Get in Touch

Course Outline

Day 1: Foundations of Artificial Intelligence and Document Analysis Capabilities

  • Module 1: Introduction to AI for Public Service Professionals
    • Clarifying core concepts of AI, machine learning (ML), and natural language processing (NLP) using accessible terminology.
    • Positioning AI as a collaborative instrument: Shifting focus from potential disruption to operational support.
    • Review of relevant case studies demonstrating successful AI deployment in regulated sectors such as legal and financial services.
  • Module 2: Essential NLP Functions for Document Processing
    • Document Classification: Utilizing AI to automatically categorize document types, including charters, financial reports, and environmental permits.
    • Entity Extraction: Leveraging AI to identify and retrieve specific data points such as executive names, capital values, effective dates, and taxpayer identification numbers.
    • Sentiment Analysis and Risk Assessment: Detecting potential liabilities or adverse indicators within contractual clauses and documentation.
  • Module 3: Practical Applications of Machine Learning
    • Mechanisms of supervised learning through the use of historical document datasets.
    • The critical role of data quality in ensuring accurate model performance.
    • Overview of the machine learning project lifecycle, ranging from data acquisition to model validation.

Day 2: Operational Applications, Technology Landscape, and Strategic Planning

  • Module 4: Workshop - Aligning Workflows with AI Solutions
    • Interactive exercise to identify high-volume manual tasks within the licensing workflow.
    • Collaborative strategy session on applying NLP and ML technologies to address identified inefficiencies.
  • Module 5: Overview of AI Technologies and Tools for Government
    • Evaluation of solution tiers, ranging from off-the-shelf software-as-a-service (SaaS) offerings to customizable platforms.
    • Demonstration of selected AI tools designed for document analysis.
  • Module 6: Developing and Executing an AI Initiative
    • Procedures for initiating a pilot program.
    • Establishing key performance indicators, such as processing time reduction and error minimization.
    • The role of human oversight: Emphasizing the necessity of expert verification in AI-driven processes.
  • Module 7: Ethical Standards and Risk Mitigation
    • Protocols for data security and confidentiality within AI infrastructure.
    • Identification of potential algorithmic bias and strategies for remediation.
    • Establishing accountability and trust in automated analysis outcomes.
  • Module 8: Conclusion and Implementation Roadmap
    • Formulating a strategic action plan for AI integration within the licensing division.
    • Final review and Q&A session.

Requirements

Intended Beneficiaries

  • Licensing Division
  • Administrative and records staff
 14 Hours

Number of participants


Price per participant

Testimonials (1)

Upcoming Courses

Related Categories