Artificial intelligence in higher education
When you take a selfie and the mobile phone camera finds your face with a rectangle – that's artificial intelligence (AI). When your friends are automatically tagged in a picture on social media – that's AI. When you get content recommendations for music, movies and series on various streaming services – that's also AI. AI development affects the whole of society and all people.
Key concepts
Artificial intelligence (AI) – Has no clear definition but refers to software that is autonomous and adaptive to varying degrees, i.e. works independently and adapts itself.
Data – Information that is registered somewhere.
Algorithm – A sequence of instructions. Like a recipe for baking.
Model - The part of the software that is used to solve the problem, for example make a prediction.
Training data – The data used to train the model in machine learning.
Machine learning – An important subfield of AI. Systems that get better at a given task as the amount of experience and data increases.
Neural network – A tool for solving machine learning problems. It is a structure for training a model that is loosely based on the biological neural networks found in our brains.
Deep learning – An important subfield of machine learning. In deep learning, there is a neural network containing many layers of neurons (non-deep learning involves neural networks with only one or a small number of layers of neurons).
Generative AI - AI that can generate data: text, images, film and music.
Bias – A distortion or skew in the calculation or interpretation of the available information.
Algorithmic discrimination – Occurs because the training data on which a model is trained is biased. This data is originally authored by humans and reflects, in both content and quantity, preconceived ideas and patterns in society.
Nowadays, AI is established in virtually all areas of society. Yet, surprisingly, many of us have a very limited understanding of how these technologies work and what they can be used for.
In order for us to make wise decisions and realise the potential of AI, each and every one of us needs to upgrade our knowledge of AI. Economists, politicians, teachers, nurses, lawyers, doctors, musicians, engineers and chefs. No one can say that AI does not affect them or their profession.
For teachers in higher education, this means that course syllabuses may need to be updated and that teaching may need to include the latest knowledge on how AI may affect students' future profession or research area.
Ultimately, it comes down to the world we want to live in. Knowledge gaps about AI in large parts of society become a democracy problem. It is not just the programmers who need to think about privacy, legislation, ethical aspects and security. Or to decide in which areas of healthcare, education, industry or the legal system AI is suitable or not. Many of these issues are political in nature and affect everyone.
At the bottom of this page, under the “Videos – with reflection and discussion questions” tab, you will find a short introductory video (14 min) about what AI is.
Generative AI
More recently, we have seen the emergence of several new services that can generate text, images and music. One example of generative AI is the ChatGPT service launched in late 2022 by the research company OpenAI and partly funded by Microsoft. The development continues and Microsoft is integrating generative AI into several of its services.
On the page Generative AI in teaching and examinations, you will find pedagogical support that has been devised based on discussions with teachers and external monitoring, and with the aid of a lawyer and information security manager. This information has also been approved by the Strategic Council for Education to ensure it is in line with the university's position on generative AI.
Below you will also find 10 tips on how you as a teacher can deal with the rapid development of generative AI.
10 tips for dealing with AI development
- Try ChatGPT or another generative tool. The best way to get an idea of AI-based text generator tools is to try them yourself.
- Watch the video on AI text generator tools if you are curious about how you could use AI text generator tools as a resource in your teaching or what you need to be aware of to prevent cheating in examinations. The video is found under the “Videos – with reflection and discussion questions” tab further down on this page.
- Think about how AI affects, or will affect, your subject or field. Are there any applications you are aware of?
- Think about what is considered relevant knowledge today and tomorrow. Our students need to be equipped for a world in which AI, as a technology, is part of society.
- Think about what students need to know about how AI affects their future professional role or research area. Are there any aspects of the profession or research area in which AI could be used?
- Make AI part of the content of your course. This could relate to current and future applications, ethical and legal aspects, or perhaps opportunities and challenges in your field. Algorithmic discrimination, deep fakes and social media influence campaigns are just a few examples. Assessment support in healthcare screening, self-driving cars and customised content recommendation are other examples of what your content could include.
- Teach critical evaluation of sources. Students need to be able to think critically about AI-generated claims and texts. A general understanding of how generative AI works can make a big difference and demystify what may otherwise feel unfamiliar and complex.
- Engage in discussions with colleagues about how to address this in relation to examinations within your subject. How do you create relevant and high-quality examinations that assess what you intend to assess in relation to intended learning outcomes and learning activities? This is a question that needs to be kept alive. The examinations must be both legally certain and relevant.
- Test your examination tasks in a text generator tool. This will give you an idea of how well an examination task works. For example, is the question too general?
- Look over your examinations. The video on AI text generator tools, which is found under the heading “Videos – with reflection and discussion questions” further down on this page, provides some tips on things to think about in relation to take-home examinations. Following up on take-home examinations, contextualising, focusing on the process, combining and varying examination formats, asking students to meta-reflect, using peer assessment or using AI-generated texts as part of the examination are some strategies you can use. No one can do everything, but maybe you, together with your colleagues, can start somewhere and do something?
Generative AI for the teacher in our learning platform
The latest update of our learning platform Bb Learn (Blackboard) includes generative AI as a tool for the teacher. This allows teachers to use AI and their own good judgement to generate modules, headings, images, question banks and assessment matrices. This can then provide inspiration and a foundation for further review and refinement. If you think this sounds exciting and want some help getting started, you can contact the Centre for Academic Development for a small demonstration of the new functionality. Read more on the AI in Bb Learn page.
Getting started with AI integration
We have provided some suggestions on how to go about integrating AI into your programme. You can find both information and support materials on the How to integrate perspectives in your programme page.
Read more
Artificial intelligence and robotics at Örebro University
WASP-ED: The Wallenberg AI and Transformative Technologies Education Development Program