December 27, 2017

Interesting Things on the Internet: December 27th 2017

  • The Dangers of Elite Projection. The needs of the many are not the same as the needs of the few.
  • What Do You Call a World That Can’t Learn From Itself?. "So just as Americans don’t get how bad their lives really are, comparatively speaking — which is to say how good they could be — so too Europeans don’t fully understand how good their lives are — and how bad, if they continue to follow in America’s footsteps, austerity by austerity, they could be. Both appear to be blind to one another’s mistakes and successes."
  • Why is Southern Rail like an aircraft carrier? I think this captures some of the reason behind the last link - this focus on the appearance of things going well, rather than the work of making things go well.
  • Silicon Valley Is Turning Into Its Own Worst Fear "I used to find it odd that these hypothetical AIs were supposed to be smart enough to solve problems that no human could, yet they were incapable of doing something most every adult has done: taking a step back and asking whether their current course of action is really a good idea. Then I realized that we are already surrounded by machines that demonstrate a complete lack of insight, we just call them corporations."
  • No hack needed: Anonymisation beaten with a dash of SQL. Anonymising data is near impossible.
  • Computer latency: 1977-2017. In terms of speed-at-responding-to-us, modern computers are lots worse than those of the 80s. My first computer takes 2nd place, and my third computer is 5th. I expect the one I'm typing this on is far down the list.
  • My Internet Mea Culpa. I'm not sure where I sat on believing the elders of the Web, but my critical faculties have taken too long to develop and have had too little impact thus far. There is much work to do if we're to realise the promise of computers and the Internet. This Twitter thread from @seldo has some good thoughts on the topic.
  • Bernard Stiegler: “The time saved through automation must be granted to the people” [translation]. "The work of tomorrow will be discontinuous [intermittent]. Periods of employment will alternate with periods of acquiring, developing and sharing knowledge. The right to the contributory income will be “rechargeable”, based upon the number of hours of employment. In case of problems, the system will be accompanied by a minimum living wage [revenu minimum d’existence] – as a social protection system accompanying the scheme."
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December 11, 2017

Interesting Things on the Internet: December 11th 2017

And a fantastic talk about tech leadership, principles and ethics from Bryan Cantrill at Monktoberfest...

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December 10, 2017

We Should Stop Using AI As a Way to Duck Responsibility

I've been reading Eric Rodenbeck's Fake-but-good-enough-for-robots satellite imagery, drawn by artificial intelligences. It's a good and interesting read, but there's something in its language that needles me.

We shouldn't surrender agency to algorithms. As software engineers, system designers and technologists we should be wary of explanations that imply that "the AI did it". It's a convenient, and understandable, defence because the alternative is to admit that we built a system that doesn't work as we intended, that has bugs. Even if the bugs are really subtle and dependent on datasets used for training, or combinations of sensors that are hard to predict.

However, it's all a bit "a big boy did it and ran away".

It feels to me that it's similar to the "code isn't political" myth that I hope we can all agree was a lie.

Eric's examples, and I'm as guilty as he is for reaching for the same metaphors when trying to explain what I do, aren't really "how robots see us" or "how robots talk with us".

The green circles overlaid on the video imagery aren't something a robot has created, they're written by people to help said people get a better understanding of how their code works. When I build things like that they're little meta-tools to help me work out why my code isn't doing what I thought it would.

I think that if we frame it in that way - tools and techniques to help humans understand algorithms - it leads us into a different but more useful rabbithole. Chasing down that one leads people to ask better questions of the technologists about what they were trying to achieve, why that has ended up in this unintended consequence, and how we might fix that or build better tools to explain it further.

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December 04, 2017

Interesting Things on the Internet: December 4th 2017

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