Legal Industry Path

The legal services sector worldwide is facing a digital transformation. The arrival of new data-driven technologies encouraged by automation and developments in artificial intelligence (AI) is promising significant disruption to long-established practices  and will open the doors to ancillary revenue streams.

‍Learning Path

The Learning Path has five (5) modules which enables you and your organization to create an AI holistic strategy to drive long-lasting business impact.

‍Module 1: AI Strategy‍

The pathway to using AI is not fast and requires digital transformation and a continuous approach and culture change all before any benefit is realized. Your AI initiatives start with an understanding of holistic AI strategy.

You will learn:

• Define a holistic AI strategy using a framework for driving digital transformation that drives business value.
• Describe Industry 4.0 key components and functionality with AI.
• Identify opportunities using AI SWOT (strengths, weaknesses, opportunities and threats) model analysis.
• Discover how AI can support your organization to improve efficiencies, cut costs, provide customer insights, and generate new product ideas.

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Module 2: AI Technology

Law firms must build their capacity and capabilities to understand and appropriately adopt AI technology. This understanding starts with AI literacy including, data and the readiness of algorithms for legal practice, AI design life cycle, risk assessment, auditing. clinical processes.  This module is devoted to how appropriately use data science and AI products and services, IEEE P7003 Algorithm Bias Consideration standards,  and introduction to AI, machine learning (ML) data mining. topics include: supervised & unsupervised learning, reinforcement learning AI/ML workflow covering model building, auditing framework, stakeholder analysis framework, risk management assessment, and auditing.

You will learn:

• Explain the fundamentals of AI, Machine Learning, and Deep Learning.
• Evaluate methods for AI design stages framework for a litigation case.
• Comprehend  data collection and preparation for building an AI model.
• Describe the concepts of data bias and algorithm bias detection and mitigation.
• Comprehend how to leverage the technologies for your organizations.
• Comprehend a framework for defining the level of explainability based on technical, legal and economic considerations.
• Explain what acceptance tests driven development (ATDD), and algorithmic model’s life cycle.
• Review AI auditing framework and its core components.
• Evaluate Risk management by design across the algorithmic model’s life cycle.
• Comprehend AI auditing framework.
• Explain the stages of data life cycle.

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Module 3: AI Culture

When implementing cutting edge technology, such as AI and machine learning, organizational culture can be a leading factor to the success and failure of AI implementations.  A successful AI strategy must consider cultural issues as well as business issues. Becoming an AI-ready organization requires a fundamental transformation in how you do things, how employees relate to each other, what skills they have, and what processes and principles guide your behaviors.

You will learn:

• Comprehend the importance of building an AI-ready culture.
• Explain how ADKAR framework can help you lead organizational change.
• Comprehend how to apply the AI maturity model Assessment to your business.
• Evaluate the characteristics that foster an AI-Ready culture.

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Module 4: AI Governance

Governments are the primary enablers of technology and market stimulators and regulators of general activities in our society. The consequences of  (AI) in government are wide and important. The characteristics of these technologies will have an influence on almost everything in public organizations, from social implications linked to concepts like public trust, transparency, or accountability. This module focuses on a conceptual framework for thinking about governance and responsible AI.

You will learn:

• Evaluate the emerging regulatory and policy landscape surrounding artificial intelligence (AI) in jurisdictions around the world.
• Explain AI government challenges that translate into design requirements for a future governance model of AI.
• Comprehend a representation layered model for AI governance.
• Review explainable AI (XAI) stages to  applied to AI governance.
• Consider professional conduct rules that may trigger when use AI to serve clients.
• Comprehend responsible AI global police framework.
• Evaluate an AI auditing framework  and its core components.

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Module 5: AI Applications

Ongoing advancements in AI guarantee to disrupt the very foundations of how legal service is conducted and delivered.  AI and law join hands to make creative applications to automate repetitive lawful procedures. With the help of natural language processing, the present infusion of AI in law can aid experts in streamlining the legal processes, analyze agreements rapidly, discover any flaws or imperfection in an agreement. This module is devoted to legal technology, and natural language processing (NLP) implementation to support on legal services.  The United Nations recognized Code Explorers for designing, developing, and deployment NPL applications.

You will learn:

• How top law firms such as automating their services to improve business efficiency.
• Comprehend how to apply voice assistance on your practice.
• Evaluate how to apply LegalTech applications by performing customer market segmentation to optimize marketing strategy.
• Evaluate the different categories in which AI applications are used in the legal profession and learn the benefits.

Expert Instruction

Instructor-led program delivered by Abel Pena-Fernandez an AI advisor, IEEE Senior Member.

Length of Program

Twenty (20) hours total per Industry path - 2 - 3 hours per week

Cost

$2448.00 per Industry Path per person - Five (5) Learning Path Modules

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‍Contact Us for details and schedule.

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