AI Resources, Training & Updates,

For clarity and consistent usage across Hood’s AI policies, guidance, and training materials, the following terms are defined as follows:

Artificial Intelligence (AI)

Artificial Intelligence refers to computer systems designed to perform tasks that typically require human intelligence, such as reasoning, problem-solving, learning, and decision-making.

Machine Learning (ML)

A subset of AI that enables systems to automatically learn and improve from data without being explicitly programmed. ML models identify patterns and make predictions or decisions based on data.

Generative AI

A class of AI systems capable of creating new content, including text, images, audio, video, or code, based on learned patterns from large datasets. Examples include Microsoft Copilot, ChatGPT and Google Gemini. 

Automation

The use of technology to perform tasks with minimal human intervention. Automation may or may not involve AI (e.g., rule-based workflows vs. intelligent decision systems).

Human-in-the-Loop

A governance approach in which human oversight, review, or intervention is required at critical stages of AI system design, deployment, or use to ensure accountability, accuracy, and ethical compliance.

AI-assisted tool

Any software or platform that incorporates AI capabilities to augment a task. Examples include Microsoft 365 Copilot, Zoom AI Companion, and Microsoft Editor — all of which are licensed for Hood community use.

FERPA

The Family Educational Rights and Privacy Act, the federal law protecting the privacy of student education records. Data input into AI tools may implicate FERPA if it includes personally identifiable student information.

Hallucination

When an AI system generates information that is plausible sounding but factually incorrect or entirely fabricated. A significant risk in research and academic contexts.

High-stakes context

Any use of AI that informs a consequential decision affecting a student or employee — for example, admissions, academic standing, grading, financial aid, disciplinary action, or hiring. High-stakes contexts require meaningful human review under Principle VI.

The Skill Accelerators program offers a unique series of non-degree professional development badges.

Digital badges are short, focused, competency-based credentials that provide in-demand skills, knowledge and experience. The Skill Accelerators program is designed for working professionals seeking to upskill and advance their careers without committing to the demands of a full graduate degree. Most badges are offered online for convenience and flexibility.

We offer badges in several focus areas, including business, computing, counseling and trauma, equity and inclusion, biotechnology and education. Topics range from finance, human resources, AI and data analytics, diversity in education and much more. Badges are offered at foundational, intermediate and advanced levels, and any badge can be applied toward a future master’s degree.

Applied Generative AI

Badge Description

Offered through The George B. Delaplaine Jr. School of Business at Hood College, this badge focuses on using generative artificial intelligence (AI) to innovate and add value in various business areas. It teaches using generative AI for solving problems and enhancing organizational processes. Key generative AI concepts and techniques like GANs, VAEs and transformer models are covered. The course applies the WINS framework (Words, Images, Numbers, Sounds) in sectors such as healthcare and finance. Participants will engage in lectures, case studies and exercises, concluding with a project to create a custom language model. The aim is to equip business professionals with skills in strategic generative AI application, management and ethical considerations.

 AI and Education: Innovation, Impact, and Integrity

Badge Description

The AI and Education: Innovation, Impact and Integrity badge offers educators and educational leaders a critical examination of artificial intelligence (AI) in K-12 and higher education. The course explores AI’s innovative potential to personalize learning and streamline administrative tasks, while also addressing its broader impact. Topics like bias, data privacy, misinformation and intellectual property concerns will be covered in this course. Learners will engage in emerging and existing technologies that support instruction, literacy, leadership and school operations. Through hands-on projects, discussions and readings, participants will develop the skills to make informed ethical decisions about technology integration. Legal aspects of digital tools, including copyright and digital citizenship, are also covered. Emphasizing integrity in educational practice, the course prepares learners to critically assess and lead the responsible use of AI in diverse learning environments. At the end of the semester, learners will be equipped to ensure unbiased and thoughtful applications of AI that support the core values of teaching and learning.

Please visit the College catalogue for the most up to date listing. Sample courses include:

CS 528 Artificial Intelligence

Fall Forum Workshops

August 10, 2026

Purpose: You will use Copilot Chat to examine assignment design, draft AI-use language, and create a rubric framework using fictional examples only.

Workshop #1b: Microsoft Copilot for Daily Workflow and Organization (1:00-1:45 PM)

Hands-on productivity use cases for email summaries, meeting recaps, drafting replies, rewriting for tone, organizing action items, and reducing administrative workload.

Purpose: Practice safe, browser-based Copilot Chat workflows that do not require Premium Copilot and do not require sensitive or student information.

Purpose: Design a privacy-safe tutoring chatbot behavior using generic course content. You will not use grades, attendance, student identity, advising history, eligibility, disability, health, or other student records.

Applied examples using synthetic attendance data, student scenarios, planning prompts, feedback generation, and AI-supported student success workflows.

Educause Navigating AI Shockwaves in Higher Education

A Collaboration with Gartner | 2026 EDUCAUSE Mission Partner

Join Gartner’s “Navigating AI Shockwaves in Higher Education,” a four-part webinar series designed to equip institutions with practical strategies and insights for embracing GenAI. Explore real-world use cases, foster AI literacy among staff, prepare your data for AI readiness, and learn cybersecurity best practices in the age of artificial intelligence. Each session features leading Gartner analysts sharing actionable guidance tailored to the unique challenges and opportunities facing higher education.

These EDUCAUSE webinars are a four-part series.

Part 1: August 6, 2026 | 12:00 noon–1:00 p.m. ET
GenAI Use Cases and Lessons Learned in Higher Education
Register for Part 1→

Part 2: August 10, 2026 | 12:00 noon–1:00 p.m. ET
Guiding Teams to AI Confidence and Adaptability
Register for Part 2→

Part 3: August 17, 2026 | 2:00–3:00 p.m. ET
AI Ready Data is Not What You Might Think It Is
Register for Part 3→

Part 4: August 19, 2026 | 3:00–4:00 p.m. ET
Best Practices in Cybersecurity in the Age of AI
Register for Part 4→ 

Counted Out: Free Virtual Screening + Live Conversation

On August 8, join us for our first-ever, free virtual screening of COUNTED OUT, followed by a live conversation about the knowledge and confidence we need to navigate our world in an age of AI. 

COUNTED OUT takes us on a journey to answer an urgent set of questions: how do we reclaim our mathematical confidence? How do we take back the agency to make better decisions, to protect ourselves from misinformation, to guide our children, and to improve our quality of life in concrete, meaningful ways?  

Other Internal Events

Please visit the CTL webpage for upcoming AI related trainings. 

Internal Training

External Training

• June 5th 2-3 pm ET: One hypothetical AI rollout. Five world-class perspectives.

Practical AI for Instructors and Students (10 to 12 minutes each)
Wharton School, University of Pennsylvania

• Part 1: Introduction to AI for Teachers and Students
• Part 2: Large Language Models (LLMs)
• Part 3: Prompting AI
• Part 4: AI for Teachers
• Part 5: AI for Students

• Exploring the Risks and Benefits of AI
• AI in Cancer Research & Clinical Care

Artificial intelligence is no longer on the horizon for higher education — it is embedded in how faculty prepare courses, how students write and study, how staff handle routine communications, and how  institutions make operational decisions. Generative AI tools have become broadly accessible in a period of  roughly three years, outpacing the usual rhythms of policy development, governance review, and curriculum redesign. Peer institutions, accreditors, and professional associations are all actively developing AI frameworks, and Hood faces both an opportunity and an obligation to act thoughtfully.

The Taskforce was established to meet this moment. Its charge was not to produce a one-time policy document but to build the institutional capacity — principles, structures, processes, and resources — that will allow Hood to navigate AI integration responsibly over time. It issued a report in Spring 2026. For more information, email co-chairs lascolette@hood.edu and boulton@hood.edu.