Position Statement on the Use of ML / KI Techniques in Software Engineering For the adesso Hochschulbeirat

I just submitted the following short position statement on how to work with ML / KI techniques in software engineering. This is a statement on using such techniques for the engineering of software, not in the software itself, which is a (not completely, but mostly) separate issue.

ML / KI techniques can be use in software development to assist the human engineer. Properly applied, they can make engineers more productive by helping them focus on understanding and solving the human problem behind the software to be developed (essential complexity) and by freeing them from getting distracted by technical implementation details (accidental complexity).

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Translation (to German) of Interview on Open Source in the Public Sector

I recently was interviewed about open source in the public sector and blogged my answers here:

t3n magazin now (liberally) translated these to German. Check it out: Ich denke, dass Software mit offenem Quelltext längst gewonnen hat. (local copy).

Why Open Source is Good for Your Economy (FOSSC19 Recap)

It is no secret that software is everywhere. No traditional product has remained untouched, whether the product is being produced using software or whether software is an integral part of it. As part of this wave of digitization, established vendors from outside the software industry need to avoid that someone else will reap all the profits from their products. That someone else would be software companies that supply needed components. In particular software platforms can have such network effects that their providers can reach a monopoly position so that dependent vendors who need the platform will face a diminishing profit margin.

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The Argument For a Moral Machine in Autonomous Driving

I have a strong aversion against letting people drag their feet from being responsible for their actions. I feel particularly strongly about this when delegating work to machines, which are not able to act using an appropriate moral value system. Starting a car and letting an autonomous driving unit take over is one such example: When faced with an impossible situation (run over an old lady or three children or commit suicide), it still has to be the driver’s decision and not a machine’s.

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Why Open Source is Good for Your Economy

Today, at FOSSC 2019 in Muscat, Oman, I gave a talk about the benefits of sponsoring open source software development to about anyone who isn’t the software vendor whose product is getting replaced by that open source software. These are the slides. I will be repeating the same message at the German Forschungsgipfel in March. Also, here is a slideshare version:

[slideshare id=131019008&doc=osecon16x9-190208141547]

Happy New Year, The Second Amendment, And Private Messaging

There is wisdom in the second amendment of the constitution of the United States of America. A key motivation was to allow people to defend themselves against an oppressive government. Back when it was formulated, self-defense meant bearing firearms, which seems quaint today given that a government could came after you with tanks and drones. So, beyond a narrow U.S. legal interpretation, the amendment needs interpretation in a modern context. As such, it is of relevance to the world at large.

What does the right to self-defense against a potentially oppressive government mean?

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The Dancing Robot Dog: Magic Trick or Real Artificial Intelligence?

You may have seen the video below by Boston Dynamics. It shows a robot dog dancing to Uptown Funk by Bruno Mars. It is fun and funny to watch, but people also expressed serious worries about robot inroads into human behavior. However, there is no explanation by Boston Dynamics and it is not at all clear whether this is a simple magic trick created to fool the onlookers or real artificial intelligence (AI) progress.

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Open Data: Source of Public Income or Invaluable Common Good?

Not surprisingly, this huddling panel at the 2018 Berlin Open Data Day came to no specific conclusion, just different opinions on business models and who should earn what income.

Some nuggets of insight: Leave it to public institutions to decide for themselves — open data should be freely available, otherwise some commercial business models break down — cities should be neutral to startups and establish collaborations for everyone’s benefit — leave it to companies to generate value from open data and they will give back #muwhaha — don’t monetarize open data at all — if users don’t pay, public institutions won’t have the funds to provide open data — open data should be considered public infrastructure and follow established practices — the data belongs to the public anyway — selling data is too expensive for a city.

In related news, some cheap laughs for public institution bashing from one panelist. Personally, I find this less than helpful.

One amusing quote from another panelist:

In theory, we all agree, in practice, we do not.

I guess more sustainability research is needed.