Slide deck: LLM's unleashed - Applying ChatGPT in information governance and compliance

ILTA Masterclass series

Team

LLMs Unleashed: Applying ChatGPT in

Chris Hockey, , IGP, CIPP/US

Senior Associate | Information Risk and Governance

Alvarez & Marsal Disputes and Investigations, LLC

Kandace Donovan

LegalRM’s Vice President Operations, North America

www.legal-rm.com

What are LLMs?

The Basics

✓ Definition of Large Language Models (LLMs) like ChatGPT

✓ Overview of How LLMs work

✓ Significance in interpreting and generating text

What are LLMs

✓ Advanced AI algorithms designed to understand, interpret, and generate human like text

✓ Models like ChatGPT are trained on LARGE amounts of text data

✓ Enables them to grasp a wide range of topics, language nuances and context

✓ They perform tasks ranging from answering questions and summarizing information to composing emails, articles, and coding

The Basics

Overview of How LLMs Work

Let’s

The Perfect Dog

✓ Learns basic commands

✓ Understands nuance

✓ Can be specially trained

✓ Learns from success and mistakes

✓ Responds to new commands

✓ Socializes well

✓ Continuously learns

The Perfect Dog

✓ Learns basic commands

✓ Just like a dog starts its training by learning basic commands like “sit”, “stay”, and “come,” an LLM begins its journey with basic language understanding.

✓ This involves processing large amounts of text data to learn the structure of language and the meanings of words and phrases.

Initial Training on Data

The Perfect Dog

✓ Understanding nuances

✓ As the training progresses, the dog learns to understand more nuanced commands that are not just about what to do, but how to do it

✓ Fetch gently – bring something back without damaging it

✓ An LLM learns to understand nuances in language, such as context, tone, and the subtle differences in meaning that change with word order or emphasis

Advanced Language Understanding

The Perfect Dog

✓ Customized training

✓ Each dog is unique and might require special attention to certain commands or behaviors

✓ LLMs are fine-tuned on specific datasets to perform well on particular tasks or understand industry-specific jargon

✓ Enhances performance in targeted areas

Model

Fine-tuning

The Perfect Dog

✓ Rewards and corrections

✓ Effective dog training involves rewarding correct behavior and gently correcting mistakes

✓ LLMs are also “trained” using feedback loops, where correct outputs are reinforced, and errors are used as learning opportunities to improve the model’s accuracy and relevance

Feedback Loops

The Perfect Dog

✓ Adapting to new commands

✓ A well-trained dog can learn to respond to new commands it hasn’t heard before by relying on its general training and the context

provided by the trainer

✓ LLMs can generate responses to new or unseen queries based on the large training set of training data and the ability to infer meaning from context

Adapting to New Inputs

The Perfect Dog

✓ Socialization

✓ A dog needs to be socialized to behave well in various environments and with different people

✓ LLMs need exposure to a wide range of text from different sources, genres, and perspectives to understand and generate diverse and balanced outputs

Exposure to Diverse Data

The Perfect Dog

✓ Continuous training

✓ Dog training isn’t a one-time event; it’s a continuous process that involves learning new skills and refining old ones

✓ LLMs are continuously updated with new data and improved algorithms to enhance their performance and capabilities over time

Ongoing Learning and Updates

What’s the significance?

• LLMs have revolutionized the way we interact with machines by providing more natural, conversational interfaces

• They excel in understanding context and intent, making them invaluable for applications in customer service, content creation, tutoring, and more

• Their ability to rapidly analyze and synthesize information from large volumes of text makes them powerful tools for data analysis, summarization, and decision support systems

IG Basics

✓ “Minimizing information risks and costs while maximizing information value”

–

✓

Robert Smallwood

“Policy-based control of information to meet legal, regulatory, risk and business demands. It involves keeping information as required by regulations and laws, discarding it according to retention schedules, and leveraging valuable information for insights - AIIM

LLMs in IG

Potential of LLMs in IG

The digital age demands dynamic governance strategies

✓ Enhancing Efficiency and Accuracy

✓ Facilitating Data-Driven Decision Making

✓ Enhancing Compliance and Risk

✓ Personalizing Information Governance Policies

Harnessing LLMs in IG

✓ Enhancing Decision-Making

✓ Improving Regulatory Compliance

✓ Streamlining Records Management

✓ Facilitating Data Privacy Management

✓ Customizing Information Policies

✓ Promoting Knowledge Sharing, Management and Collaboration

✓ Develop Training and Professional Development

Prompt Examples for Application of LLMs to IG

Sample Prompts

Custom Information Governance Policies

"Your mission is to leverage your advanced processing and analytical capabilities to aid our organization in refining our information governance policies. This task involves a detailed examination of our extensive datasets to understand the distinct attributes and inherent risks of different types of information we manage. The ultimate goal is to develop nuanced governance strategies that not only bolster our security posture but also improve the usability and accessibility of our data, all while ensuring compliance with relevant privacy regulations like GDPR and CPRA.

Please proceed with the following steps:

1. Conduct a comprehensive analysis of our datasets to categorize the information based on its nature, such as personal data, financial records, operational data, and sensitive intellectual property. Highlight the unique characteristics and handling requirements of each category.

2. Evaluate the potential risks associated with each type of information, considering factors like sensitivity, regulatory obligations, and exposure to cybersecurity threats. Pay special attention to data that falls under the purview of GDPR and CPRA, noting specific compliance requirements.

3. Based on your analysis, propose tailored information governance policies for each category of data. Your recommendations should address data collection, storage, access controls, encryption, and disposal practices, ensuring they are appropriately stringent for the data's sensitivity and risk profile.

4. Suggest mechanisms for monitoring compliance with these tailored governance policies, including regular audits, employee training programs, and automated tools for policy enforcement.

5. Recommend strategies to enhance the usability and accessibility of data within the confines of the proposed governance frameworks. This may involve innovative data classification schemes, user-centric access models, or advanced encryption techniques that allow secure data sharing.

6. Provide a detailed report summarizing your findings, risk assessments, and policy recommendations. Include actionable steps for implementing the suggested governance strategies and ensuring ongoing compliance with GDPR, CPRA, and other relevant regulations.

By accomplishing this task, you will significantly contribute to our organization's ability to manage information responsibly and effectively, safeguarding against data breaches and legal risks while maximizing the value and accessibility of our data assets."

Lite Version

"Given the variety of information managed by organizations, including personal data, financial records, and confidential business information, each with its own security and compliance requirements, can you provide general guidelines on developing information governance policies that address the unique needs and risks associated with these types of information? Include considerations for enhancing data security, ensuring privacy compliance, particularly with regulations like GDPR and CPRA, and improving data usability and accessibility."

Sample Prompts

Structured and Unstructured Data

"You have been provided with a dataset that includes various structured data points across multiple sources. Your task is to conduct a thorough analysis of this dataset to identify and report any anomalies, inconsistencies, or errors that might indicate data quality issues. This includes outliers in numerical data that deviate significantly from the average values, as well as any contradictory information that appears across different data sources. Your goal is to ensure the integrity and reliability of our data by highlighting these discrepancies for further investigation.

Please proceed with the following steps:

1. Start by providing a brief overview of the dataset, including the types of data sources involved and the key numerical metrics being tracked.

2. Conduct an initial scan of the numerical data to identify any outliers. Please use statistical methods such as Z-scores or IQR (Interquartile Range) to determine if there are data points that fall outside the expected range.

3. Compare information across different data sources to detect any inconsistencies or contradictions. Highlight any records that do not align with the overall data pattern or information from other sources.

4. For each anomaly, inconsistency, or error detected, provide a detailed description, including the specific data points involved and your reasoning for flagging them as issues.

5. Summarize your findings in a report, listing the detected anomalies and inconsistencies, along with any potential impact they might have on data quality and reliability.

6. Offer preliminary recommendations for addressing these data quality issues, such as further investigation of specific anomalies or a review of data collection and processing protocols.

"Your task is to meticulously analyze a collection of unstructured data, which includes various forms of text content such as articles, reports, and documents. The primary goal is to identify and highlight any potential quality issues, focusing specifically on incorrect or outdated information that may compromise the integrity and utility of the data. By examining the content and context, assess the accuracy, timeliness, and relevance of the information presented.

Please follow these steps to ensure a comprehensive analysis:

1. Begin with a general overview of the content, summarizing the main themes and types of information contained within the unstructured data.

2. Analyze the text for factual accuracy, identifying statements that may be incorrect based on current knowledge or contradictory to widely accepted facts. Highlight these areas for further investigation.

3. Examine the content for temporal relevance, looking for dates, events, or references that suggest the information might be outdated. Pay special attention to temporal phrases or markers that indicate when the information was relevant.

4. Consider the context in which the information is presented, evaluating whether the content remains relevant and accurate in the current context or if it has been superseded by more recent developments.

5. For each instance of potentially incorrect or outdated information, provide a brief explanation detailing why the information was flagged, including any external references or logical deductions used in your assessment.

6. Compile a report summarizing the potential quality issues identified, categorizing them into 'Incorrect Information' and 'Outdated Information.' Include specific examples and your rationale for each category.

7. Offer recommendations for updating the content to resolve the identified issues, suggesting ways to correct inaccuracies and refresh outdated information to improve the overall quality of the data.

Sample Prompts

"Your task is to review and analyze the attached documents, which contain policies, procedures, and operational records of our organization, to ensure they comply with relevant compliance requirements across different jurisdictions and industries in which we operate. This includes data protection laws like GDPR in Europe and CPRA in California, financial regulations, and industry-specific guidelines.

1. Summarize the key compliance areas covered in the documents, focusing on data protection, financial reporting, and any specific industry regulations mentioned.

2. Identify any sections of the documents or described practices that may not meet the current standards of the GDPR, CPRA, or other applicable regulations. Highlight these sections and explain the potential issues of non-compliance.

3. Check for any outdated information or references to repealed laws and regulations, indicating documents or sections that need updating.

4. Suggest modifications or actions needed to address the non-compliant areas or outdated information you have identified. This could include revising policy language, updating procedures, or implementing new compliance measures.

5. Provide a brief overview of best practices for maintaining compliance with these regulations, including regular review cycles, employee training, and compliance monitoring systems. This review is crucial for identifying potential compliance risks and taking proactive steps to mitigate them, thereby reducing the risk of fines and legal issues related to non-compliance."

Sample Prompts

Records Management

"Assume you're tasked with enhancing our organization's records management system using your capabilities. We have a variety of documents, including contracts, reports, employee records, and policy manuals, that need to be organized efficiently. Our goals are to improve the accessibility of critical information and ensure our document handling practices comply with relevant retention policies.

1. Provide an outline for categorizing these documents into logical groups based on their content type (e.g., financial, HR, legal, operational).

2. For each category, suggest a set of indexing keywords or phrases that could help in quickly identifying and retrieving specific documents or information.

3. Describe a simple system for tagging documents with their retention period according to our policy, which categorizes records into 'shortterm' (1-3 years), 'mid-term' (4-7 years), and 'long-term' (over 7 years) retention schedules.

4. Offer a method for efficiently retrieving documents based on the categories, indexing keywords, and retention tags you've suggested. Include how to handle requests for information that may span multiple categories or require cross-referencing.

5. Recommend a routine check-up strategy to review the classified and indexed documents for compliance with our retention policy, including how frequently this should be done and what steps to take if non-compliance is detected. This system will not only streamline our document management process but also enhance our compliance posture by ensuring information is retained and disposed of in accordance with legal requirements and best practices."

Sample Prompts

Information Sharing and Collaboration

"Your goal is to enhance collaboration within our global organization, where diverse teams often face challenges due to language barriers and technical jargon. You are also tasked with supporting our legal team by developing a knowledge base that consolidates precedents, regulations, and internal legal know-how. This effort is critical for fostering effective knowledge sharing and ensuring easy access to vital legal information.

1. Start by summarizing key documents related to ongoing projects across different departments. Focus on distilling complex information and technical jargon into clear, concise summaries that can be easily understood by team members with varying levels of expertise.

2. Translate these summaries into multiple languages commonly used within our organization to ensure that all team members, regardless of their primary language, can access and understand the shared knowledge.

3. Outline a strategy for compiling legal documents, precedents, and regulations relevant to our operations into an organized, searchable knowledge base. This includes structuring the information in a way that allows for easy access and retrieval.

4. Suggest a method for updating the legal knowledge base regularly with new information, ensuring that the legal team always has access to the latest precedents and regulatory changes.

5. Recommend tools or practices for promoting the use of this knowledge-sharing platform among team members and legal staff, encouraging active contribution and engagement. Through this initiative, you will play a pivotal role in promoting a culture of open communication and collaboration, reducing knowledge gaps, and supporting our legal team's efforts to navigate complex legal landscapes efficiently."

Sample Prompts

Training and Education

"Your mission is to develop an interactive training module for our new information governance staff and attorneys, focusing on practical learning experiences that align closely with their daily tasks. This training module should introduce them to the core principles of information governance, legal compliance, data protection practices, and how to handle real-life scenarios they might encounter.

1. Begin by outlining the key topics and principles of information governance that are essential for new staff and attorneys to understand. Include data protection laws (like GDPR and CPRA), records management, privacy policies, and risk management strategies.

2. Create a series of interactive scenarios based on common challenges and tasks in information governance. For each scenario, provide background information, objectives, and decision points where learners must choose how to proceed based on best practices.

3. Incorporate questions and quizzes throughout the module to assess understanding and retention of the material. Provide feedback on their choices, explaining the reasoning behind the correct answers and offering insights into improving their decision-making.

4. Suggest practical exercises that allow learners to apply what they've learned, such as drafting a privacy policy based on given requirements or developing a plan to respond to a hypothetical data breach.

5. Recommend resources for further learning and professional development in information governance, including authoritative texts, industry guidelines, and relevant legal statutes.

6. Conclude the module with a comprehensive assessment that covers all the topics discussed. Use this as an opportunity to reinforce key learning points and ensure the staff and attorneys are prepared to apply their knowledge in their roles. This interactive training module will not only equip our new information governance staff and attorneys with the necessary knowledge and skills but also engage them in practical learning experiences that enhance their understanding and application of information governance practices in their daily work."

Considerations for Digital Transformation

✓ Strategic Alignment ✓

Cultural Adaptation

✓ Change Management

✓

Continuous Evaluation and Adaptation

Guide to Incorporate LLMs

✓

Assessment and Planning

✓ Pilot Programs

✓ Training and Skill Development

✓ Technology Alignment

Data Privacy and Model Bias

✓ Prioritizing Data Security

✓ Ensuring Transparent Usage

✓ Mitigating Model Bias

✓ Continuous Monitoring for Bias

Challenges of Implementation

Ethical Considerations

✓ Developing Ethical Guidelines

✓ Ensuring Human Oversight

✓ Promoting Transparency in Decision-Making

✓ Engaging with Stakeholders

✓ Adapting to Ethical Evolution

Challenges of Implementation

Embracing the Future

✓ Integration with Advanced Technology

✓ Moving Towards Predictive Governance

✓ Customization and Personalization at Scale

✓ Providing Deeper Insights

✓ Fostering Collaboration

✓ Ethical and Responsible Use Frameworks

Other webinars in the ‘Team IG’ series

April 11

May 2

May 23

June 27

‘The importance of change management for successful IG’ with Leigh Issacs from DLA Piper

‘Bringing order from chaos’ with Kathleen Jimenez from White & Case

‘Metrics – what to capture’ with Kate Wertime and Brad Zimmerman from Jones Day

‘Dissecting Microsoft Teams’ with Kathleen Jimenez from White & Case

Other ILTA webinars from the iCompli team

April 4

May 20

May 28

June 26

Leveraging AI for information governance

Empowering AI success through advanced IG technology

Optimising efficiency and cost - Mastering DMS cloud migration strategies

Streamlining data management - Insights on minimising your data footprint

www.legal-rm.com