Inclusive AI Usage: Ethical & Unbiased Machine Learning

Name: Inclusive AI Usage: Ethical & Unbiased Machine Learning
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Learn how AI and machine learning work and apply inclusive, ethical practices to reduce bias in your AI projects.

Created byPowerToFly Courses

Last updated 10/2025

English

What you'll learn

Understand how machine learning technology works and how it’s created
Use inclusive prompt writing techniques to develop bias-free content
Use inclusive prompt writing techniques to develop bias-free content
Apply learnings from this course into everyday life

Course content

4 sections • 13 lectures • 1h 11m total length

What is AI?6:22
In this lesson, Jess covered some key definitions and concepts related to artificial intelligence. Let’s recap some of them and dive even deeper into the vocabulary that surrounds this topic.

Artificial intelligence: a machine’s ability to perform the cognitive functions we typically associate with human minds such as perceiving, reasoning, learning, interacting with an environment, problem solving, and even exercising creativity.
Machine learning: a branch of artificial intelligence based on algorithms that are trained on data. These algorithms can detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. The algorithms also adapt in response to new data, experiences, and human input to improve their efficacy over time.
Neural networks: a subset of machine learning and deep learning algorithms that mimic the way biological neurons in the human brain signal to one another. Neural networks rely on training data to learn and improve their accuracy over time.
Deep learning: is a subset of machine learning methods based on neural networks where multiple layers of processing lead it to extract increasingly complex features of the data. These methods can be supervised, unsupervised, or semi-supervised.
Supervised: a subcategory of machine learning defined by its use of labeled datasets to train algorithms to classify data or predict outcomes.
Unsupervised: a subcategory of machine learning defined by its use of unlabeled data to train algorithms. It discovers patterns in the data and solves for clustering or association problems.
Semi-supervised: a type of machine learning that occurs when only part of the given data set has been labeled.
We know that this is a lot of information, and it can seem overwhelming, especially if you don’t have previous understanding of artificial intelligence and machine learning technologies. But don’t fret! We’ll keep things pretty simple in this course, and we’ll make sure to highlight any key information that you must know before moving on to the next lesson.
Lecture 1 quiz
AI Technologies5:24
All of the technological, academic, and scientific advancements that we’ve made so far with the help of machine learning is impressive. Let’s take a look at some other major advancements compiled by Burnie group that we can look forward to in the future.

Medical imaging: Computer vision represents a huge technological advancement for medical imaging and preventative care. The diagnostic program Zebra Medical Vision collects and analyzes medical scans for various clinical identifiers. It then accesses a database of millions of scans, enabling it to provide critical information such as the location of a tumor or a patient’s risk of cardiovascular disease.
Transit safety: AI technology is paving the way for autonomous cars and accident-free transit systems. The combination of deep learning and computer vision allows cars to observe and safely interact with the surrounding environment. Road safety can be further increased by AI-enabled navigation systems, which alert drivers to potential accidents and suggest alternative navigation routes.
Geospatial analytics: Geospatial analytics use computer vision to gather and compare satellite imagery with historical data in order to develop insights. Using these insights, AI-enabled satellites can track economic trends from space. Orbital Insight, for example, predicts retail sales based on satellite images of retail store parking lots.
Service industry: Some AI-enabled robots can not only understand human language but can recognize human emotions. Using computer vision, Softbank’s humanoid robot Pepper can interpret facial expressions as human emotions and generate responses accordingly. Pepper can also recognize and remember individual faces and preferences. It is primarily used as a greeter in Japanese office buildings, restaurants, banks, and stores.
Emotional detection: Emotional detection systems powered by AI can detect human emotions without visual input. Researchers at MIT have developed EQ Radio, a system that learns to identify human emotions based on heartbeat data collected by wireless signals. This technology may one day be used by smart homes to detect if a resident is experiencing a heart attack.
As you can see, the future of AI is bright. But what if technology gets so smart that it begins to outperform humans? This idea, called Strong AI, is being studied.
Strong AI is a hypothetical application of AI that aims to create intelligent machines that are indistinguishable from the human mind. The theory is that it would be able to perform intelligent human level activities, have the ability to learn and think, it would be creative and have common sense and logic, and be able to solve problems at a faster pace than humans.
A computer that thinks like, or even better than, a human. Whether you’re excited, intrigued, or totally freaked out by this, it’s totally understandable. We still have a very long way to go to even get remotely close to developing Strong AI systems, and to get there, we’ll have to clear up a lot of ethical, legal, and intellectual issues around the subject. In fact, many experts are confident that these types of systems cannot be developed, while others are more optimistic.
Lecture 2 quiz
AI Limitations and pitfalls7:55
If you’re at all familiar with AI-based applications and technologies (which you likely are, because 77% of people already use AI-powered technology), the benefits of its adoption are clear. But it’s very important to understand that, just like with everything, it has its limitations and pitfalls.
In this lesson, Jess highlights a few of those limitations, which were mostly an effect of human bias.
The global AI market is growing at an increasingly fast rate. This is a huge growth opportunity for businesses, a major disruption for industries, and an amazing opportunity to boost productivity on an individual level. However, it's important to find a balance between taking advantage of the benefits these technologies offer and making sure you’re avoiding some of the limitations of these technologies through AI usage inclusion best practices. We’ll go over some of them in the next module.

In the meantime, check out the resource in this lesson highlighting case studies of bias in AI technologies.
Lecture 3 quiz
Section 1 quiz

Copywriting and content production6:42
In this lesson, Jess talked about AI-powered copywriting and content production tools. Let’s recap some of the concepts she touched on.
AI copywriting is the creation of written content via machine learning. It harnesses natural language processing and large language model technologies. Let’s review some of those definitions.
Natural language processing: the ability of a computer program to understand human language as it is spoken and written.
Large language models: deep learning algorithms that can recognize, summarize, translate, predict, and generate content using very large datasets.
Some common AI software that can be used for copywriting and content production include ChatGPT, Jasper, and ContentShake.
These technologies use prompts as instructions to create a final result. Remember, prompting is the process of creating input (usually text) instructing the Generative AI to generate the desired response. There are actually AI-based tools that can help you optimize your prompts for AI. You can choose which program you’ll be working with, write your prompt, and the technology will optimize it for you. Prompt Perfect is an AI-powered AI prompt optimization tool. It also compares the results of your original prompt to the optimized prompt. Exploring these types of technologies is a great way to improve your prompt writing skills.

As you continue to do so, consider how you can harness these technologies to promote inclusion in other areas of your life and work. For example, you can use ChatGPT to evaluate text for potential bias. This can be helpful to spot imbalances or discrimination in company policy, training materials, and even personal emails. It can also be prompted to rewrite job descriptions without using discriminatory or biased language. Of course, this should just be a first line of defense against potential exclusion, inequity, and bias. And we always recommend hiring DEIB professionals to ensure that your company’s policies and trainings are inclusive.

For more information on how to make your AI usage more inclusive, check out the resource
Inclusive Generative AI Use Guide.
Lecture 4 quiz
Customer service6:55
dvancements in technology and the adoption of AI have rapidly changed the landscape of customer service. As companies continue to prioritize providing a better customer experience, AI tools for customer service have emerged as essential solutions for delivering efficient and effective support. With AI-powered chatbots and assistants, customer service teams can automate responses to frequently asked questions, offer personalized product recommendations, handle multiple customer conversations simultaneously, and operate 24/7 without exhaustion. This not only frees up time for service agents to tackle complex queries but also significantly reduces customer waiting time.
Let’s take a look at some real life applications of AI-powered customer service tools.
YOUS: a messaging software that offers real-time translations for voice and video chats using AI-based technologies. The AI-based translator can be used for audio/video meetings, phone conversations, and messaging and is eight times less expensive than human translators. It also can continuously improve its accuracy.
Delve AI: an AI platform that allows you to develop data-driven customer personas using social media analytics and Google Analytics data. Users may also utilize competition data to hone their ideal customer profile and blend it with information from their desired segment.
QuickReplai: a messaging software that offers on-demand virtual communication services. It uses AI technology to customize replies to the user’s requirements.
Kaizan: an intelligence platform that leverages language models to extract taks and actions from calls. It provides meeting summaries, recommendations for next steps, and risks and opportunities that can help the team maintain and score new clients.

These technologies have done well in increasing efficiency and productivity. But we have to be careful, because they do have their limitations. Remember the Bing example Jess mentioned in the lesson? We also talked about data protection as a major factor to keep track of when using AI. One thing we didn’t touch on is the actual customer experience.

Customers expect to be treated as individuals with unique needs and concerns, which is why empathy is such an important aspect of customer experience. AI can help deliver personalized experiences at scale, but it must be used in a way that respects each customer's uniqueness, which is much harder to do for a robot than a human. So, make your best effort to strike a balance between efficiency and empathy.
In fact, a responsible and ethical AI strategy in customer experience includes balancing all of these things, ensuring data privacy and transparency, and providing human oversight. By doing so, organizations can provide an experience that is both efficient and empathetic, and that meets their customers' needs and expectations.
Lecture 5 quiz
Presentation design and image generation6:16
Generative AI is some of the most impressive forms of machine learning technology for many people. It almost seems like magic when we get a piece of art, a song, a presentation, or even a video after simply writing a prompt.
However, just like with all forms of machine learning at this point in time, there are some ethical red flags with generative art AI. These ethical issues and risks mainly surround ownership, data privacy, and security. The lack of transparency that many generative AI software companies have is especially dangerous.
Some people argue that producing art entirely through AI and capitalizing on it without notifying or rewarding the original artist or artists is completely unethical. At this point in time, artists can do very little to reclaim their property or stop engines from using and reproducing their work. Taking action on this issue will become clearer once more laws and regulations are put into place regarding artificial intelligence. The bright side is, some companies, like Shutterstock’s AI Image Generator, set a positive example by compensating artists whose work the engine uses.

Here are some other examples AI-generated art tools:
Midjourney
DALL-E
DreamStudio
DeepAI
Generative AI isn’t just limited to images, though. Music and videos can also be created by AI. While this greatly empowers users to produce and use royalty-free music and amusing videos, similar to the generative art models, the ethics surrounding their use remain unresolved. Check out these AI-powered music and video generators.
Amper Music
Soundraw
MusicLM
D-ID
In case you’re looking to boost your presentations, here’s a list of AI-powered presentation design tools:
Simplified
Slidesgo
Gamma
Tome
Lecture 6 quiz
Coding5:58
An AI code assistant is a predictive coding software tool that uses artificial intelligence to help developers write code faster and more accurately. It uses and learns from past data and makes predictions about future data. This information can then be used to generate new code. Whether you’re a seasoned software engineer or a novice developer, you can use some of the following tools to help you in your coding journey.
GitHub Copilot
Amazon CodeWhisperer
Tabnine
Sourcegraph Cody
AskCodi
Lecture 7 quiz
Personal assistance4:52
AI-powered personal assistants are incredible for performing tasks and increasing productivity. But their benefits go beyond that. Let’s explore some ways AI opens the door to better accessibility.

AI accessibility refers to the use of artificial intelligence technology to improve accessibility for individuals with disabilities. It involves developing and implementing AI solutions that address barriers and challenges faced by people with disabilities in various aspects of life.

This Hand Talk article shares some AI assistive technology examples such as image and facial recognition, caption generators, lip reading technology, and more.
Speech recognition tools like Voiceitt are making a huge impact on users with non-standard speech patterns, enabling them to communicate more clearly. The technology is particularly beneficial for individuals who have cerebral palsy, Parkinson’s disease and Down syndrome, wherein producing clear speech can be challenging.
AI can be hugely beneficial for people with vision impairments. Seeing AI is an app that is able to identify objects through a phone camera and dictate what is there to the user, offering them more independence in their daily lives.
There are AI-powered mobility devices, such as wheelchairs, that can take audio cues from the user, allowing them to navigate autonomously. UPnRIDE and WHILL are organizations that are focusing on building out this cutting edge technology.
IEEE Computer Society notes that AI is “enhancing opportunities for digital accessibility because of the various ways that people can interact with AI-powered tools to make them work.” However, they flag that many tools are programmed with unintentional bias and discrimination, which can be addressed by partnering with accessibility experts during the software planning process.

Jagdeep Sidhu, CEO of Syslabs, a leading organization in AI-supported multilingual voice translation and recognition presented another challenge about the use of AI in accessibility. “When it comes to people with visual, auditory, or mobility-related impairments, there is no denying that AI-driven technologies hold incredible potential. That said, one of the most significant hurdles in integrating AI for accessibility lies in the realm of cost. It’s an unfortunate reality that people with disabilities often face steeper costs and challenges to perform everyday tasks compared to those without disabilities.”
Needless to say, we’ve got a ways to go to make AI inclusive and accessible for all. But the advancements we’ve made so far are very promising. Can you think of any other potential AI-powered solutions that can help you or others go about life more easily? Keep thinking and meet us in the next module.
Lecture 8 quiz
Section 2 quiz

Inclusive prompt commands6:29
Now that we’ve gone through the basics of how machine learning technology works, this lesson aimed to help you hone your prompt commands to get the best possible result. You can check out the resource linked below for a more detailed exploration of inclusive prompting strategies. And in the next lesson, we’ll tackle some of the larger implications of inclusive AI usage.
Lecture 9 quiz
Ethics of AI + other usage considerations6:03
AI has the potential to be so disruptive that it’s essential that it is developed and used in a responsible way that minimizes potential to cause harm. We already know some of the dangerous factors – bias, a lack of transparency and liability, job replacement, and a certain lack of control. In coming years, we will see continued focus on mitigating these problems and remaining vigilant for new ones. AI ethicists will be increasingly in demand as legislation is produced and as businesses present the need to adhere to ethical standards and deploy appropriate safeguards.
Lecture 10 quiz
Future implications of AI6:02
As Jess mentioned, the best way to stay up to date with the current state of AI and all of the developments we’ve talked about in this lesson is by following websites and content creators who are experts in the field. Check out the resource below for a list of websites, social media profiles, and accounts to follow to stay up-to-date on all things AI.
Lecture 11 quiz

Requirements

No prior technical knowledge or AI experience is required. Basic comfort using a computer or digital tools will be helpful, but not mandatory. Curiosity and a willingness to explore new technology will support your learning experience.

Description

Machine learning and artificial intelligence (AI) are emerging topics that’re getting an unprecedented amount of coverage and usage around the world. From writing formal emails to generating art work to organizing finances, the possibilities these technologies have unlocked are endless.

AI, machine learning, deep fake, deep learning, neural networks. The list goes on. All of these buzzwords point to emerging developments in technology that are quite literally changing the world. From organizing personal finances to advancing climate change research to diagnosing and treating diseases, Artificial Intelligence is taking the world by storm and impacting individuals, companies, and societies as a whole.

Although the future of AI sounds promising, we’re already seeing some of the limitations that come with it like bias, lack of transparency, and ambiguous ethical applications. As we continue on our journey to create more inclusive and equitable spaces, it's important that we equip ourselves with the knowledge and prowess to harness these technologies and use them for good.

LEARNING OBJECTIVES

After taking this course, learners will be able to:

Understand how machine learning technology works and how it’s created
Use inclusive prompt writing techniques to develop bias-free content
Use inclusive prompt writing techniques to develop bias-free content

FAQs

Do I need experience in artificial intelligence, machine learning, or coding before taking this course?
No. The course is designed for beginners and introduces concepts in clear, accessible language.

Is this course technical or theoretical?
It’s a blend of both. You’ll learn how AI and machine learning work at a high level, along with practical examples and simple exercises you can apply in real use cases—no programming required.

Will I learn how to write prompts and use AI tools during the course?
Yes. The course includes guidance on prompt writing, examples, and ways to interact with AI responsibly and effectively.

Does this course cover the risks or ethical considerations of AI?
Yes. You’ll explore important considerations such as fairness, transparency, accountability, and challenges related to unintended outcomes.

Will this course teach me how to build or code a machine learning model?
No. This course focuses on understanding AI concepts, how the technology works, and how to use it thoughtfully—not on programming or engineering.

Is this course relevant if I already use AI tools like ChatGPT, Gemini, or Claude?
Yes. Even experienced users often benefit from learning how AI systems operate and how to improve their approach to prompts and decision-making.

Who this course is for:

This course is for beginners and professionals alike who want to understand how AI works and learn to use it responsibly.

Inclusive AI Usage: Ethical & Unbiased Machine Learning

What you'll learn

Explore related topics

Course content

Understanding Machine Learning3 lectures • 20min

Main uses of AI5 lectures • 31min

Inclusive practices for AI use3 lectures • 19min

Key Takeaways and Final Review2 lectures • 2min

Requirements

Description

Who this course is for: