Workshop 1: Introduction to AI Tools for Novice Users

Seminar 1, Part 1: Introduction to AI Tools for Novice Users

Course Notes for Instructor

Overview (10 minutes)

  • Welcome participants and introduce the seminar series.
  • Provide a brief overview of the seminar’s objectives and the topics to be covered in Part 1.

Introduction to LLMs (10 minutes)

  • Explain what Large Language Models (LLMs) are and how they work.
  • Introduce popular LLMs like Copilot and ChatGPT.
  • Highlight the potential applications of LLMs in the nonprofit sector, specifically in fundraising.

Ethical Considerations and Responsible AI Use (15 minutes)

  • Discuss the importance of using AI responsibly and ethically.
  • Address potential biases in AI data and provide strategies for mitigation.
  • Exercise 1: Divide participants into breakout rooms. Ask them to discuss examples of potential biases in fundraising data and brainstorm mitigation strategies. (5 minutes)
  • Emphasize the need for transparency and accuracy in AI-generated content for fundraising.
  • Exercise 2: Present a case study of an AI-generated fundraising email. Ask participants to identify areas that require human review and editing for accuracy and transparency. (5 minutes)

Setting Up and Familiarizing with AI Tools (10 minutes)

  • Provide a step-by-step guide for setting up accounts and accessing LLM tools like Copilot and ChatGPT.
  • Offer resources and tutorials for participants to familiarize themselves with the tools.

Data Security Considerations (5 minutes)

  • Briefly discuss data security considerations when using AI tools with sensitive donor information.
  • Provide best practices for ensuring data privacy and security.

Instructions for Participants

  1. Participate in the discussion on potential biases in AI data and contribute to brainstorming mitigation strategies during Exercise 1.
  2. Review the AI-generated fundraising email case study in Exercise 2. Identify areas that require human review and editing to ensure accuracy and transparency. Be prepared to share your findings with the group.
  3. Follow the step-by-step guide provided by the instructor to set up accounts and access LLM tools like Copilot and ChatGPT. Utilize the provided resources and tutorials to familiarize yourself with the tools.
  4. Take note of the data security considerations and best practices shared by the instructor when using AI tools with sensitive donor information.
  5. Engage in the Q&A session at the end of Part 1 to clarify any doubts or questions you may have.

Exercises

Exercise 1: Addressing Potential Biases in AI Data

  • Objective: Identify potential biases in fundraising data and brainstorm mitigation strategies.
  • Duration: 5 minutes
  • Instructions:
  1. Divide participants into breakout rooms.
  2. Ask participants to discuss examples of potential biases in fundraising data.
  3. Encourage participants to brainstorm strategies for mitigating these biases.
  4. Reconvene and have each group share their findings.

Exercise 2: Ensuring Transparency and Accuracy in AI-Generated Content

  • Objective: Identify areas in an AI-generated fundraising email that require human review and editing.
  • Duration: 5 minutes
  • Instructions:
  1. Present a case study of an AI-generated fundraising email to the participants.
  2. Ask participants to review the email and identify areas that require human intervention for accuracy and transparency.
  3. Encourage participants to share their findings with the group.
  4. Discuss the importance of human oversight in AI-generated content.

Q&A Session (10 minutes)

  • Allocate time for participants to ask questions and clarify any doubts related to the topics covered in Part 1.
  • Encourage participation and address each question thoroughly.
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