Generative AI for Scholarship: Week 1— The Basics

Friday, February 20, 2026 · 4:00–5:30 pm · Northwest Building, Room B103

This session introduces the core concepts behind large language models, effective prompt engineering, and responsible use of AI in research.

Use Your Harvard-Affiliated Google Account

Important: For this course, you must access Google Gemini using your Harvard-affiliated Google account (e.g., yourname@g.harvard.edu). This ensures your data is protected by Harvard's enterprise security agreements. See Why Use Harvard/HUIT Accounts below for details.

Prerequisites

Before the session, please verify that you can access Google Gemini:

Go to google.com and sign in with your Harvard-affiliated Google account (e.g., yourname@g.harvard.edu)
Look for the 3×3 grid of dots (⋮⋮⋮) in the upper right corner of the page, next to your profile picture
Click on this grid to open the Google apps menu
Verify that you see a menu similar to the one shown below, with various Google apps including Gemini (the colorful star icon):

Important: If you don't see the 3×3 grid of dots, or if Gemini is not in your apps menu, please contact the instructors before the session. You may need to enable certain Google services or use a different Google account.

Don't have a Harvard Google account? If you need to set up a g.harvard.edu account, visit Harvard Google Workspace for instructions.

Accessing Google Gemini

For this session, we'll use Google's Gemini AI, which is accessible directly from your web browser using your Harvard-affiliated Google account.

How to Access Gemini

Open your web browser and go to google.com
Make sure you're signed in to your Harvard-affiliated Google account (e.g., yourname@g.harvard.edu)
Click the Google apps menu (the grid of dots) in the upper right corner of the page (see Figure 1 above)
Look for the Gemini icon (a colorful star) in the app menu
Click on Gemini to open the AI assistant

Alternatively, you can go directly to gemini.google.com

Note: Gemini may ask you to agree to terms of service when you first use it. Review the terms, particularly regarding data usage and privacy, before proceeding.

Session Topics

In this session, we'll cover:

Introduction and Overview What generative AI is and how it fits into research workflows
Google Gemini Tour and Demos Model selection, tools menu, file uploads, audio input, and hands-on prompting with a meal planning exercise
Pinned Demo Showcase Image generation, conference planning, talk posters and figures, physics simulations, and more
NotebookLM for Document Analysis Upload research papers, get source-grounded answers with citations, and review a grant proposal against NSF guidelines
Ethics of AI in Research Disclosure, evolving norms, and having explicit conversations with advisors about AI use
Data Browsing with Gemini Upload a spreadsheet and explore what AI can tell you about your data
Custom AI Assistants with Gems Create reusable, task-specific AI assistants with persistent prompts

Google AI Tools Comparison

This course will focus on three Google AI tools, each with different strengths:

Tool	Best For	Key Features	When to Use
Gemini	General-purpose AI assistant	Conversational interface Code generation Multi-turn dialogue Image understanding	Writing, brainstorming, coding, general questions
NotebookLM	Document analysis & research	Upload your own documents Source-grounded responses Automatic citations Summarization & synthesis	Analyzing papers, synthesizing research, literature review
Gems	Custom AI assistants	Pre-configured prompts Persistent uploaded context Reusable workflows Shareable within research group	Repetitive tasks, specific workflows, domain expertise

Why Use Harvard/HUIT Accounts for Generative AI?

There are three important reasons to use Harvard's secured AI endpoints rather than personal accounts:

Cybersecurity: Data sent through Harvard's secure tunnel is not stored by the vendor and is not used for AI model training. Your inputs are protected by Harvard's enterprise agreements.
Privacy: You can upload early research results, draft papers, and data up to and including Level 3 confidential data. This would not be safe to do with a personal AI account.
Accounting: API usage fees can be directly linked to research grants through HUIT billing, providing clear cost tracking and proper attribution of expenses.

What Data Can You Send to AI Tools?

Using Harvard's secure endpoints (Gemini via your Harvard Google account or Claude via HUIT Bedrock), you can send data classified up to Level 3 (Confidential) — but not Level 4 or 5.

Harvard data classification levels table

Harvard data classification levels and what can be sent through HUIT-secured AI endpoints. Source: Harvard Privacy & Information Security.

Key rule: Use the "high watermark" principle — if any element in a file is Level 4 (e.g., a column containing SSNs in an otherwise Level 3 spreadsheet), the entire file is Level 4 and should not be uploaded.

Hands-On Exercises

Go to Session 1 Exercises

Additional Resources

Gemini Documentation Official documentation from Google
NotebookLM Help Center Google's official guide to using NotebookLM — uploading sources, asking questions, generating summaries and audio overviews
Gems Documentation How to create, customize, and share Gems (custom AI assistants) in Gemini
Anthropic Research Research papers on AI safety and capabilities
Harvard FAS AI Training Sessions Additional Harvard AI training resources (requires Harvard login)

Post-Session Survey

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