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Steve Ballinger, MBA

Master the cutting edge of AI, responsibly.

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Master the cutting edge of AI, responsibly.

Generative AI (GenAI) using Large Language Models (LLMs) like ChatGPT and Google Gemini are revolutionizing the way we interact with technology. But with great power comes great responsibility. This course equips you to understand the ethical implications of LLMs and ensure their responsible use.

What You'll Learn:

  • The potential benefits and drawbacks of Generative AI.

  • Understanding bias in AI and how it impacts LLM outputs.

  • The rise of deep fakes and the ethical concerns surrounding them.

  • Data privacy and security considerations with Generative AI.

  • Frameworks for responsible development and deployment of LLMs.

  • Who Should Enroll:

    • Developers & Programmers: Working with LLMs to create applications, you'll gain the knowledge to mitigate bias, ensure data privacy, and build trust with users.

    • Business Professionals: Integrating LLMs into marketing, customer service, or content creation? Learn how to leverage their power ethically and responsibly.

    • Policymakers & Legislators: Shaping the future of AI requires an understanding of ethical considerations. This course equips you to create future-proof regulations.

    • Educators & Researchers: Developing the next generation of AI? Learn how to promote ethical practices within your field.

    • Content Creators & Writers: Exploring the use of LLMs for content generation? This course will help you navigate issues of authorship, plagiarism, and responsible use.

    • Journalists & Media Professionals: Combating misinformation and deepfakes is crucial. Gain the knowledge to identify potential issues and ensure ethical reporting.

    • Anyone Interested in AI's Future: This course offers a comprehensive understanding of the ethical landscape surrounding LLMs, preparing you for a future driven by AI.

This course is designed to be accessible and informative, regardless of your professional background.

Don't be left behind in the AI revolution. Enroll today and become a leader in the responsible use of Generative AI (GenAI).

Many thanks.

Steve Ballinger

Udemy Instructor

Demystifying AI: Your Frequently Asked Questions Answered

Artificial intelligence (AI) is a rapidly evolving field with a lot of buzz surrounding it. But what exactly is it, and how does it work? This post dives into the world of AI, answering some of your most frequently asked questions.

1. What is Artificial Intelligence (AI)?

AI is a broad term encompassing the intelligence displayed by machines, particularly computer systems. It's about creating intelligent agents that can perceive their environment, learn from data, and take actions to achieve specific goals. There are different types of AI, but most commonly we see:

  • Narrow AI (Weak AI): This type excels at performing specific tasks, like playing chess or recognizing faces.

  • General AI (Strong AI): This hypothetical AI would possess human-level intelligence and be able to perform any intellectual task a human can.

2. What is Generative AI?

Generative AI is a subfield of AI that focuses on creating new data, like text, images, or even code. It uses complex algorithms, often inspired by how the human brain works, to analyze existing data and then generate entirely new pieces of content that follow the same patterns.

For example, generative AI can be used to create realistic-looking images of people who don't actually exist, or to write different creative text formats, like poems or scripts.

3. What are LLMs (Large Language Models)?

LLMs are a type of AI model trained on massive amounts of text data. This allows them to process information and respond to questions in a way that simulates human conversation. I, for instance, am a large language model.

LLMs are used in a variety of applications, including chatbots, virtual assistants, and machine translation. They're constantly evolving, becoming better at understanding and responding to complex queries.

4. What is ChatGPT and Google Gemini.

ChatGPT and Gemini are both large language models, but we're developed by different companies. ChatGPT is from OpenAI, while Gemini is a product of Google AI. They share many capabilities, like generating text, translating languages, and writing different kinds of creative content. However, they may have different strengths and weaknesses, as they are trained on different datasets and have unique underlying algorithms.

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What's inside

Learning objectives

  • Identify and explain the potential benefits and drawbacks of generative ai across various applications.
  • Evaluate the ethical implications of deepfakes, a product of generative ai and articulate best practices for responsible use and detection.
  • Discuss the data privacy and security concerns associated with generative ai development and deployment.
  • Apply frameworks for responsible development and deployment of generative ai in a real-world context.

Syllabus

Ethics & Generative AI (GenAI)
Welcome and Quick Introduction to the AI Ethics Course!
Setting The Stage: How Would You React To These AI Ethical Situations.
Read more
Deep Fakes. Are Deep Fakes (AKA Deepfakes) the Biggest Potential Problem?
How To Spot A Deepfake. (Protecting Yourself From Deep Fakes).
What is Generative AI (GenAI) Exactly?
Its The Machines! AI Systems and Ethics
Transparency and the Black Box Problem.
Information Privacy in an AI World.
Fairness & Bias​.
Mitigating System Issues: Human Oversight & Informed Consent>
Oh No It's Us! Humans And AI Ethics​
Intro To Humans Using AI Unethically.
Copyright Concerns​.
AI Created Avatars (Will They Replace Us?)
AI Impact on Your Job. Job Displacement & Societal Impact​.
The Potential Big Pitfalls Of Advertising Inside our use of AI like ChatGPT.
Limitations Of AI. Hallucinations & more with LLM like ChatGPT and Gemini.
AI Models That Can Help Us
5 Principles​ Ethical Intelligence​ Model.
IBM AI Ethics Model.
Salesforce AI Ethical Maturity Model.
Big Predictions And Next Steps For Living In An GenAI World.
Big Predictions on the Future of Artificial Intelligence & Ethical Impact.
Top 4 Action Steps + Extra Step​

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores ethical implications of AI, addressing current industry concerns
Applies ethical frameworks to real-world AI contexts, enhancing learners' practical understanding
Focuses on Large Language Models (LLMs), which are highly relevant in current AI applications
Taught by Steve Ballinger, a recognized expert in AI ethics
Suitable for a wide audience, including developers, business professionals, and policymakers
Requires learners to engage with complex ethical issues in AI, which may be challenging for some

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Ethics & Generative AI (GenAI) with these activities:
Compile Course Materials
This is a good opportunity to consider what you know already in preparation for taking this course
Show steps
  • Gather course syllabus, handouts, and notes
  • Put course notes, handouts, and any other relevant documents in an organized place, such as a binder or folder
  • Make copies of any notes and handouts as needed
Complete Online Tutorials on Generative AI
Engage in hands-on tutorials to gain practical experience with Generative AI and LLMs
Browse courses on Generative AI
Show steps
  • Identify online tutorials or courses that cover Generative AI and LLMs
  • Follow the tutorials step-by-step, experimenting with different examples and techniques
  • Complete all the exercises and assignments in the tutorials
Create an AI Resource Collection
This is an opportunity to gather and organize resources that will support your ongoing learning in AI
Show steps
  • Search for and bookmark relevant websites, articles, and videos on AI topics
  • Compile a list of AI books, conferences, and workshops
  • Create a database or spreadsheet to organize your AI resources
Four other activities
Expand to see all activities and additional details
Show all seven activities
Develop a Generative AI Application
Apply your knowledge in a real-world setting by creating an application that leverages Generative AI
Show steps
  • Brainstorm an idea for a Generative AI application
  • Design and develop the application using appropriate tools and frameworks
  • Test and refine the application to ensure it meets the desired functionality
Attend an AI Ethics Workshop
Engage with experts and practitioners in the field to delve deeper into ethical considerations and best practices for AI
Browse courses on AI Ethics
Show steps
  • Research and identify upcoming AI ethics workshops or conferences
  • Register and attend the workshop, actively participating in discussions and activities
  • Connect with other attendees and speakers to exchange ideas and insights
Mentor Junior AI Practitioners
Consolidate your understanding by sharing your knowledge and experience with others, reinforcing your own learning
Show steps
  • Identify opportunities to mentor junior AI practitioners or students
  • Provide guidance and support on AI concepts, tools, and best practices
  • Answer questions and offer constructive feedback to help mentees develop their skills
Contribute to Open-Source AI Projects
Engage with the broader AI community by contributing to open-source projects, gaining practical experience and showcasing your skills
Show steps
  • Identify open-source AI projects that align with your interests and skillset
  • Review the project documentation and contribute code, bug fixes, or enhancements
  • Collaborate with other developers and maintainers to improve the project

Career center

Learners who complete Ethics & Generative AI (GenAI) will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists play a key role in the development and deployment of Generative AI (GenAI) models, using their expertise in data analysis, modeling, and machine learning techniques. This course provides a foundational understanding of the ethical implications of GenAI, enabling Data Scientists to build and implement models responsibly. By addressing issues such as bias, privacy, and deepfakes, this course empowers Data Scientists to navigate the ethical landscape of GenAI and contribute to the responsible advancement of the field.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models, including GenAI models. This course equips Machine Learning Engineers with the knowledge and skills to identify and mitigate ethical concerns related to GenAI, such as bias, data privacy, and algorithmic fairness. By understanding the ethical implications of GenAI, Machine Learning Engineers can develop and deploy models that align with ethical principles and societal values.
AI Ethics Researcher
AI Ethics Researchers specialize in the ethical implications of artificial intelligence, including GenAI. This course provides a comprehensive exploration of the ethical challenges posed by GenAI, helping AI Ethics Researchers develop frameworks and best practices for responsible AI development and deployment. By engaging with the latest research and case studies, this course empowers AI Ethics Researchers to contribute to the ongoing dialogue and shape the ethical future of AI.
AI Policymaker
AI Policymakers develop and implement policies that govern the development and use of AI, including GenAI. This course provides AI Policymakers with a deep understanding of the ethical implications of GenAI, enabling them to create policies that promote responsible innovation and protect the public interest. By exploring case studies and engaging with experts, this course empowers AI Policymakers to shape the legal and regulatory landscape for GenAI.
Ethical Hacker
Ethical Hackers use their skills to identify and exploit vulnerabilities in computer systems and networks to improve security. This course provides Ethical Hackers with the knowledge and tools to assess the security risks associated with GenAI models and identify potential vulnerabilities. By understanding the ethical implications of GenAI, Ethical Hackers can contribute to the development of secure and trustworthy AI systems.
Privacy Analyst
Privacy Analysts ensure that organizations comply with data privacy laws and regulations. This course provides Privacy Analysts with a comprehensive understanding of the privacy concerns associated with GenAI, enabling them to develop and implement privacy-preserving measures. By addressing issues such as data collection, storage, and use, this course empowers Privacy Analysts to protect user data and maintain trust in AI systems.
Legal Counsel (Technology)
Legal Counsel specializing in technology provide legal advice on the development and use of AI, including GenAI. This course provides Legal Counsel with a deep understanding of the ethical and legal implications of GenAI, enabling them to advise clients on compliance, risk management, and liability. By engaging with case studies and industry experts, this course empowers Legal Counsel to navigate the complex legal landscape of AI.
Product Manager - AI
Product Managers responsible for AI products, including GenAI models, play a crucial role in ensuring that these products are developed and deployed responsibly. This course provides Product Managers with the knowledge and skills to identify and address ethical concerns throughout the product lifecycle. By understanding the potential benefits and drawbacks of GenAI, Product Managers can create AI products that deliver value while adhering to ethical principles.
Data Protection Officer (DPO)
Data Protection Officers (DPOs) are responsible for ensuring that organizations comply with data protection laws and regulations. This course provides DPOs with a comprehensive understanding of the data privacy and security concerns associated with GenAI, enabling them to develop and implement effective data protection measures. By addressing issues such as data collection, storage, and use, this course empowers DPOs to protect user data and maintain trust in AI systems.
Business Analyst (AI)
Business Analysts specializing in AI help organizations understand the business value and ethical implications of AI technologies, including GenAI. This course provides Business Analysts with a comprehensive understanding of the ethical considerations associated with GenAI, enabling them to evaluate and recommend AI solutions that align with organizational values and societal norms. By engaging with case studies and industry experts, this course empowers Business Analysts to drive responsible AI adoption.
Software Engineer (AI)
Software Engineers specializing in AI design and develop AI systems, including GenAI models. This course provides Software Engineers with the knowledge and skills to build ethically responsible AI systems. By understanding the ethical implications of GenAI, Software Engineers can implement best practices for data handling, bias mitigation, and algorithmic fairness. This course empowers Software Engineers to contribute to the development of AI systems that are trustworthy and beneficial to society.
Risk Manager (AI)
Risk Managers specializing in AI help organizations identify, assess, and mitigate risks associated with AI technologies, including GenAI. This course provides Risk Managers with a comprehensive understanding of the ethical and legal risks associated with GenAI, enabling them to develop and implement risk management strategies. By engaging with case studies and industry experts, this course empowers Risk Managers to navigate the complex risk landscape of AI and ensure the responsible development and deployment of GenAI systems.
Journalist (AI)
Journalists specializing in AI report on the latest developments and ethical implications of AI technologies, including GenAI. This course provides Journalists with a deep understanding of the ethical considerations associated with GenAI, enabling them to critically evaluate and inform the public about the responsible development and deployment of AI. By engaging with experts and exploring case studies, this course empowers Journalists to contribute to a well-informed public discourse on AI and its impact on society.
Educator (AI)
Educators specializing in AI teach courses and develop curricula on AI technologies, including GenAI. This course provides Educators with a deep understanding of the ethical implications of GenAI, enabling them to educate students on the responsible development and deployment of AI. By engaging with experts and exploring case studies, this course empowers Educators to prepare the next generation of AI professionals with the knowledge and skills to navigate the ethical challenges of AI.
Consultant (AI)
Consultants specializing in AI provide guidance and support to organizations on the development and deployment of AI technologies, including GenAI. This course provides Consultants with a deep understanding of the ethical implications of GenAI, enabling them to advise clients on responsible AI adoption. By engaging with experts and exploring case studies, this course empowers Consultants to help organizations navigate the ethical challenges of AI and derive maximum value from AI technologies.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Ethics & Generative AI (GenAI).
Explores the challenge of aligning AI systems with human values. It must-read for anyone interested in the ethical development and deployment of AI.
Provides a comprehensive overview of the ethical issues surrounding AI. It valuable resource for anyone interested in the ethical development and deployment of AI.
Explores the potential risks and benefits of superintelligence and provides guidance on how to mitigate the risks. It thought-provoking read for anyone interested in the ethical implications of AI.
Provides a clear and accessible overview of the ethical issues surrounding AI. It valuable resource for anyone looking to understand the ethical challenges and opportunities of AI.
Explores the potential risks and harms of deepfakes and provides guidance on how to mitigate these risks. It timely and important read for anyone concerned about the ethical implications of Generative AI.
Examines the role of algorithms in society and the ethical concerns surrounding their use. It provides a valuable framework for understanding the ethical implications of Generative AI.
Provides a comprehensive overview of the ethical issues surrounding information technology, including the ethical implications of AI. It valuable resource for anyone interested in the ethical development and deployment of AI.
Explores the potential impact of AI on society and the future of humanity. It thought-provoking read for anyone interested in the ethical implications of Generative AI.

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