AI Masterclass: Tools, Trade-offs, and Tough Questions (updated)

The AI Masterclass is fully booked.

Program

• 12:45 Walk-in

• 13:00 Introduction and AI-pitfalls by Theo van Mourik

• 13:45 workshop round 1

• 14:45 coffee break

• 15:00 workshop round 2

• 16:00 small group discussion on what you learned and how to apply it

• 16:30 Key note Mark Thompson: Going Local: From the Frontier to the Desktop and Back Again

• 17:00 End

• 1. Discussion: AI and environmental sustainability
  Perhaps you have heard the discourse on AI tools and their environmental impact, but how accurate is it? In this discussion session, we will discuss whether the environmental impact is communicated accurately, exaggerated or not emphasized enough. We will talk about what we know about the footprint of training, using, and energy / water consumption of Generative AI (GenAI) models. This can be a place to learn something new about the environmental footprint of GenAI, or to share your views if you already follow the topic closely.  The discussion does not have to be limited to environmental sustainability: there will be space to discuss more broadly about societal and human sustainability of GenAI as well. 
  
  This workshop will be led by a teaching-assistant of the Data science team of CIT.
  

• 2. Discussion: AI and Privacy
  Join this discussion session on AI privacy and security, designed to explore the real-world risks and responsibilities that come with using artificial intelligence. The session begins with a short presentation covering how the privacy risks surrounding AI during training and use, followed by security risks surrounding AI. We will then discuss why privacy is important followed by how you can ensure privacy on a user and university level. 
  
  This discussion will be led by a teaching-assistant of the Data science team of CIT accompanied by a privacy and security officer of the Digital Competence Center.
  

• 3. Discussion: AI and Data Autonomy
  As AI systems are becoming increasingly embedded in everyday tools and workflows, questions about who owns, controls and benefits from the underlying data are becoming harder to ignore. In an age where data means power, we invite you to this discussion session to explore the tensions between convenience and privacy and how we can protect our autonomy in a data economy. 
  
  This workshop will be led by a teaching-assistant of the Data science team of CIT.
  

• 4. Discussion: Ethical AI use in research
  Are you a researcher, or simply invested in the integrity of academic work? Join us for a discussion session exploring the ethical questions raised by AI tools in research. Together, we'll examine how these tools might reshape research quality, and whether the productivity gains from automation are worth the risks that come with them. Whether you're an enthusiastic user or a skeptic, this session invites a discussion about where AI and research ethics intersect.
  
  This discussion will be led by Anna Mikhaylovskaya.
  

• 5. Discussion: The state of agentic AI; will tools like Openclaw ever be safe enough for work?
  Agentic AI holds the promise of actually taking over a lot of work and doing tasks at your command. Composing a mail based upon your previous mail conversations with that person; booking a hotel based on your agenda using your credit-card information; finding that document on your hard drive you worked on recently for a company which name you cannot remember but rhymed with ravioli. 
  
  These are all tasks a dedicated and trusted personal assistant could do for you. But can we trust agentic AI? All the risks and concerns concerning AI apply to agentic AI even stronger. There are also new risks and concerns that only apply to agentic AI. Still many people dabble with this technology. In this discussion session you will discuss the current risks of agentic AI, trying to predict if agentic AI will ever be deemed safe enough for work.
  
  This discussion will be led by an employee of the Data science team of CIT.
  

• 6. Mini-workshop: Prompt-engineering
  During this workshop, you will discover how different types of prompting techniques for artificial intelligence (AI) tools can be a useful addition to your workflow. We will introduce different types of prompting, explore their strengths and limitations, and share best practices and optimal scenarios for using them. 
  
  Attend this workshop if you would like to improve your use of Generative AI models (GenAI). You are expected to have a basic understanding of (a) GenAI model(s) of your choice. 
  
  This workshop will be led by a teaching-assistant of the Data science team of CIT.

• 7. Mini-workshop: Design with AI
  During this workshop, you will discover how artificial intelligence (AI) can transform your design workflow. Whether you are designing a poster for your next team outing, creating diagrams for a presentation, or creating images for social media, AI tools can help you improve your results. We will introduce the AI design tools, explore their strengths and limitations, and share best practices for using them. We will focus on the tool Canva AI, and also briefly show Gamma and Napkin AI.
  
  Attend this workshop if you are interested in using AI for design-based tasks or wish to learn more about it. You are not expected to have any experience with niche design AI tools, but are expected to have basic experience with AI. 
  
  This workshop will be led by a teaching-assistant of the Data science team of CIT.
  

Prerequisites

If you would like to attend any discussion session, there are no prerequisites. You and your ideas are welcome, no matter the level! We find it is always best if there is a good balance of experts and beginners for the most flourishing discussion.

If you would like to attend:

• The Prompt Engineering, Design with AI or Coding with AI workshops, you are expected to have basic experience with Generative AI (GenAI) models.

_{This is a Research Support Hub workshop. The Research Support Hub is a CIT initiative to support all researchers and PhD-candidates throughout the University of Groningen on data management, geo-services, statistics, machine Learning, AI-tools and high performance computing.}