Introduction

This document was created and is maintained by WHCCD's AI Workgroup and aims to provide some general guidelines and considerations around the use of artificial intelligence at West Hills Community College District.  This document is intended to highlight key considerations and prompt conversations around the deployment and use of AI.  While AI can enhance the quality and effectiveness of teaching and learning, student support, and institutional operations in community colleges, AI also poses ethical, social, and technical challenges that must be addressed carefully and cautiously.

Some definitions of key terms related to AI are provided below to establish a common understanding of terms.  Additional terms can be found here: https://westhills.cc/4b3qisw

• Artificial Intelligence (AI) - The simulation of human intelligence processes by machines, especially computer systems. These processes include learning, reasoning, and self-correction.
• Generative AI - AI systems that can create new content, such as text, images, and music, based on the data they have been trained on. Examples include GPT-4 for text generation and DALL-E for image creation.
• Machine Learning (ML) - A subset of AI that uses algorithms and statistical models to enable computers to perform tasks without explicit instructions by relying on patterns and inference.

AI Use Considerations and Guidelines

• Ethical and Responsible AI Use:
  • Align AI initiatives with the mission, vision, and values of WHCCD.
  • Ensure that AI is used to support and augment human capabilities.
  • Promote equity, diversity, and inclusion in designing, developing, and deploying AI systems.
  • Respect the privacy, security, and consent of students, faculty, staff, and stakeholders.
  • Avoid submitting protected and confidential data to third-party AI tools and systems.
  • Ensure the transparency, explainability, and accountability of AI systems and their outcomes.
  • Adhere to the ethical principles and guidelines of professional associations and organizations related to AI and education.
  • Reducing the likelihood of bias
  • Safeguard Intellectual Property
• Human-Centered AI Development:
  • Adopt a human-centered and participatory approach to AI development and implementation.
  • Involve students, faculty, staff, and stakeholders in the co-design, co-creation, and co-evaluation of AI systems.
  • Provide clear and transparent information and communication about the AI systems’ purpose, function, and limitations.
  • Collective bargaining implications (function replacement, augmentation, upskilling).
• AI Education and Professional Development:
  • Provide ongoing education and training on AI for students, faculty, staff, and stakeholders.
  • Consult with relevant experts, practitioners, and communities of practice on AI best practices and standards.
• AI System Management and Infrastructure:
  • Monitor and evaluate the impact and effectiveness of AI systems and adjust them as needed.
  • Use open, interoperable, and accessible AI platforms and tools that are compatible with WHCCD’s infrastructure and resources.

Recommendations for Continued Development

• Create opportunities for innovation, collaboration, and the dissemination of AI-related knowledge and practices.
• Establish an AI governance process within the Technology Committees, which involves representatives from different groups and levels of WHCCD.
  • Develop a process to conduct a needs assessment and a feasibility study before adopting or developing any AI system.
  • Develop an understanding of how our data is used in third-party systems.
  • Adapt the software renewal process to include considerations for AI tools and products.
• Develop finer-grain recommendations and considerations by functional area (i.e., faculty, students, administrative, and support functions).
• Continue to review and monitor the legislation and regulations at the state, federal, and international levels that affect AI use and development.
  • Analyze the implications and challenges of complying with different legal frameworks and standards.
  • Identify the gaps and opportunities for community colleges to influence and shape the AI policy agenda.

Additional Resources

AI, especially generative AI, is an emerging field of research; below are some resources that may be of interest in helping to deploy AI tools in a responsible manner.

• AI Readiness Framework
• Ethical AI for Teaching and Learning (Cornell University)
• How Higher Ed Can Adapt to the Challenges of AI (chronicle.com)

Legislative and Regulatory Landscape

As of June 2024, here is a list of significant AI-related legislation currently being tracked.

• California
  • SB 313 - Create an Office of AI to oversee AI use by state agencies (not necessarily applicable to CCCs).
  • Current Status 2/1/2024: Failed, returned to Secretary of Senate
  • AB 331 - Automated Decision Tools
  • Current Status 2/1/2024: Failed.
  • SB 721 - California Interagency AI Working Group (input from citizens)
  • Current Status 2/1/2024: In Progress
• Federal
  • Federal AI Bill of Rights - https://whitehouse.gov/ostp/ai-bill-of-rights/
• Other States
  • SV 1103 in Connecticut– Passed in 2023
  • EU - AI Act  - Adopted March 2024