Learning cafe XVIII: AI - what is essential in future learning with machine learning? (10.5.2023) 9ca1f7ca7d5d434196017a7a9047a741

The topic will be introduced by Jussi Jokinen from cognitive science, who has a general understanding of the interfaces between natural and artificial intelligence, and will be contextualised from the perspective of pedagogy and academia.

Learning cafe XVIII: AI - what is essential in future learning with machine learning? (10.5.2023)

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ChatGPT, Bard, Grammarly, DeepL, LLM, AI aka artificial intelligence, machine learning and neural networks - will AI be a blessing or a siren, a temptation or a curse to learning? How will AI change learning, the work of the researcher, and the work of the academic - or has already? What is AI based on? And what are the risks of AI for learning - and the opportunities? Does AI have the potential to be as big a revolution in knowledge and in learning work as it is predicted to be?

There are no sure answers to this hot and fresh topic - but often even good questions help to move forward and focus on the most relevant aspects. The essential - and interesting - question is, what can ultimately be automated - and what remains for humans? What are the work-life skills now, in 5 years or 10 years - and how should they be learned? How will the use of AI change what is required of graduates? What could we already automate now - with or without AI? For example, how does an AI-enabled email filter differ from self-adjusted email filters, and what are the advantages and disadvantages of manual filtering? What are some AI applications that are worth considering - or at least exploring - in your own IT work? What threats does AI pose, for example in terms of data privacy and security? And will AI finally be able to shape the Ultimate Question that fits the 42 answers? A staggering number of unanswered questions - not all of them yet answered.

The topic will be introduced by Jussi Jokinen from cognitive science, who has a general understanding of the interfaces between natural and artificial intelligence, and will be contextualised from the perspective of pedagogy and academia.

Contents:

Getting the basics correct: intelligence, artificial intelligence, machine learning, neural network, language model, natural and artificial intelligence, wisdom
Differences between natural and artificial intelligence; limitations, benefits, etc.
Case AI in education - opportunities, threats
Open questions; what we don't know yet; what needs to be studied; creative use of AI opportunities