agile learning

d. Tailored learning contents directed at problem solving

e. Integrated learning and development platform backed by a learning and training management system

f. Evaluation framework using the updated Kirkpatrick evaluation methodology

g. Review and refinement to ensure that the organizational KPIs (key performance indicator) are met

4. Create a Student e-Portfolio

Academic institutions are encouraged to create a student e-Portfolio that would capture the students’ learning experiences which they can share with their future employers or partners.

Organizations that require support to create these cloud based e-Portfolio can contact us.

5. Create a Skills Portfolio

Organizations and enterprises are also encouraged to create their own Skills Portfolio for their employees and this can be connected with our knowledge and skills bank that is constantly updated as part of our adaptive and agile learning.

Services

Our Products & Services

We develop comprehensive AI-enabled product and service to enable enterprises,
organizations and governments to achieve improved efficiencies, cost optimization,
enhanced brand perception and promote greater customer centricity.

Platform

We develop for our partners and clients:

AI-Enabled Dashboard as a centralized platform with interactive dashboards for real-time insights and decision-making.

API Gateway for easy integration with existing enterprise systems and third-party applications.

Security and Compliance measures and compliance with data protection regulations.

Technology Services

We work with our partners and clients to design and develop:

Large Language Models (LLMs): We utilize state-of-the-art LLMs like GPT-4 for natural language understanding and generation.

Machine Learning Algorithms: Implement ML algorithms for data analysis, predictive analytics, and anomaly detection.

Computer Vision: Employ computer vision algorithms for image and video analysis.

Cloud Infrastructure: Utilize scalable cloud platforms like AWS, Azure, or Google Cloud for processing and storage.

IoT Integration: Incorporate IoT sensors and devices for data collection and real-time monitoring.

API Strategy

API Documentation: We provide comprehensive API documentation to assist developers in integrating with your AI-powered solutions.

Developer Support: We offer developer support and forums to address technical queries and issues.

Scalability: We help ensure APIs are designed for scalability to accommodate increasing demand.

Process

Data Collection and Integration: We develop processes to gather data from various sources within the enterprise, including operational data, customer data, and market data.

Data Preprocessing: We support our partners and clients to clean, normalize, and transform data to make it suitable for analysis.

Predictive Modeling: We help build machine learning models for demand forecasting, quality control, and resource allocation.

Customer Feedback Loop: We establish a process for continuous feedback analysis from customer interactions to enhance product/service offerings.

Optimization Framework: We help implement algorithms for resource optimization, supply chain management, and pricing strategies.

Agile Development: We support our partners and clients to adopt agile methodologies for software development to respond quickly to changing market demands.

Data

We work with our partners and clients to manage the following:

Data Lake and Data Warehouse: Store and manage data in a centralized data lake or data warehouse for easy access and analysis.

Data Quality Assurance: Implement data quality checks and data governance practices to ensure data accuracy.

Data Analytics: Utilize data analytics tools for in-depth analysis of historical and real-time data.

Data Monetization: Explore opportunities to monetize data by offering insights to partners or customers.

Our Approach

Customer Centricity is Key

We work with our partners and clients on strategies and programs on:


Personalization

How to use AI to personalize customer experiences and recommendations.

Chatbots/Virtual Assistants

How to implement AI-driven chatbots and virtual assistants to enhance customer support.

Sentiment Analysis

How to analyze customer sentiment through NLP to improve products and services.

Feedback Loop

How to create a feedback loop with customers to iterate and enhance offerings.

Talent Development

Building Your Most Important Resource

We work with our partners and clients to develop talents on:

AI Training and Skill Development

Invest in training employees to understand and leverage AI technologies.

Cross-Functional Teams

Form cross-functional teams including data scientists, engineers, business analysts, and domain experts.

Change Management

Implement change management strategies to ensure smooth adoption of AI-driven processes.

Continuous Learning

Encourage a culture of continuous learning and adaptation to stay updated with evolving AI technologies.

Contact

Email Us

To contact us regarding our offerings, email Zaid Hamzah (Mr),
our Founder, at [email protected].


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