Category Archives: Linux

[$] A policy for Link tags

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The Git source-code management system stores a lot of information about
changes to code — but it does not hold everything that might be of interest
to a developer who needs to investigate a specific change in the future.
Commits in a repository are the end result of a (sometimes extended)
discussion; often, that discussion will result in changes to the code that
are not explained in the changelog. For some years now, many maintainers
have followed the convention of applying a Link tag to commits that points
back to the mailing-list posting of the change. Linus Torvalds has been
expressing his dislike for this convention for a while, though, and its
time appears to be coming to an end.

How FOSS Projects Handle Legal Takedown Requests (F-Droid)

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The F-Droid project has some
advice for free-software projects on how to deal with takedown
requests.

As part of our legal resilience research, we spoke with a range of
legal experts, software freedom advocates, and maintainers of
mature FOSS infrastructure to understand how others manage these
moments. In this article, we share what we learned, and how F-Droid
is incorporating these lessons into its own approach.

Promoting young people’s agency in the age of AI

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Part of teaching young people AI literacy skills is teaching them to critically think about AI, and to design AI applications that address problems they care about. How to do this was the focus of our June research seminar.

An educator helping a learner in the classroom

Working together to design AI

Our June research seminar was delivered by Netta Iivari, Professor in Information Systems at the University of Oulu’s INTERACT Research Unit.

The INTERACT research group focuses on understanding and supporting participatory design, user-centered design, user-driven innovation, and human interaction with technology in everyday life contexts. From this perspective, “users” aren’t considered as passive consumers, but as valuable co-creators and content producers. This calls for different approaches that place emphasis on empowerment and inclusion in designing, shaping, and co-creating information technology in everyday life.

As part of this work, Netta introduced the idea of ‘transformative agency’ — empowering children to believe they can solve problems they care about — and its application in secondary computing education. She showed examples of how to foster young people’s transformative agency within computing, specifically focusing on transdisciplinary approaches to learning about AI and inviting young people to critically analyse and design their futures with AI tools in it.

Netta began by giving an overview of two of the INTERACT Research Unit’s projects: 

  1. The Make a difference (MAD) project (2019–2023) explored critical design with young people, focusing on their emerging designer and maker identities in the context of tackling a significant societal problem — in this case, bullying. 
  2. Children’s transformative agency and emerging technologies for social good (TAKEOVER) (2024–2028), a current project, explores the potential of emerging technologies (artificial intelligence, virtual reality (VR), social robots, etc.) to address societal problems, such as climate change, gender equality, bullying, and discrimination. It focuses on children’s emerging transformative agency and activist identities when engaging with these tools and topics. 
An educator points to an image on a secondary learners computer screen.

Netta explained that these projects give young people an opportunity to begin to address the problems they care about, even though they may be very complex problems. From this problem-solving perspective, children are introduced (or ‘sensitised’) to emerging technologies as tools for social good.

She then went on to outline the key pedagogical approaches that underpin these projects:  

  1. Critical, ethical, empowering design
    This pedagogy draws on critical and speculative design traditions in design research and encourages young people to take a critical perspective towards society, its norms, and the status quo, as part of design thinking. Children consider the ethical values and consequences of their designs. They begin to experience the ways in which engaging in the design process can be empowering and transformative for them, collectively as well as individually. 
  2. Transformative agency of children
    This approach encourages young people to consider their capacity to have agency in the world, by enabling them to envision change and commit to taking action to solve problems that they care about. 
  3. Fostering transformative agency of children in the age of AI
    Transformative agency is achieved when young people engage in ‘expansive learning’ — when they learn something novel, together, and are encouraged to look beyond the confines of school work, the topic, themselves, and the tools available for solving the problem. This approach fosters an active, critical, reflective mindset that encourages children to believe that they can make change and have impact in the world. 

The project design process

The projects follow 3 design phases and include a range of plugged and unplugged activities, as shown in Figure 1.

Figure 1. The project phases

Netta then described in more detail some of the activities that have been used to address these different project phases and the design process involved. For example, to explore what are the problems that children really care about, they are asked to imagine ‘carrying a stone in your pocket for one week, as if it was a magic tool. Where could it be used in your everyday life? What problems could it solve? What problems would you like it to solve and how?’ 

Young people are then introduced to a range of novel technologies, for example, VR headsets, robots, and emulators of AI-driven social media platforms, such as “Somekone”, developed as part of the Generative AI project at the University of Eastern Finland. They deconstruct and reconstruct generative AI tools by prompting large language model chatbots such as ChatGPT, Gemini, Claude, etc. and exploring bias in their outputs. They perform small-scale algorithmic auditing and create mini language models (with Google Colab), using the text in Alice in Wonderland to train their models, and then open datasets (books as text files from Project Gutenberg). In exploring the responses generated, they experience the potential and the limitations of such tools and gain an important understanding of the human activity involved in the development of AI technologies. 

Secondary school age learners in a computing classroom.

Once they have had this ‘sensitising‘ exposure to a range of tools, they then work in groups on a project that makes use of AI to solve the societal problem they have chosen. These problems could encompass a range of topics, such as racism, animal rights, the impact of AI, war, mental health, bullying. The young people are prompted to think about how large language models can be used to solve the problem, or parts of the problem. But importantly, they are also asked to consider the different motives and perspectives of the multiple stakeholders involved in the problem and its solution and whether their model ideas will create new problems when deployed.

They follow the 3 project phases shown in Figure 1 to design and make a range of digital (robots, apps, videos) and non-digital artefacts to solve their problem. Netta emphasised that although it could take 10 weeks or more to implement all the suggested activities, it is also possible to pick and choose individual tasks from the 3 phases to suit available curriculum timescales.

Envisioning and critiquing AI futures

Other project tasks involve: 

  • Envisioning AI futures by imagining that a miracle has happened overnight and the problem has disappeared — what is the result? 
  • Critiquing AI futures by creating best and worst case scenarios of the consequences of the AI systems they design, creating video adverts promoting their AI solutions and anti-adverts, focusing on the possible negative consequences of their prototypes 
  • Fostering action-taking by presenting theatrical performances to showcase how their designs tackle a problem and illustrating the AI-related issues surrounding the topic or by creating activism campaign material to mobilise the school community on the same themes 
Secondary education learners in the classroom

These projects situate learning about data-driven technologies in real-world contexts and promote a transdisciplinary approach, teaching and learning about AI from a problem-solving perspective. 

This perspective conveys important messages to young people — that they do have agency and can take action in the face of many of the world’s problems, that they can and should be active, critical users of the new technologies that surround them, and that these technologies can be used to change the world for good. 

Netta ended the seminar by asking viewers to consider how they could foster transformative agency in the young people they teach and whether or not they consider it to be important in computing education.

Resources relating to the projects can be found at interact.oulu.fi.

Join our next seminar

In our current seminar series, we’re exploring teaching about AI and data science. Join us at our next seminar on Tuesday 14 October from 17:00 to 18:30 GMT to hear Viktoriya Olari talk about data-related concepts and practices for AI education in K–12.

To sign up and take part, click the button below. We’ll then send you information about joining. We hope to see you there.

The schedule of our upcoming seminars is online. You can catch up on past seminars on our previous seminars page.

The post Promoting young people’s agency in the age of AI appeared first on Raspberry Pi Foundation.

AMD EPYC 9575F CPUs For GPU/AI Servers Show Leading Performance In Benchmarks

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Since the launch of the AMD EPYC 9005 series nearly one year ago, I have performed hundreds of different benchmarks on these EPYC “Turin” processors across a wide range of workloads/disciplines to really terrific performance, power efficiency, and value. AMD EPYC 9005 performs exceptionally well compared to the competition from Intel and ARM CPU vendors. One area though I hadn’t explored to this point was how well the AMD EPYC 9005 series performs for serving as the host CPU for GPU/AI servers. That changed as I recently wrapped up some benchmarks exploring that area using the AMD EPYC 9575F and it managed to accelerate past the available competition in proving capable of being the superior host processor for AI servers.

Wireshark 4.4.9 Protocol Analyzer Released with Updated Protocols and Bug Fixes

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Wireshark 4.4.9 has been released today as the ninth maintenance update to the latest Wireshark 4.4 stable series of this popular, open-source, free, and cross-platform network protocol analyzer software for Linux, macOS, and Windows systems.

The post Wireshark 4.4.9 Protocol Analyzer Released with Updated Protocols and Bug Fixes appeared first on Linux Today.