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AI Literacy and Critical Thinking

Learn more about AI, how it works, and the challenges and ethical implications of using it.

What is AI?

 

Elements of AI

Do you want to learn more about what AI really means — and how it’s created? Do you want to understand how AI works and learn about its implications? Feel free to take this free online course to deepen your understanding of AI. The Elements of AI is a series of free online courses created by MinnaLearn and the University of Helsinki. The first course, Introduction to AI, is a free online course for everyone interested in learning what AI is, what is possible (and not possible) with AI, and how it affects our lives – with no complicated math or programming required. It include six chapters, combines theory with practical exercises and can be completed at your own pace.

Evolution of AI

The following slides provide a brief history of AI evolution.

These slides are taken from the ChatGPT Unleashed: What to Expect This Fall and How to Prepare webinar offered by Alchemy on June 22, 2023 slides.

Generative AI: Free & Open Educational Resources

Your Guide to Communicating with Generative Artificial Intelligence

Learn how to use ChatGPT and other AI tools to accomplish your goals using a free and open-source curriculum designed for all skill levels! We recommend you take a look at "Basics" and "Basic Applications."

 

Generation AI: Human-centered Prompts for the Modern Educator - Design Mindset (free downloadable ebook)

This book helps you gain skills in AI prompting, lesson planning, and seamless communication.

AI Considerations

According to the 2023 UNESCO's "Chat GPT and Artificial Intelligence in Higher Education Quick Start Guide", the main challenges and implications of ChatGPT in higher education are:

  • Academic integrity
    • ChatGPT raises academic integrity concerns in higher education due to potential plagiarism and cheating. Reliable ChatGPT detection tools have yet to be developed.
  • Lack of regulation ChatGPT
    • ChatGPT's unregulated development raises concerns. Over 1,000 academics and leaders call for a pause to investigate risks and develop shared protocols.
  • Privacy concerns
    • In April 2023, Italy became the first country to block ChatGPT over privacy concerns and ethical issues regarding data collection and age verification, setting a precedent for AI-related data practices.
  • Cognitive bias
    • ChatGPT lacks ethical principles and can't differentiate between truth and bias or truth and fiction ("hallucination"). Critical analysis and cross-referencing with other sources are crucial when using its results.
  • Gender and diversity
    • Gender and discrimination concerns extend beyond ChatGPT to all AI forms due to underrepresentation of females in AI-related fields and generative AI's capability to perpetuate biased content and stereotypes.
  • Accessibility
    • Two main accessibility concerns for ChatGPT are restricted availability due to government regulations and uneven internet access, raising issues of equity and regional disparities in AI education and development.
  • Commercialization
    • ChatGPT offers both free and subscription options. Careful regulation is necessary for AI tools run by profit-driven companies, which may lack openness and use data for commercial purposes in higher education settings.

While AI technology offers significant advancements and efficiencies, it also comes with considerable environmental costs. The training and deployment of AI models require vast amounts of computational power, leading to high energy consumption and substantial carbon footprints. This article delves into the environmental impact of AI, highlighting the need for sustainable practices and the development of greener technologies. Resources and studies are provided to facilitate a deeper understanding of AI's ecological implications.

Recommended Reading:


Content Generation
The AI research tool Open Knowledge Maps was used to find the articles on the topics, and ChatGPT-4 was used to draft the paragraphs using the topics and the OA articles as prompts. The drafts were then revised by the library.

As AI technology continues to evolve, it brings forth a range of intellectual property concerns. The creation and use of AI models often involve complex algorithms and vast datasets, raising questions about ownership, rights, and the protection of intellectual property. The articles below explore the legal and ethical challenges associated with AI, including issues related to copyright, patents, and the fair use of data. They underscore the importance of establishing clear guidelines and policies to safeguard intellectual property while fostering innovation. Resources and case studies are provided to help navigate the intricate landscape of AI and intellectual property.

Recommended Reading:


Content Generation
The AI research tool Open Knowledge Maps was used to find the articles on the topics, and ChatGPT-4 was used to draft the paragraphs using the topics and the OA articles as prompts. The drafts were then revised by the library.

The development and maintenance of AI systems often rely on a hidden workforce, commonly referred to as "ghost workers." These individuals perform crucial tasks such as data labeling, content moderation, and training AI models. Many of these workers are located in the Global South and are paid minimum wages for their labor, often under harsh and precarious conditions. The article below explores the ethical and social implications of labor exploitation in the AI industry and provides resources for further understanding and advocacy.

Recommended Reading:


Content Generation
The AI research tool Open Knowledge Maps was used to find the articles on the topics, and ChatGPT-4 was used to draft the paragraphs using the topics and the OA articles as prompts. The drafts were then revised by the library.

Digital Labor Dynamics explores the transformation of work in the age of AI and digital platforms. The following article highlights the emergence of various forms of platform-based labor, including on-demand work, microwork, and social networked labor. These new labor models involve human tasks essential for training and maintaining AI systems, such as data annotation and content moderation. Understanding these dynamics is crucial for addressing the socio-economic impacts of AI, including labor rights, fair wages, and the future of employment in a technology-driven world.

Recommended Reading:


Content Generation
The AI research tool Open Knowledge Maps was used to find the articles on the topics, and ChatGPT-4 was used to draft the paragraphs using the topics and the OA articles as prompts. The drafts were then revised by the library.