camp2023-57139-eng-Free_Software_opus.srt

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 [MUSIC]

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 [MUSIC]

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 All right, welcome everybody.

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 Day three, first talk on the Bits and Bombers stage.

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 How's everybody doing?

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 [APPLAUSE]

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 Yes, still a bit tired, but we have nice weather today, not too much sun,

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 so you can fully enjoy the talk by Joseph Devo Geis.

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 He will talk briefly for about 25 minutes on the impact of software

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 on energy and resource consumption and give us an overview of the environmental harm

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 and the potentials for savings there and how free software in special

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 is well positioned to address the issue.

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 And in the end, we will have a Q&A session.

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 And, yeah, if you have any questions, you can raise your hands,

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 and we will get a mic to you.

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 So give Joseph a warm round of applause again and enjoy the talk.

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 [APPLAUSE]

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 Yeah, thank you. Thank you very much.

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 Thank you to the organizers at Bits and Bomber.

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 This has been great so far.

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 So the title of my talk today is Free Software, Software Design for the Environment.

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 And this is part of a larger KDE eco-initiative

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 working on sustainability issues in KDE and free software.

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 Before I get started, though, I like to make my talks a little bit interactive.

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 Feel free, if when I'm talking you have a question that's burning

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 and you want to ask it right away, you can just raise your hand,

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 and either the mic will come to you or I can repeat it for the audience.

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 Before we get started, though, I wanted to ask you,

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 what are some words and phrases that you associate with free software?

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 And I'll repeat here for the people who are online.

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 Great.

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 Great, yeah, good.

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 Empowerment.

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 Empowerment.

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 Powerful.

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 Say it again.

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 Powerful.

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 Powerful.

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 Customizable.

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 Customizable.

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 Collaboration.

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 Collaboration.

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 Collaboration.

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 Great.

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 Sustainable.

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 Sustainable.

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 So most people don't say sustainable,

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 and I hope by the end of this talk all of you,

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 next time someone asks you that question, will say sustainable.

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 I have many links in the slides.

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 If you want to download them, they're available at our repository.

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 I will also return to the slide if you remind me at the end of the talk.

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 Just wait a second.

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 Great.

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 So to get started, just to frame the issue that we're talking about.

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 So this is a post on Macedon from Ed Hawkins.

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 He's a climate scientist at the University of Reading,

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 in which he has a graph.

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 I don't expect you can really see the graph,

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 but I hope you can see that all but one have an upward slope to it.

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 Okay?

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 You can probably guess what these are measurements of.

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 This is the global temperature, CO2 emissions, sea levels.

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 There's only one that's going down.

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 That's the ice thickness.

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 And he writes in the post,

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 "Changes are emerging across the climate system.

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 Everywhere we look, the climate is changing rapidly.

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 These changes are not normal.

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 They're caused by the burning of fossil fuels."

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 Fossil fuels are also being burned in the ICT sector.

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 So information and communications technology is right now an area

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 that's being researched to figure out how much energy is consumed

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 and how much the ICT sector contributes to CO2 emissions.

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 This is a graph, again, all having upward slopes,

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 which is a meta study looking at various research papers

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 trying to estimate what the CO2 emissions are of the ICT sector.

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 One thing I want to point out here is that the estimates vary.

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 You can see some grow exponentially, some grow linearly.

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 However, they're all growing.

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 And if you take it, sort of try to average over what all of the studies seem to show,

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 it appears that ICT sector contributes between 2 and 4 percent of CO2 emissions globally.

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 To put that into perspective,

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 that's roughly the equivalent of the global aviation industry,

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 which is estimated around 2.5 percent.

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 This analysis for the ICT sector includes everything

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 from production, transportation, end-of-life treatment of devices,

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 to energy consumption of the Internet,

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 to energy consumption driven by the software you're running at home or in your office.

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 Also includes Bitcoin, machine learning, training, etc.

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 Right now, the current trajectory, if you look here as well as here,

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 if things don't change, it's going to continue growing.

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 And some estimates put that up to about 30 percent of global CO2 emissions by 2050.

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 So it's growing. It's increasing rapidly.

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 One thing I want to point out here, and I like this quote from this,

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 it's a tech brief from the Association of Computing Machinery,

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 computing can help mitigate climate change.

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 How? By substituting other activities that we're doing.

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 But it must first cease contributing to it,

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 because it's growing in some cases faster than it's substituting.

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 I'm going to focus today in this talk on the different ways

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 that software is driving energy consumption specifically.

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 Of course, energy consumption does contribute to CO2,

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 depending on what the power grid mix is.

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 I'm not going to talk too much about estimates of CO2.

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 I'm going to talk specifically about power consumption,

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 as well as production costs.

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 I'm going to do that in two different ways.

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 I'm going to talk about efficiency, energy efficiency,

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 in terms of achieving the same result when doing the same task,

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 but consuming less energy, as well as conservation,

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 that is reducing the waste that's driven by software.

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 And let's look at some examples of this.

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 First, in terms of efficiency.

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 This is a comparison of two word processors.

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 It's from the Umweltbundesamt.

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 It's some research done by the Umweltkampus Birkenfeld,

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 in which they compared various software products doing the same thing,

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 and then looking at their energy consumption differences.

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 Word processor one, the green bar plot,

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 is a free and open source software product.

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 They don't mention which one.

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 The blue one is a proprietary one.

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 Again, they don't mention which one.

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 And as you can see here, to do the exact same thing,

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 to achieve the same result,

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 word processor two consumes about four times the energy.

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 Okay, for an individual, this may not make much of a difference.

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 But you can't think of software's energy consumption on an individual basis.

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 Word processors are in every office, in every university,

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 on everyone's computer.

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 People are using it globally all the time.

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 If you think about these numbers when you scale it up,

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 they add up very quickly.

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 And to give an example of that,

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 this is from a talk from Hasso Plattner Institute, Detlef Thoms,

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 in which he does a back-of-the-envelope calculation,

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 in which you reduce a process by one CPU second.

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 Okay, it's a very minimal change.

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 That's about the equivalent of a savings of 10 watt seconds.

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 And if you multiply that by 1.5 million users,

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 now that's not very many users,

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 and you assume that there are 20 such reductions a day,

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 so this reduction in the CPU usage happens 20 times a day,

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 and you multiply that by 230 working days a year,

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 you end up with 19 megawatt hours of savings.

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 Now, if you're like me, that doesn't mean much to you.

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 To put that into perspective,

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 if you take a modern electric vehicle

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 and drive it back and forth from Shanghai six times,

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 that's about the equivalent of 19 megawatt hours.

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 Okay, so these are very simple changes

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 that result in big savings once you scale it up.

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 And the thing about software is that you're not only changing on one computer,

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 but you're changing every computer that gets that update, right?

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 And when you think about it on a global level,

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 these savings really add up very quickly.

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 If I can convince just 500 developers--

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 and I've been giving similar talks now for about a year and a half,

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 so this is a very realistic goal--

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 500 developers to try to achieve just 10 of those efficiency gains,

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 multiply that by 19 megawatt hour savings,

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 and you're talking about the energy consumption

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 of 30,000 two-person households in one year.

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 So scaling it up, you get to really big efficiency gains.

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 Okay, now conservation.

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 Reducing the waste.

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 And when we're talking about waste,

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 let's start where the waste lands in the landfill.

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 And this is a graph--infographic representing the e-waste from 2016.

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 Already one year before that,

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 Akim Steiner from the UN commented that there's a tsunami of e-waste

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 rolling out over the world.

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 In 2015, there was 44.7 million tons of e-waste produced.

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 That's about the equivalent of 4,500 Eiffel Towers.

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 If you were to stack those Eiffel Towers,

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 it would be about 17 times Mount Everest high.

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 Okay, this is in one year, and it's growing.

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 In 2019, the World Economic Forum said

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 that e-waste is the fastest growing waste stream in the world.

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 In 2022, 60 million tons of e-waste, a 33% increase.

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 Of that e-waste, about 20% is estimated to be recycled.

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 And in what ends up in the landfill,

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 although e-waste accounts for about 2% of the total waste,

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 it's 70% of the toxic waste.

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 What does software have to do with e-waste, right?

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 So, e-waste is hardware.

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 Software can drive e-waste.

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 Some of you may have had this warning message

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 that your device is no longer supported.

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 If your software is tied to that device,

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 then that device becomes unusable,

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 at least not without serious disadvantages to you as a user.

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 The software might become more and more bloated

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 as more features are added,

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 and the energy that's consumed

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 or the processing power that's needed by the hardware

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 is so much that older hardware can no longer support that software.

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 As a result, what you have is devices that are now produced

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 and transported unnecessarily,

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 and functioning devices end up as e-waste in the landfill.

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 This is particularly problematic,

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 thinking about it in terms of CO2.

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 This is a graph from a book from Lange and Santorius

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 called "Smarta Kuhn-U-Neveld".

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 This is data from Apple's own sustainability reports

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 from an iPhone in which they estimate

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 how much CO2 is produced per device

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 and then what it's attributable to.

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 They find, Apple reports, that the production,

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 end-of-life treatment and transportation

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 accounts for about 80% of the CO2 emissions of a device.

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 So, sending a device into the landfill before its time

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 is a huge waste of resources.

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 So, to me, they're both the same thing, right?

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 I mean, if the hardware doesn't allow the software,

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 it's because the software can't function on that hardware.

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 So, what could the hardware vendors

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 where to open or provide support?

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 Right, okay, so the question is,

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 so things like bootloaders being proprietary

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 and then not allowing devices to then run other software, right?

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 That's a design decision.

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 That's maybe not directly a software in the sense of...

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 It is a software decision because that's proprietary.

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 You can't then access the device.

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 So, I would say, I mean, software and hardware,

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 those are the...what you're describing,

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 so the question was about when the hardware is so locked down

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 that you can't install other software on it.

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 And that's a situation where you have a device

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 that's tied to one particular software product, right?

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 But that's a design decision and it's still related to software.

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 And I would say we should all be fighting

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 for the right to repair, to include software,

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 including things like opening up bootloaders

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 so that you can install other software products on it.

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 So, yeah, production and end-of-life treatment

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 and transportation are going to contribute

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 to much of the CO2 emissions of a device.

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 But it's not only CO2 emissions.

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 The end-of-life treatment also contributes

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 to polluting air, soil, et cetera,

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 often in countries in the global south,

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 both where the devices are...the metals are mined,

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 often under horrible conditions,

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 and then they return there to then end up

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 in treatment centers or in landfills.

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 This here is in Ghana.

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 So, I mentioned at the beginning that there are cases

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 where digitization can substitute other activities,

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 and one of the questions there is is,

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 what is the relative harm difference

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 between the digital product and the non-digital one?

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 This is, again, from Lange and Centorious.

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 It's a comparison of e-readers

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 in terms of their environmental harm and books, paper books.

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 Paper book production also contributes

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 to environmental harm in terms of polluting water and soil

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 with the chemicals used to create the paper.

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 And the production of an e-reader contributes also

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 to environmental harm in terms of the different materials

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 that go into it, often toxic.

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 Per device, 300 liters of water are required,

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 and one estimate has CO2 emissions

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 at 170 kilograms per device.

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 And Lange and Centorious estimate that if you read

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 about 30 to 60 paper books or more,

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 at that point, the environmental harm,

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 it's worth getting the e-reader

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 from what you're contributing.

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 This is one estimate. These are very hard estimates to make.

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 The point being that these are things

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 that you have to consider.

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 Substitution is not in itself always better.

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 In the case of e-readers, statistics about how many books

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 people read per year in comparison

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 to how long devices are supported.

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 So one Wikipedia article had the start date

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 and end date for production of e-readers

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 as 1.5 years on average.

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 The average US-American reads 60% read less than five books per year.

283
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 So to get to the number of 30 to 60,

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 it's going to require using that device for a long time,

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 which likely won't be the case given the short-term lifespan

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 of these devices.

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 So one of the things I want to point out there in those parts

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 is software design in terms of the energy consumption,

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 as well as its support for hardware,

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 can influence the environmental harm of the ICT sector.

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 And this was the motivation for eco-certifying software.

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 Many people ask, well, what does software have to do with eco-certification?

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 That's what I'm going to talk about now.

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 The Blue Angel released the award criteria for software in 2020.

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 The award criteria are aligned with FOSS values of transparency

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 and user autonomy.

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 And there are three main categories to the award criteria--

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 resource and energy efficiency,

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 potential hardware operating life, and user autonomy.

300
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 Just to get an overview before I focus on some of the user autonomy characteristics,

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 which are inherent to software license with a free software license.

302
00:17:21,000 --> 00:17:25,000
 Before we get there, though, let's look at some of the different criteria--

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 resource and energy efficiency--that's related to the energy consumption of software.

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 The criteria don't have a threshold, but rather a transparency requirement

305
00:17:35,000 --> 00:17:39,000
 so that users are aware of how much energy this software consumes

306
00:17:39,000 --> 00:17:42,000
 when running typical tasks.

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 Potential hardware operating life--

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00:17:44,000 --> 00:17:47,000
 the requirements are that it runs on hardware at least five years old.

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 I think this is a little too low,

310
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 especially given that many Linux distributions run on hardware much older than that.

311
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 And the user autonomy requirements include things like uninstallability,

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00:17:59,000 --> 00:18:05,000
 modularity, which influences the sort of software feature creep and bloat,

313
00:18:05,000 --> 00:18:08,000
 continuity of support, documentation,

314
00:18:08,000 --> 00:18:12,000
 so that there's long-term reuse and repairability of software,

315
00:18:12,000 --> 00:18:16,000
 transparency so that users can decide which software products to use

316
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 so you're not locked into an inefficient program,

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 as well as offline capability and freedom from advertising,

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 both of which consume energy.

319
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 Just some background, the Blue Angel Oculus from KDE

320
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 is the first Blue Angel certified software.

321
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 Currently, it's the only one.

322
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 I hope to convince at least some people that it's worth at least meeting

323
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 the award criteria if you're interested in the topic

324
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 or considering applying for ECO certification.

325
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 So here, getting to the characteristics about free and open source software

326
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 and how it relates to energy efficiency and resource consumption.

327
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 So looking at the criteria,

328
00:18:57,000 --> 00:19:02,000
 it's hard to single out a single one when it comes to the topics of efficiency and conservation.

329
00:19:02,000 --> 00:19:04,000
 They're all interrelated.

330
00:19:04,000 --> 00:19:08,000
 But here, I want to focus on a couple of them together in three different parts.

331
00:19:08,000 --> 00:19:12,000
 So first, I want to look at the energy consumption and hardware performance

332
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 related to uninstallability and modularity,

333
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 and perhaps related to offline capability and freedom from advertising.

334
00:19:21,000 --> 00:19:24,000
 So we take it for granted in the free and open source software community

335
00:19:24,000 --> 00:19:27,000
 that you can uninstall software.

336
00:19:27,000 --> 00:19:29,000
 This is something that is obvious to us,

337
00:19:29,000 --> 00:19:34,000
 and many of us probably have never thought about that in terms of efficiency gains.

338
00:19:34,000 --> 00:19:38,000
 But unwanted software components that remain on a system

339
00:19:38,000 --> 00:19:43,000
 contribute to longer boot-up times, longer shutdown times,

340
00:19:43,000 --> 00:19:47,000
 perhaps extra processes running when you're using that software, et cetera.

341
00:19:47,000 --> 00:19:51,000
 All of which, if you go back to the one CPU second reduction,

342
00:19:51,000 --> 00:19:56,000
 all of which adds up when you multiply that over millions of users.

343
00:19:56,000 --> 00:20:03,000
 So uninstallability is a way to create a more efficient system.

344
00:20:03,000 --> 00:20:08,000
 Again, going back to this graph comparing the two different word processors,

345
00:20:08,000 --> 00:20:12,000
 if you want to take a deeper look at what the energy consumption looks like over time,

346
00:20:12,000 --> 00:20:15,000
 here's a plot, again, from that same measurement,

347
00:20:15,000 --> 00:20:20,000
 looking at the word processor, the open source word processor,

348
00:20:20,000 --> 00:20:24,000
 which is on the bottom plot in comparison to the proprietary word processor,

349
00:20:24,000 --> 00:20:26,000
 which is on the top plot.

350
00:20:26,000 --> 00:20:31,000
 And what you can see here is doing the exact same thing.

351
00:20:31,000 --> 00:20:33,000
 They have very different energy profiles.

352
00:20:33,000 --> 00:20:37,000
 The x-axis is showing over time while running different tasks,

353
00:20:37,000 --> 00:20:42,000
 things like opening a document, changing the layout, and then saving the document.

354
00:20:42,000 --> 00:20:46,000
 And I want to focus here on what happens after that blue line.

355
00:20:46,000 --> 00:20:52,000
 That's the point at which the document is saved and the software goes idle.

356
00:20:52,000 --> 00:20:56,000
 And what you can see here is that the proprietary software

357
00:20:56,000 --> 00:20:58,000
 continues doing things in the background.

358
00:20:58,000 --> 00:21:01,000
 It does it quite a bit, actually.

359
00:21:01,000 --> 00:21:08,000
 And in comparison, the free and open source software product goes idle as you would expect.

360
00:21:08,000 --> 00:21:13,000
 The report doesn't say what exactly is happening in this time period.

361
00:21:13,000 --> 00:21:19,000
 There is also measurements in this approach where they're looking at network traffic,

362
00:21:19,000 --> 00:21:22,000
 writing to disk, etc.

363
00:21:22,000 --> 00:21:26,000
 That data is not in the report, so I don't know what's happening here.

364
00:21:26,000 --> 00:21:30,000
 It might be telemetry.

365
00:21:30,000 --> 00:21:34,000
 I think that's a reasonable guess.

366
00:21:34,000 --> 00:21:37,000
 If it's proprietary software, you can't turn this off necessarily

367
00:21:37,000 --> 00:21:40,000
 unless the company decides that you're allowed to.

368
00:21:40,000 --> 00:21:42,000
 If this is free and open source software,

369
00:21:42,000 --> 00:21:45,000
 developers can then take a look, see what it's doing,

370
00:21:45,000 --> 00:21:50,000
 and then decide to remove this functionality if users don't want it.

371
00:21:50,000 --> 00:21:57,000
 All of this is contributing to that energy profile of these two word programs.

372
00:21:57,000 --> 00:22:03,000
 So, again, yeah, just that this adds up when you start thinking about it,

373
00:22:03,000 --> 00:22:09,000
 scaling it up across millions or billions of users.

374
00:22:09,000 --> 00:22:14,000
 Okay, the next topic, so potential hardware operating life,

375
00:22:14,000 --> 00:22:16,000
 as well as continuity of support,

376
00:22:16,000 --> 00:22:20,000
 which is what determines how long you can use that device

377
00:22:20,000 --> 00:22:25,000
 and not have disadvantages opening yourself up to malware and things like this,

378
00:22:25,000 --> 00:22:28,000
 known malware, documentation,

379
00:22:28,000 --> 00:22:31,000
 how long can that software be supported over time,

380
00:22:31,000 --> 00:22:35,000
 will depend to some extent on how well it's documented,

381
00:22:35,000 --> 00:22:40,000
 transparency that users can decide which software they want to use

382
00:22:40,000 --> 00:22:44,000
 and then move to different software products if they want to.

383
00:22:44,000 --> 00:22:49,000
 And this will all influence how long you can continue to use a particular piece of hardware.

384
00:22:49,000 --> 00:22:56,000
 This is an image from a 2009 Macbook.

385
00:22:56,000 --> 00:23:02,000
 This end of life was in 2019 where it was no longer supported by Apple.

386
00:23:02,000 --> 00:23:08,000
 And so the last version of MacOS that was supported was 1010.

387
00:23:08,000 --> 00:23:12,000
 This is from a KDE contributor who was asking around

388
00:23:12,000 --> 00:23:18,000
 if KDE users were using hardware that was no longer supported by the original vendors.

389
00:23:18,000 --> 00:23:21,000
 This is now currently still in use today,

390
00:23:21,000 --> 00:23:26,000
 running Kabuntu 22.04 with all of the security updates, et cetera,

391
00:23:26,000 --> 00:23:29,000
 and is apparently working just fine.

392
00:23:29,000 --> 00:23:31,000
 I know I have this experience.

393
00:23:31,000 --> 00:23:35,000
 I'm running also older hardware at home on my desktop computer,

394
00:23:35,000 --> 00:23:39,000
 which is no longer supported running Linux.

395
00:23:39,000 --> 00:23:47,000
 This device would otherwise end up in the closet or perhaps worst case

396
00:23:47,000 --> 00:23:50,000
 where it doesn't end up being treated or it goes to end of life treatment center

397
00:23:50,000 --> 00:23:58,000
 and all of that CO2 that is associated with the production has now been wasted.

398
00:24:02,000 --> 00:24:11,000
 Okay, and the last section that I want to talk about in terms of the user autonomy criteria

399
00:24:11,000 --> 00:24:16,000
 is the offline capability and freedom from advertising.

400
00:24:16,000 --> 00:24:23,000
 This is a report from a research and consultancy group

401
00:24:23,000 --> 00:24:26,000
 which does policy reports for the EU

402
00:24:26,000 --> 00:24:30,000
 in which they looked at what is called unwanted data use.

403
00:24:30,000 --> 00:24:38,000
 And they define unwanted data use as the data for data mining and advertising

404
00:24:38,000 --> 00:24:40,000
 that users can't shut off.

405
00:24:40,000 --> 00:24:48,000
 Given a statistic that in the EU, about 60% of users would shut it off if they could.

406
00:24:48,000 --> 00:24:50,000
 So they call this unwanted data use.

407
00:24:50,000 --> 00:24:54,000
 And they try to estimate what the energy consumption and CO2 emissions are

408
00:24:54,000 --> 00:24:57,000
 associated with that unwanted data use.

409
00:24:57,000 --> 00:25:02,000
 This graph here is just showing that there are several components to energy consumption.

410
00:25:02,000 --> 00:25:04,000
 I've been focusing on desktop software.

411
00:25:04,000 --> 00:25:07,000
 That's most of what KDE does.

412
00:25:07,000 --> 00:25:10,000
 But of course, if you're doing anything that's distributed,

413
00:25:10,000 --> 00:25:13,000
 client server or similar type systems,

414
00:25:13,000 --> 00:25:18,000
 you're also going to be consuming energy in the network and in data centers.

415
00:25:18,000 --> 00:25:28,000
 And this unwanted data use is at best attributable to about 3 million metric tons of CO2,

416
00:25:28,000 --> 00:25:33,000
 according to this report, at worst 8 million metric tons.

417
00:25:33,000 --> 00:25:38,000
 And this would be, according to this report, equal to the carbon footprint

418
00:25:38,000 --> 00:25:43,000
 of about 370,000 to 950,000 EU citizens.

419
00:25:43,000 --> 00:25:47,000
 This is for something people don't want.

420
00:25:47,000 --> 00:25:52,000
 So the blue angel recognizes that if users can turn it off when they want,

421
00:25:52,000 --> 00:25:57,000
 you remove this energy consumption from the ICT contributions

422
00:25:57,000 --> 00:26:02,000
 to energy consumption and CO2 emissions.

423
00:26:02,000 --> 00:26:05,000
 Of course, these things are all intertwined.

424
00:26:05,000 --> 00:26:11,000
 Things like advertising and data mining, et cetera,

425
00:26:11,000 --> 00:26:17,000
 might also make it hard to run a browser on an old piece of hardware.

426
00:26:17,000 --> 00:26:21,000
 In fact, I find one of the biggest problems when upcycling hardware

427
00:26:21,000 --> 00:26:26,000
 is opening a browser the minute you try to do anything on the internet.

428
00:26:26,000 --> 00:26:35,000
 Currently, website design is so energy consuming that it can break your system.

429
00:26:35,000 --> 00:26:40,000
 That's related to Roberta's great talk yesterday.

430
00:26:40,000 --> 00:26:43,000
 So these things are, of course, interrelated.

431
00:26:43,000 --> 00:26:50,000
 Offline capability for your advertising will influence how long you can run hardware, et cetera.

432
00:26:50,000 --> 00:26:58,000
 So we wanted to document our experience applying for the blue angel eco-certification

433
00:26:58,000 --> 00:27:02,000
 so that other free and open source software developers can also do this.

434
00:27:02,000 --> 00:27:10,000
 We released a handbook in February this year, Applying the Blue Angel Criteria to Free Software.

435
00:27:10,000 --> 00:27:15,000
 You're welcome to download it from our website, eco.kde.org.

436
00:27:15,000 --> 00:27:23,000
 The book goes over what I'm calling the three steps to eco-certification, measuring your software.

437
00:27:23,000 --> 00:27:28,000
 So to do that, you need to define what typical usage of that software would look like,

438
00:27:28,000 --> 00:27:33,000
 emulate it using a script, which is all documented in this handbook,

439
00:27:33,000 --> 00:27:37,000
 and then run it several times, run some statistical analyses,

440
00:27:37,000 --> 00:27:41,000
 which you can do with a tool provided by the Unveiled Compass called Oscar,

441
00:27:41,000 --> 00:27:44,000
 the open source software consumption analysis in R.

442
00:27:44,000 --> 00:27:54,000
 And once you have that, you document your user autonomy criteria that you're compatible with them and submit it.

443
00:27:54,000 --> 00:27:56,000
 The book, though, is more than that.

444
00:27:56,000 --> 00:28:00,000
 It's something that you can send to your friends if you're interested in this,

445
00:28:00,000 --> 00:28:03,000
 send it to your marketing department if you work at a company,

446
00:28:03,000 --> 00:28:06,000
 send to your project manager if you're on a team,

447
00:28:06,000 --> 00:28:10,000
 in which it goes over various aspects of this topic.

448
00:28:10,000 --> 00:28:13,000
 The first part is the why. Why does this matter?

449
00:28:13,000 --> 00:28:17,000
 So related to energy consumption, resource consumption driven by software.

450
00:28:17,000 --> 00:28:23,000
 What is the blue angel? What's its history?

451
00:28:23,000 --> 00:28:28,000
 How is it recognized internationally as well as in Germany?

452
00:28:28,000 --> 00:28:33,000
 And then how do you fulfill then the requirement for software?

453
00:28:33,000 --> 00:28:38,000
 You can also read it online here.

454
00:28:38,000 --> 00:28:44,000
 For those of you who are interested in this but don't have access to a power meter,

455
00:28:44,000 --> 00:28:46,000
 power meters are...

456
00:28:46,000 --> 00:28:49,000
 So the approach that the blue angel recommends and the one that we're using in our lab

457
00:28:49,000 --> 00:28:56,000
 is an external power meter attached to a machine that then is emulating user behavior.

458
00:28:56,000 --> 00:28:59,000
 Power meters are expensive.

459
00:28:59,000 --> 00:29:02,000
 Really good power meters are really expensive.

460
00:29:02,000 --> 00:29:08,000
 The off-the-shelf solutions, which are okay, they don't have great resolution.

461
00:29:08,000 --> 00:29:14,000
 The one that is recommended, the Guta power meter, gets like five measurements per second,

462
00:29:14,000 --> 00:29:17,000
 which you can then average and get an idea of what's happening.

463
00:29:17,000 --> 00:29:22,000
 Better ones can get like a thousand measurements per second.

464
00:29:22,000 --> 00:29:26,000
 However, you're going to be out of three to four hundred euros to buy one.

465
00:29:26,000 --> 00:29:31,000
 If you're interested in just checking this out but don't have five hundred euros,

466
00:29:31,000 --> 00:29:37,000
 you can invest ten euros and buy a power plug and hack it and turn it into a power meter

467
00:29:37,000 --> 00:29:41,000
 that gets about one measurement for every 200 milliseconds.

468
00:29:41,000 --> 00:29:47,000
 And that's also documented in this.

469
00:29:47,000 --> 00:29:53,000
 Say it again.

470
00:29:53,000 --> 00:29:59,000
 I don't know.

471
00:29:59,000 --> 00:30:01,000
 Can we ask that at the end?

472
00:30:01,000 --> 00:30:03,000
 Because I also wanted to open up...

473
00:30:03,000 --> 00:30:05,000
 I usually like to do Q&A where also other people in the crowd,

474
00:30:05,000 --> 00:30:09,000
 because I don't have a monopoly on this information at all.

475
00:30:09,000 --> 00:30:15,000
 So if someone here might know the answer to that but I don't know it, ask it again in the Q&A.

476
00:30:15,000 --> 00:30:17,000
 The lab setup looks like this.

477
00:30:17,000 --> 00:30:20,000
 You have a system under test. That's the machine that you're testing.

478
00:30:20,000 --> 00:30:24,000
 A power meter attached to it and then another computer that's then collecting the data

479
00:30:24,000 --> 00:30:29,000
 and then used to evaluate it.

480
00:30:29,000 --> 00:30:33,000
 We set up a lab in KDAB Berlin.

481
00:30:33,000 --> 00:30:38,000
 This is a picture of one of the sprints.

482
00:30:38,000 --> 00:30:45,000
 This is Arna Tarara from Green Coding Berlin who was very helpful with Folker Kausa,

483
00:30:45,000 --> 00:30:53,000
 Nicholas Fela and several others in the KDAB community who helped us get this lab setup.

484
00:30:53,000 --> 00:30:59,000
 The current setup is only accessible if someone is there in person.

485
00:30:59,000 --> 00:31:02,000
 We're working on that. I'm going to come back to those slides.

486
00:31:02,000 --> 00:31:06,000
 Right now in a project which should be done by next month

487
00:31:06,000 --> 00:31:10,000
 in which we are making the lab remotely accessible so that a developer,

488
00:31:10,000 --> 00:31:13,000
 and we want to open this up to all free software developers,

489
00:31:13,000 --> 00:31:20,000
 this is not only a KDE thing, can design their usage scenario that they want to measure,

490
00:31:20,000 --> 00:31:25,000
 upload it with their code and then it will automatically run in the lab in KDAB

491
00:31:25,000 --> 00:31:30,000
 and then give you a report back so that all you have to do is define the usage scenario

492
00:31:30,000 --> 00:31:35,000
 and then you get some energy consumption measurements related to your software.

493
00:31:35,000 --> 00:31:46,000
 And of course all of this is KDE free software so anyone can take it, adapt it to their needs as they see fit.

494
00:31:46,000 --> 00:31:50,000
 What you would need to do if you wanted to use a lab like this,

495
00:31:50,000 --> 00:31:57,000
 you have to define a standard usage scenario that requires identifying typical tasks done by a user,

496
00:31:57,000 --> 00:32:03,000
 perhaps identify particularly the high energy ones to get an idea of energy consumption related to that,

497
00:32:03,000 --> 00:32:06,000
 create a flowchart of actions and then emulate it.

498
00:32:06,000 --> 00:32:08,000
 There are many ways to emulate it.

499
00:32:08,000 --> 00:32:17,000
 Right now KDE is focused on using Selenium, which is often used for web emulation,

500
00:32:17,000 --> 00:32:23,000
 adapting that for desktop software.

501
00:32:23,000 --> 00:32:28,000
 There were several talks at Academy just a few weeks ago which you can watch about this approach,

502
00:32:28,000 --> 00:32:32,000
 but it's also useful for user emulation.

503
00:32:32,000 --> 00:32:38,000
 Once you have that, then you upload it to the machine you want to test,

504
00:32:38,000 --> 00:32:45,000
 you get the results back and then there's this tool, Oscar, where you can then upload the data and get a report back.

505
00:32:45,000 --> 00:32:52,000
 The nice thing is that with this lab set up with a remote access, all of that's automated.

506
00:32:52,000 --> 00:32:58,000
 Just a little bit more generally, KDE has a current goal of sustainable software.

507
00:32:58,000 --> 00:33:03,000
 Every two years we vote on three unifying goals for the community.

508
00:33:03,000 --> 00:33:06,000
 One of the things that we're working on is measuring our software,

509
00:33:06,000 --> 00:33:09,000
 but there are several other things related to this,

510
00:33:09,000 --> 00:33:19,000
 such as documentation of the ways that free software, in particular our software at KDE, supports sustainability.

511
00:33:19,000 --> 00:33:25,000
 Maybe I'll end on this and then we can open up to a Q&A.

512
00:33:25,000 --> 00:33:32,000
 When you look at the big picture, this can seem like small drops on hot stones.

513
00:33:32,000 --> 00:33:40,000
 This is perhaps nothing compared to what it's required to train a large language model

514
00:33:40,000 --> 00:33:47,000
 or the explosion of IoT devices, etc.

515
00:33:47,000 --> 00:33:55,000
 This is a comic from XKCD, of course there is a comic about this, in which Q-ball says,

516
00:33:55,000 --> 00:34:00,000
 "I'm trying to fix the problem of the world, can you help?"

517
00:34:00,000 --> 00:34:07,000
 White hat says, "It's obvious you don't actually care, if you did, we'd be trying to fix this other bigger problem."

518
00:34:07,000 --> 00:34:10,000
 Q-ball asks, "You want to help me fix that bigger problem?"

519
00:34:10,000 --> 00:34:14,000
 White hat says, "No, for another reason I'll think of later."

520
00:34:14,000 --> 00:34:20,000
 The bigger problem fallacy, saying there's something bigger that's a bigger problem than what you're trying to fix,

521
00:34:20,000 --> 00:34:24,000
 is a fallacy, it doesn't mean the other problem is not a problem.

522
00:34:24,000 --> 00:34:30,000
 Also, sometimes tackling the biggest problem is not the most effective approach.

523
00:34:30,000 --> 00:34:34,000
 You have to think about what resources you have available to you.

524
00:34:34,000 --> 00:34:39,000
 At KDE, we are desktop software developers, we can influence this.

525
00:34:39,000 --> 00:34:44,000
 I hope I've convinced you that it does add up, once you start looking at the numbers.

526
00:34:44,000 --> 00:34:48,000
 I'd also say climate change and combating climate change

527
00:34:48,000 --> 00:34:53,000
 require changes in every single aspect of society.

528
00:34:53,000 --> 00:34:56,000
 This is where we can contribute and where we can focus our energies.

529
00:34:56,000 --> 00:34:59,000
 There are areas that maybe you can contribute to.

530
00:34:59,000 --> 00:35:02,000
 I hope that I've convinced you it's worth working on,

531
00:35:02,000 --> 00:35:06,000
 because most people here are involved in some sense with ICT,

532
00:35:06,000 --> 00:35:09,000
 and you can make a change, and you can make a difference.

533
00:35:09,000 --> 00:35:12,000
 I want to leave it on that note, and then go to Q&A.

534
00:35:12,000 --> 00:35:19,000
 [applause]

535
00:35:19,000 --> 00:35:23,000
 Thank you. Thank you so much, Joseph, for that insightful talk.

536
00:35:23,000 --> 00:35:30,000
 By the way, before we start with the Q&A, just a reminder that if you found that talk so insightful as I did,

537
00:35:30,000 --> 00:35:33,000
 and learned something new, maybe you can post that out to the Fediverse.

538
00:35:33,000 --> 00:35:37,000
 The hashtag from this stage is #bitsandboimer.

539
00:35:37,000 --> 00:35:41,000
 Now to the Q&A. We have our wonderful stage manager, Rico,

540
00:35:41,000 --> 00:35:48,000
 who can come along and pass you a microphone, so everybody will hear you just fine.

541
00:35:48,000 --> 00:35:51,000
 As I said earlier, I don't have a monopoly on information.

542
00:35:51,000 --> 00:35:55,000
 If anyone here has an answer, please feel free to speak up.

543
00:35:55,000 --> 00:36:01,000
 I feel like this is a wonderful crowd to crowdsource information gathering.

544
00:36:01,000 --> 00:36:09,000
 Well, actually, it seems to me that this problem is an efficiency problem, more or less.

545
00:36:09,000 --> 00:36:19,000
 We want to do a task with the fewest resources possible in the fastest way, of course,

546
00:36:19,000 --> 00:36:28,000
 which is shouldn't we just continue to optimize our code, which is the way to do it,

547
00:36:28,000 --> 00:36:32,000
 and to remove stuff we don't need.

548
00:36:32,000 --> 00:36:36,000
 That's basically put it in a short way.

549
00:36:36,000 --> 00:36:42,000
 Is it this correct, or are there other things also to it?

550
00:36:42,000 --> 00:36:47,000
 So thinking about things like uninstallability, right?

551
00:36:47,000 --> 00:36:49,000
 That's beyond just optimization.

552
00:36:49,000 --> 00:36:54,000
 That's a design decision for how you then allow users to use that software.

553
00:36:54,000 --> 00:36:57,000
 So I would say it's beyond just this one efficiency.

554
00:36:57,000 --> 00:37:02,000
 I think that's absolutely important, but you have to think about it also in that holistic sense of

555
00:37:02,000 --> 00:37:05,000
 can users -- okay, you might make the most efficient software,

556
00:37:05,000 --> 00:37:08,000
 but can users uninstall it if they don't need it?

557
00:37:08,000 --> 00:37:10,000
 That's a design decision.

558
00:37:10,000 --> 00:37:16,000
 I don't think many people think of free software licensing as a design idea,

559
00:37:16,000 --> 00:37:20,000
 but in many ways it determines how users can interact with your software.

560
00:37:20,000 --> 00:37:25,000
 This is an example, one, of uninstalling something or only installing what you want.

561
00:37:25,000 --> 00:37:30,000
 So it's more than just optimization, I would say.

562
00:37:30,000 --> 00:37:38,000
 My question is that there is a sustainable supply chain law in the European Union

563
00:37:38,000 --> 00:37:44,000
 and in Germany, Lieferkettengesetz, which if it would be taken serious,

564
00:37:44,000 --> 00:37:51,000
 you could not import or sell any other phone here except the Fairphone,

565
00:37:51,000 --> 00:37:59,000
 because other phones would fall under this law, which is prohibiting importing things

566
00:37:59,000 --> 00:38:08,000
 where parts of it in the production process have violated human rights or environmental laws.

567
00:38:08,000 --> 00:38:14,000
 So my first question is, is there anybody talking about this in this community,

568
00:38:14,000 --> 00:38:18,000
 about this not fulfilling this law?

569
00:38:18,000 --> 00:38:25,000
 My second question is if this Lieferkettengesetz, this supply chain law,

570
00:38:25,000 --> 00:38:29,000
 could be applied also to software?

571
00:38:29,000 --> 00:38:34,000
 Is there some idea that you just say it could not be sold

572
00:38:34,000 --> 00:38:43,000
 if it doesn't comply some minimum standard of environmental responsibility?

573
00:38:43,000 --> 00:38:47,000
 So I don't know anyone talking about that, the supply chain issues,

574
00:38:47,000 --> 00:38:50,000
 maybe someone here does.

575
00:38:50,000 --> 00:38:54,000
 I'll let the moderator decide.

576
00:38:54,000 --> 00:39:00,000
 If someone has a comment on that, please feel free.

577
00:39:00,000 --> 00:39:05,000
 Well, I wanted to ask a question that goes into the similar direction,

578
00:39:05,000 --> 00:39:11,000
 because I was wondering, are there legislations being discussed

579
00:39:11,000 --> 00:39:19,000
 about reducing the energy consumption of software and to the supply chain law?

580
00:39:19,000 --> 00:39:26,000
 I personally thought that it's more about the human rights problem,

581
00:39:26,000 --> 00:39:34,000
 mainly about hardware then, and that then this law would not apply to software,

582
00:39:34,000 --> 00:39:47,000
 but that's only how...

583
00:39:47,000 --> 00:39:58,000
 Can you pass the mic so that...

584
00:39:58,000 --> 00:40:01,000
 So, yeah, so anyone else have a comment on that?

585
00:40:01,000 --> 00:40:06,000
 Yeah, software in general and Lieferketten,

586
00:40:06,000 --> 00:40:13,000
 we also have kind of Lieferketten supply chains, we have libraries,

587
00:40:13,000 --> 00:40:17,000
 we have operating systems, we have whatever,

588
00:40:17,000 --> 00:40:20,000
 and these things also need to be produced in some way,

589
00:40:20,000 --> 00:40:23,000
 someone needs to sit down and code them.

590
00:40:23,000 --> 00:40:29,000
 So it would make sense that it applies there.

591
00:40:29,000 --> 00:40:34,000
 I'm not a lawyer, I cannot really answer this question,

592
00:40:34,000 --> 00:40:40,000
 but it makes sense that we also look at our supply chains

593
00:40:40,000 --> 00:40:46,000
 and how they are ecologically, that we are good or bad.

594
00:40:46,000 --> 00:40:50,000
 For example, we could choose a framework that is more efficient,

595
00:40:50,000 --> 00:40:54,000
 we could choose a framework that makes stuff easier for us,

596
00:40:54,000 --> 00:41:00,000
 and of course, software can also be produced under conditions

597
00:41:00,000 --> 00:41:03,000
 which are not compatible to human rights.

598
00:41:03,000 --> 00:41:07,000
 You can force people to sit down and program stuff,

599
00:41:07,000 --> 00:41:18,000
 and this code would be unethical to use in a way as programmers.

600
00:41:18,000 --> 00:41:25,000
 Do we have time for another question?

601
00:41:25,000 --> 00:41:29,000
 Yeah, so what do you have to say about the law of diminishing returns?

602
00:41:29,000 --> 00:41:33,000
 For example, is there a way to know what's the point

603
00:41:33,000 --> 00:41:36,000
 when we already reached those diminishing returns

604
00:41:36,000 --> 00:41:41,000
 and we have to move on to something else to keep optimizing and doing that stuff?

605
00:41:41,000 --> 00:41:47,000
 Is there some finger rule?

606
00:41:47,000 --> 00:41:54,000
 I don't have a rule of thumb for when that is.

607
00:41:54,000 --> 00:41:59,000
 I do think we still have a lot of low-hanging fruit, to be honest,

608
00:41:59,000 --> 00:42:03,000
 before we get to the problem of diminishing returns.

609
00:42:03,000 --> 00:42:08,000
 I think there's enough that we could do in terms of designing your website,

610
00:42:08,000 --> 00:42:13,000
 following green-coding practices, being able to turn off advertising,

611
00:42:13,000 --> 00:42:16,000
 continuing to support hardware, opening up bootloaders

612
00:42:16,000 --> 00:42:20,000
 so you can install any software on any device that you bought.

613
00:42:20,000 --> 00:42:23,000
 These are all things I think are pretty low-hanging fruit,

614
00:42:23,000 --> 00:42:27,000
 which already make a big contribution before we're even at that point.

615
00:42:27,000 --> 00:42:30,000
 That's my personal opinion on that.

616
00:42:30,000 --> 00:42:37,000
 Thanks.

617
00:42:37,000 --> 00:42:45,000
 What's your opinion on these bloat solutions like Docker or Snap and stuff

618
00:42:45,000 --> 00:42:49,000
 who actually for a small application ship a whole operating system

619
00:42:49,000 --> 00:42:56,000
 and thus bloat my disk so that I think next time I need a bigger SSD in my laptop

620
00:42:56,000 --> 00:43:01,000
 because some applications take up to a couple of hundred gigabytes?

621
00:43:01,000 --> 00:43:04,000
 Is there an estimation?

622
00:43:04,000 --> 00:43:10,000
 What's the difference in CO2 footprint of half a terabyte and one terabyte?

623
00:43:10,000 --> 00:43:14,000
 What's your opinion there?

624
00:43:14,000 --> 00:43:17,000
 I don't have a particular opinion.

625
00:43:17,000 --> 00:43:21,000
 I do think it's an empirical question that we have a lab we could maybe start testing

626
00:43:21,000 --> 00:43:25,000
 to see if these differences in how you install,

627
00:43:25,000 --> 00:43:28,000
 which approach you take to installing software,

628
00:43:28,000 --> 00:43:31,000
 if that influences things like general energy consumption.

629
00:43:31,000 --> 00:43:34,000
 I think we could look at that and see it.

630
00:43:34,000 --> 00:43:41,000
 I can imagine that there are arguments that upgrades can result in more efficient software

631
00:43:41,000 --> 00:43:47,000
 that might outweigh the disadvantages of installing it through a flat pack

632
00:43:47,000 --> 00:43:52,000
 if there is a difference there, but I don't know.

633
00:43:52,000 --> 00:43:54,000
 We have two more questions left.

634
00:43:54,000 --> 00:43:59,000
 Unfortunately, then we have to close, but discussions can also unfold afterwards.

635
00:43:59,000 --> 00:44:00,000
 Maybe you're around here for a while.

636
00:44:00,000 --> 00:44:01,000
 I'm definitely around for a while.

637
00:44:01,000 --> 00:44:04,000
 Great. Please.

638
00:44:04,000 --> 00:44:13,000
 On the CO2 footprint of software, Docker Solutions and something else,

639
00:44:13,000 --> 00:44:21,000
 look just into the power consumption of Hello World in C or in Python.

640
00:44:21,000 --> 00:44:31,000
 It's 20 times more in Python to realize a Hello World program than in C or in some other languages.

641
00:44:31,000 --> 00:44:38,000
 All the time in the back head when we talk about software or something like that,

642
00:44:38,000 --> 00:44:45,000
 the big bloat solutions who do need Python and bigger compilers, Rust,

643
00:44:45,000 --> 00:44:52,000
 and whatever has a high power consumption.

644
00:44:52,000 --> 00:45:04,000
 We have to go in our mind if it's useful to make this all including big systems in software and hardware,

645
00:45:04,000 --> 00:45:16,000
 or if we do not split it in small pieces, which can be done in a sampler in C and save us a lot of energy.

646
00:45:16,000 --> 00:45:17,000
 Thank you.

647
00:45:17,000 --> 00:45:18,000
 Thank you for that comment.

648
00:45:18,000 --> 00:45:22,000
 Last question, but not least.

649
00:45:22,000 --> 00:45:28,000
 I would like to highlight that besides efficiency, there's another thing that I would say is rather important

650
00:45:28,000 --> 00:45:35,000
 and we talk too little about, which is sufficiency using less in general.

651
00:45:35,000 --> 00:45:40,000
 For example, the supplies to social media or streaming services,

652
00:45:40,000 --> 00:45:49,000
 being nudged into using those media for many hours a day, which is probably not very healthy for ourselves,

653
00:45:49,000 --> 00:45:55,000
 but also if we didn't use the software for that long and the hardware as well,

654
00:45:55,000 --> 00:46:00,000
 we might be happier in the first place and use less resources.

655
00:46:00,000 --> 00:46:02,000
 Fully agree.

656
00:46:02,000 --> 00:46:05,000
 Sufficiency is definitely a good question to ask.

657
00:46:05,000 --> 00:46:06,000
 Thank you so much.

658
00:46:06,000 --> 00:46:11,000
 I think these are good closing remarks. You want to add anything for the audience?

659
00:46:11,000 --> 00:46:14,000
 I would love to talk with you some more.

660
00:46:14,000 --> 00:46:18,000
 [Music]