1.0 Introduction

✍️ Author: Frank Wolf (MMKH, Digital Analyst), Katrin Schröder (MMKH, Communications)
⏱ You will need around 90 minutes for this chapter

 

Understanding AI so you can engage with it and put it to use: the basics for everyday campus life

AI is not longer a thing of the future – it has been part of your everyday working life for quite some time now. Whether you are a lecturer, researcher, administrative staff member or student: you are encountering systems such as Copilot, ChatGPT, Mistral and other AI applications with increasing frequency. In this chapter, you will gain the necessary basic technical understanding to make sense of these developments – explained clearly and ready for immediate application.

  

You will

✅ learn key terms and how they work,

✅ distinguish between different types of AI systems and

✅ discover how language models actually "think".

✅ We will also take an initial look at the challenges associated with AI – such as biases in training data or the phenomenon of so-called hallucinations.

  

Integrating AI into our discourse

Artificial Intelligence is much more than just a trend or a hot topic. It writes texts, replies to e-mails, assesses performance, analyses data – often faster than we do. AI also appears with increasing frequency in everyday campus life: in tools such as ChatGPT, in administration, in teaching, or in exam questions.

We must therefore integrate AI as a topic into our academic, educational and societal discourses.

  

But how does AI actually work?

AI refers to computer systems that mimic human abilities such as understanding, planning, decision-making or even creativity. These systems learn from data, recognise patterns and use them to solve tasks. In a higher education context, it is not just about the use of AI, but also about the ability to critically examine it: technically, ethically and legally. This chapter provides you with the necessary foundation. Image source

  

  

📖 This chapter comprises the following sections

1.1 Basics: How AI works

An accessible introduction to how AI systems function

1.2 Types of AI: Weak vs. strong AI

An overview of key types of AI and their applications

1.3 How machines learn: Neural networks, deep learning and LLMs

A look under the bonnet of modern AI technologies such as ChatGPT

1.4 Generative AI and potential applications

An overview of various generative tools

1.5 Prompting

An overview of targeted prompting for optimal results.