Participation

Civility pledge

By participating in Engaged California, you agree to:

1. Listen to understand, not just to respond.
2. Step up and step back. Share the airtime with everyone in your group.
3. Ask questions and assume good intent. Make a genuine effort to understand the perspectives of others.
4. Stay focused on today’s issue. Avoid side conversations and technology devices.
5. Be open to new ideas. Avoid rushing to conclusions.
6. Challenge the idea, not the person. Direct your energy toward the issue.
7. Engage with curiosity and care. And have fun while we’re at it.
8. Be civil. Abuse will not be tolerated.

AI glossary of terms

These terms might come up in your discussion. We’ve defined them so everyone has the same understanding.

Artificial intelligence (AI): A computer system that does things we usually think of as needing people. This could be understanding speech, answering questions, or making predictions. AI is a broad term that covers many types of tools.

Augmentation: Using AI to assist a person rather than replace them. Examples include:

• Drafting documents
• Summarizing information
• Suggesting options that the person then reviews and decides on

Automation: Using technology to do a task with little or no human effort. Automation existed long before AI. Because of AI, we can automate a wider range of tasks, like those that involve language or judgment.

Bias: When an AI system makes results that unfairly favor or disadvantage groups. This often comes from patterns in the training data or how people built the system. It can appear even if no one intended to cause harm.

Generative AI: A type of AI that creates new content. This could be text, images, audio, or computer code. People ask the system to make this content. The system makes the content from patterns it learned from examples.

Human in the loop: A setup where people stay involved in an AI process. One form is reviewing or approving decisions an AI makes.

Large language model (LLM): A kind of generative AI that powers many popular AI chat tools. It is trained on huge amounts of text so it can understand and produce writing that looks like people made it. It uses that training text to predict what word to use next. This means it can sound confident even when it’s wrong.

Machine learning: A common way of building AI. The system learns patterns from a lot of examples. It uses those patterns to make decisions or predictions. People don’t have to write every rule for the system to do its work.

Policy: A set of rules designed to guide decisions and achieve good outcomes. It's the foundation for actions adopted by government to best serve the public.

Private sector: The part of the economy run by businesses.

Public sector: The part of the economy run by government. It includes:

• State and local government agencies
• Public schools
• Courts
• Services like the DMV or unemployment offices.

Reskilling or upskilling: Helping workers learn new skills. Reskilling prepares someone for a different kind of job. Upskilling builds on skills they already have. Both are often talked about as responses to what AI is doing to people’s work.

Training data: The examples an AI system learns from. They can be text, images, or numbers. The quality and makeup of this data shapes:

• How the system behaves
• What it does well
• Where it falls short

Worker surveillance or monitoring: Using technology, including AI, to track how employees work. This could be measuring people’s productivity, activity, or location. How companies apply technology matters. Some monitoring can be used to improve operations. Other monitoring can raise concerns about privacy.