Merge branch 'main' of https://github.com/fhdsl/AI_for_Decision_Makers …

…into main

docs/no_toc/01a-AI_Possibilities-intro.md

@@ -19,7 +19,7 @@ This course is targeted toward industry and non-profit leaders and decision make
 
 ## Curriculum
 
-In this course, we'll learn about what Artificial intelligence is, and what it isn't. We'll also learn the basics of how it works, learn about different types of AI, and set some ground rules for minimizing the harms and maximizing the benefits of AI.
+In this course, we'll learn about what Artificial intelligence is, and what it isn't. We'll also learn the basics of how it works, and learn about different types of AI.
 
 This course will cover:
 
@@ -28,7 +28,7 @@ This course will cover:
 - The take-home of how AI works
 - Key definitions of types of AI and related technologies
 - What is possible with AI
-- Ground rules for using AI for good
+
 
 ## Learning Objectives
 
@@ -37,14 +37,13 @@ We will learn how to:
 - Determine what AI is and isn't using our three part framework: the data, algorithm, and interface
 - Identify common technologies and whether or not they are AI
 - Explain the essential "behind the scenes" technology of how AI works
-- Detail ground rules for using AI ethically
 - Identify possibilities for using AI while understanding its limitations
 
 <br>
 <div class = disclaimer>
 **Disclaimer:** The thoughts and ideas presented in this course are not to be substituted for legal or ethical advice and are only meant to give you a starting point for gathering information about AI policy and regulations to consider.
 </div>
 
-# VIDEO Introduction to Exploring AI Possibilities
+# VIDEO Introduction to Exploring AI Possibilities {.unlisted .unnumbered}
 
 You can find the Google Slides for this video [here](https://docs.google.com/presentation/d/1M6lqJoN0yQDPJtO8nGWYrb7pI6kNv3uZeKcB8y5iPok/edit?usp=sharing).

docs/no_toc/01d-AI_Possibilities-ai_types.md

@@ -33,6 +33,12 @@ Neural networks often require large amounts of labeled data for training, and th
 
 <img src="resources/images/01d-AI_Possibilities-ai_types_files/figure-html//1UiYOR_4a68524XsCv-f950n_CfbyNJVez2KdAjq2ltU_g2a7d2be0b8f_0_434.png" title="CAPTION HERE" alt="CAPTION HERE" width="100%" style="display: block; margin: auto;" />
 
+<div class = "dictionary">
+Many of the machine learning approaches we're discussing here are **supervised learning** approaches. This means that data is labeled in predefined categories. An example could be "spam" or "not spam" labels attached to a data set of emails.
+
+Sometimes, we are more interested in discovering variation, regardless of how we describe, or label, the data. This is called **unsupervised learning**. An example of this approach could be clustering human cells based on what kind of genes they have turned on. We don't know what type of cells they are necessarily, but can group them based on their behavior.
+</div>
+
 ## Generative AI
 
 Artificial Intelligence exploded in the early 2020s due to advancements in **Generative AI**, which includes text generation, image creation, natural speech generation, computer code production, biological molecule discovery, simulated data, and more. Let's break down some of the following terms related to generative AI.

docs/no_toc/01f-AI_Possibilities-ground_rules.md

@@ -3,22 +3,39 @@
 
 # Ground Rules for AI
 
-Ground rules - don’t do bad things with AI!
+The rapidly changing AI landscape has brought unexpected ethical challenges. To promote benefit over harm, we suggest following these AI use and development guidelines:
 
-<!-- ## Motivation -->
+1. **Recognize guidelines**. Today, there are some guidelines for ethical use. More will be developed. It is advised that you stay up-to-date on industry-specific guidelines.
 
+1. **Consider consequences**. Think about possible downstream unintended consequences for using AI. This could be in the context of creating content or developing new AI tools. 
 
-<!-- ## Target Audience   -->
+1. **Acknowledge shortcomings**. AI is not perfect. It makes mistakes, is not necessarily superior to humans, and should be used as intended and trained. It is also only as up-to-date as its training data. While humans are very good at generalizing knowledge for different contexts, AI systems can sometimes struggle with this. Human oversight is needed for important and consequential uses.
 
-<!-- The course is intended for ... -->
+1. **Understand bias**. Realize that AI often perpetuates bias. AI is created using data generated by humans, and that data can be biased. It is important to use inclusive datasets and seek expert advice.
 
-<!-- ## Curriculum   -->
+1. **Promote access**. Promote equitable access to AI. Differences in access could worsen existing disparities, or create new ones. 
 
-<!-- The course covers... -->
+1. **Think securely**. AI poses security and privacy threats. AI needs to be used and developed carefully with these aspects in mind. Do not use proprietary or private information as prompts for consumer AI tools unless it was specifically designed for private data.
 
-# VIDEO Knowing the Ground Rules
+1. **Understand costs**. AI could exacerbate global climate change and human welfare disparities. Developers should be considerate about their computation needs and not use larger than necessary datasets. Workers who label and curate datasets should be compensated appropriately.
 
+1. **Be transparent**. Users should be transparent about their use of AI tools. It makes it easier to locate the source of issues. It also helps to uplift human contributions to work and art.
 
+1. **Credit sources**. When developing tools, be transparent about what data you used to create your AI systems. Be careful not to use work or data from individuals who did not consent to it being used in such ways.
+
+1. **Work thoughtfully**. Ramp up AI projects gradually to identify unexpected behaviors or impacts before full deployment. Starting slowly enables recognition and resolution of issues.
+
+1. **Acknowledge complexity**. Recognize that if AI systems use overly complex models, it can be difficult to trace how decisions are made using them.
+
+1. **Diversify usage**. Check the consistency of results using multiple AI tools and timepoints, where possible.
+
+1. **Keep learning**. Educate yourself and others. To comply with ethical standards, users must be educated about best use practices. If you help set standards for an institution or group, it strongly advised that you carefully consider how to educate individuals about those standards of use.
+
+To learn more about how to responsibly use and develop AI, check out the following minicourse about Avoiding AI harm.
+
+# VIDEO Knowing the Ground Rules {.unlisted .unnumbered}
+
+<br>
 <div class = disclaimer>
 **Disclaimer:** The thoughts and ideas presented in this course are not to be substituted for legal or ethical advice and are only meant to give you a starting point for gathering information about AI policy and regulations to consider.
 </div>

docs/no_toc/02d-Avoiding_Harm-adherence.md

@@ -105,7 +105,7 @@ Did this content use any content from others that I can cite?
 
 <div class = fordev>
 
-**For decision makers about AI developement:**
+**For decision makers about AI development:**
 
 * Obtain permission from the copyright holders of any content that you use to train an AI system. Only use content that has been licensed for use.
 * Cite all content that you can.

docs/no_toc/03a-Determining-AI-Needs-intro.md

@@ -21,7 +21,7 @@ You can view and download the Google Slides [here](https://docs.google.com/prese
 
 ## Motivation
 
-There are a ever increasing number of options, strategies and solutions for integrating AI solutions into a project. It can feel overwhelming to understand what these options entail let alone understand how to decide what solution best fits a use case.
+There are an ever increasing number of options, strategies and solutions for integrating AI solutions into a project. It can feel overwhelming to understand what these options entail let alone understand how to decide what solution best fits a use case.
 
 In this course we aim to give individuals the basic info they need to make basic plans for integrating AI tools into their project.
 

docs/no_toc/404.html

@@ -129,7 +129,6 @@
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#curriculum"><i class="fa fa-check"></i>Curriculum</a></li>
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#learning-objectives"><i class="fa fa-check"></i>Learning Objectives</a></li>
 </ul></li>
-<li class="chapter" data-level="" data-path="video-introduction-to-exploring-ai-possibilities.html"><a href="video-introduction-to-exploring-ai-possibilities.html"><i class="fa fa-check"></i>VIDEO Introduction to Exploring AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="video-what-is-ai.html"><a href="video-what-is-ai.html"><i class="fa fa-check"></i>VIDEO What Is AI</a></li>
 <li class="chapter" data-level="" data-path="what-is-artificial-intelligence.html"><a href="what-is-artificial-intelligence.html"><i class="fa fa-check"></i>What Is Artificial Intelligence</a>
 <ul>
@@ -221,7 +220,6 @@
 </ul></li>
 <li class="chapter" data-level="" data-path="discussion-ai-possibilities.html"><a href="discussion-ai-possibilities.html"><i class="fa fa-check"></i>DISCUSSION AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="ground-rules-for-ai.html"><a href="ground-rules-for-ai.html"><i class="fa fa-check"></i>Ground Rules for AI</a></li>
-<li class="chapter" data-level="" data-path="video-knowing-the-ground-rules.html"><a href="video-knowing-the-ground-rules.html"><i class="fa fa-check"></i>VIDEO Knowing the Ground Rules</a></li>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html"><i class="fa fa-check"></i>AI Possibilities Case Studies</a>
 <ul>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html#financial-forecasting"><i class="fa fa-check"></i>Financial Forecasting</a>

docs/no_toc/About.md

@@ -46,7 +46,7 @@ These credits are based on our [course contributors table guidelines](https://ww
 ##  collate  en_US.UTF-8                 
 ##  ctype    en_US.UTF-8                 
 ##  tz       Etc/UTC                     
-##  date     2024-01-08                  
+##  date     2024-01-09                  
 ## 
 ## ─ Packages ───────────────────────────────────────────────────────────────────
 ##  package     * version date       lib source                            

docs/no_toc/about-the-authors.html

@@ -129,7 +129,6 @@
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#curriculum"><i class="fa fa-check"></i>Curriculum</a></li>
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#learning-objectives"><i class="fa fa-check"></i>Learning Objectives</a></li>
 </ul></li>
-<li class="chapter" data-level="" data-path="video-introduction-to-exploring-ai-possibilities.html"><a href="video-introduction-to-exploring-ai-possibilities.html"><i class="fa fa-check"></i>VIDEO Introduction to Exploring AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="video-what-is-ai.html"><a href="video-what-is-ai.html"><i class="fa fa-check"></i>VIDEO What Is AI</a></li>
 <li class="chapter" data-level="" data-path="what-is-artificial-intelligence.html"><a href="what-is-artificial-intelligence.html"><i class="fa fa-check"></i>What Is Artificial Intelligence</a>
 <ul>
@@ -221,7 +220,6 @@
 </ul></li>
 <li class="chapter" data-level="" data-path="discussion-ai-possibilities.html"><a href="discussion-ai-possibilities.html"><i class="fa fa-check"></i>DISCUSSION AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="ground-rules-for-ai.html"><a href="ground-rules-for-ai.html"><i class="fa fa-check"></i>Ground Rules for AI</a></li>
-<li class="chapter" data-level="" data-path="video-knowing-the-ground-rules.html"><a href="video-knowing-the-ground-rules.html"><i class="fa fa-check"></i>VIDEO Knowing the Ground Rules</a></li>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html"><i class="fa fa-check"></i>AI Possibilities Case Studies</a>
 <ul>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html#financial-forecasting"><i class="fa fa-check"></i>Financial Forecasting</a>
@@ -634,7 +632,7 @@ <h1>About the Authors</h1>
 ##  collate  en_US.UTF-8                 
 ##  ctype    en_US.UTF-8                 
 ##  tz       Etc/UTC                     
-##  date     2024-01-08                  
+##  date     2024-01-09                  
 ## 
 ## ─ Packages ───────────────────────────────────────────────────────────────────
 ##  package     * version date       lib source                            

docs/no_toc/adherence-practices.html

@@ -129,7 +129,6 @@
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#curriculum"><i class="fa fa-check"></i>Curriculum</a></li>
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#learning-objectives"><i class="fa fa-check"></i>Learning Objectives</a></li>
 </ul></li>
-<li class="chapter" data-level="" data-path="video-introduction-to-exploring-ai-possibilities.html"><a href="video-introduction-to-exploring-ai-possibilities.html"><i class="fa fa-check"></i>VIDEO Introduction to Exploring AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="video-what-is-ai.html"><a href="video-what-is-ai.html"><i class="fa fa-check"></i>VIDEO What Is AI</a></li>
 <li class="chapter" data-level="" data-path="what-is-artificial-intelligence.html"><a href="what-is-artificial-intelligence.html"><i class="fa fa-check"></i>What Is Artificial Intelligence</a>
 <ul>
@@ -221,7 +220,6 @@
 </ul></li>
 <li class="chapter" data-level="" data-path="discussion-ai-possibilities.html"><a href="discussion-ai-possibilities.html"><i class="fa fa-check"></i>DISCUSSION AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="ground-rules-for-ai.html"><a href="ground-rules-for-ai.html"><i class="fa fa-check"></i>Ground Rules for AI</a></li>
-<li class="chapter" data-level="" data-path="video-knowing-the-ground-rules.html"><a href="video-knowing-the-ground-rules.html"><i class="fa fa-check"></i>VIDEO Knowing the Ground Rules</a></li>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html"><i class="fa fa-check"></i>AI Possibilities Case Studies</a>
 <ul>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html#financial-forecasting"><i class="fa fa-check"></i>Financial Forecasting</a>
@@ -602,7 +600,7 @@ <h3>Tips for checking for allowed use</h3>
 </div>
 <p><br></p>
 <div class="fordev">
-<p><strong>For decision makers about AI developement:</strong></p>
+<p><strong>For decision makers about AI development:</strong></p>
 <ul>
 <li>Obtain permission from the copyright holders of any content that you use to train an AI system. Only use content that has been licensed for use.</li>
 <li>Cite all content that you can.</li>

docs/no_toc/ai-acts-orders-and-regulations.html

@@ -129,7 +129,6 @@
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#curriculum"><i class="fa fa-check"></i>Curriculum</a></li>
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#learning-objectives"><i class="fa fa-check"></i>Learning Objectives</a></li>
 </ul></li>
-<li class="chapter" data-level="" data-path="video-introduction-to-exploring-ai-possibilities.html"><a href="video-introduction-to-exploring-ai-possibilities.html"><i class="fa fa-check"></i>VIDEO Introduction to Exploring AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="video-what-is-ai.html"><a href="video-what-is-ai.html"><i class="fa fa-check"></i>VIDEO What Is AI</a></li>
 <li class="chapter" data-level="" data-path="what-is-artificial-intelligence.html"><a href="what-is-artificial-intelligence.html"><i class="fa fa-check"></i>What Is Artificial Intelligence</a>
 <ul>
@@ -221,7 +220,6 @@
 </ul></li>
 <li class="chapter" data-level="" data-path="discussion-ai-possibilities.html"><a href="discussion-ai-possibilities.html"><i class="fa fa-check"></i>DISCUSSION AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="ground-rules-for-ai.html"><a href="ground-rules-for-ai.html"><i class="fa fa-check"></i>Ground Rules for AI</a></li>
-<li class="chapter" data-level="" data-path="video-knowing-the-ground-rules.html"><a href="video-knowing-the-ground-rules.html"><i class="fa fa-check"></i>VIDEO Knowing the Ground Rules</a></li>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html"><i class="fa fa-check"></i>AI Possibilities Case Studies</a>
 <ul>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html#financial-forecasting"><i class="fa fa-check"></i>Financial Forecasting</a>

docs/no_toc/ai-possibilities-case-studies.html

@@ -129,7 +129,6 @@
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#curriculum"><i class="fa fa-check"></i>Curriculum</a></li>
 <li class="chapter" data-level="" data-path="introduction-to-exploring-ai-possibilities.html"><a href="introduction-to-exploring-ai-possibilities.html#learning-objectives"><i class="fa fa-check"></i>Learning Objectives</a></li>
 </ul></li>
-<li class="chapter" data-level="" data-path="video-introduction-to-exploring-ai-possibilities.html"><a href="video-introduction-to-exploring-ai-possibilities.html"><i class="fa fa-check"></i>VIDEO Introduction to Exploring AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="video-what-is-ai.html"><a href="video-what-is-ai.html"><i class="fa fa-check"></i>VIDEO What Is AI</a></li>
 <li class="chapter" data-level="" data-path="what-is-artificial-intelligence.html"><a href="what-is-artificial-intelligence.html"><i class="fa fa-check"></i>What Is Artificial Intelligence</a>
 <ul>
@@ -221,7 +220,6 @@
 </ul></li>
 <li class="chapter" data-level="" data-path="discussion-ai-possibilities.html"><a href="discussion-ai-possibilities.html"><i class="fa fa-check"></i>DISCUSSION AI Possibilities</a></li>
 <li class="chapter" data-level="" data-path="ground-rules-for-ai.html"><a href="ground-rules-for-ai.html"><i class="fa fa-check"></i>Ground Rules for AI</a></li>
-<li class="chapter" data-level="" data-path="video-knowing-the-ground-rules.html"><a href="video-knowing-the-ground-rules.html"><i class="fa fa-check"></i>VIDEO Knowing the Ground Rules</a></li>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html"><i class="fa fa-check"></i>AI Possibilities Case Studies</a>
 <ul>
 <li class="chapter" data-level="" data-path="ai-possibilities-case-studies.html"><a href="ai-possibilities-case-studies.html#financial-forecasting"><i class="fa fa-check"></i>Financial Forecasting</a>