Hacking

Humility and hacking

This is my year of change.  One of the things on my list is to become a better hacker.  Another is to tell more of my stories, lest I finally go insane or die in a bizarre hangliding accident involving a sheep and lose them all.  This post kinda covers both. There’s a saying: “everyone knows the good hackers are; nobody knows who the great ones are”.  Well, I know some of the great ones: the ones who broke things way ahead of everyone else, who pulled off unbelievable stunts but never ever went public, and they taught me a lot when I was younger (they didn’t always realise they were teaching me, but hey, it’s in the blood).  And yes, I broke into a lot of things; I hated the privilege of secrets, enjoyed the finesse of entering without being seen and yes, on occasion the privilege of being…

Software

The ‘citizens’ have power. They can help.

[cross-post from medium] This is a confusing time in a confusing place. I’ve struggled with concepts like allyship from within, of whether I sit in a country on the verge of collapse or renewal, on how I might make some small positive difference in a place that could take the world down with it. And, y’know, also getting on with life, because even in the midst of chaos, we still eat and sleep and continue to do all the human things. But I’m starting to understand things again. I often say that the units of this country are companies, not people: that democratic power here rests a lot in the hands of organizations (and probably will until Citizens United is overturned, people find their collective strength and politics comes back from the pay-to-play that it’s become in the last decade or two). But since we’re here, I’ve started thinking about…

Software

Boosting the data startup

[cross-post from Medium] Some thoughts from working in data-driven startups. Data scientists, like consultants, aren’t needed all the time. You’re very useful as the data starts to flow and the business questions start to gel, but before that there are other skills more needed (like coding); and afterwards there’s a lull before your specialist skills are a value-add again. There is no data fiefdom. Everyone in the organization handles data: your job is to help them do that more efficiently and effectively, supplementing with your specialist skills when needed, and getting out of the way once people have the skills, experience and knowledge to fly on their own. That knowledge should include knowing when to call in expert help, but often the call will come in the form of happening to walk past their desk at the right time. Knowing when to get involved is a delicate dance. Right at…

Software

What could help fix belief problems?

[cross-post from Medium] Last part (of 4) from a talk I gave about hacking belief systems. Who can help? My favourite quote is “ignore everything they say, watch everything they do”. It was originally advice to girls about men, but it works equally well with both humanity and machines. If you want to understand what is happening behind a belief-based system, you’re going to need a contact point with reality. Be aware of what people are saying, but also watch their actions; follow the money, and follow the data, because everything leaves a trace somewhere if you know how to look for it (looking may be best done as a group, not just to split the load, but also because diversity of viewpoint and opinion will be helpful). Verification and validation (V&V) become important. Verification means going there. For most of us, verification is something we might do up front, but…

Software

What goes wrong in belief-based models?

[cross-post from Medium] This is part 3 of a talk I gave recently on hacking belief systems using old AI techniques. Parts 1 and 2 looked at human and computational belief, and the internet and computer systems development as belief-based systems. Now we look at the things that can (and do) go wrong with belief-based systems. Machine Belief Machines have a belief system either because we hard-wire that system to give a known output for a known input (all those if-then statements), or because they learn it from data. We touched on machine learning in part 1 of this series (remember the racist chatbot?), and on how it’s missing the things like culture, error-correction and questioning that we install in small humans. But before we get to how we might build those in, let’s look at the basic mechanics of machine learning. At the heart of machine learning are algorithms:…

Software

Why should technologists care about belief?

[cross-posted from Medium] This is part of a talk on hacking belief systems using old AI techniques. The first part covered human beliefs, machine beliefs, and deep learning and the internet as belief-based systems. Lean and Agile are based on belief   The build-measure-learn cycle. Image from https://steveblank.com/2015/05/06/build-measure-learn-throw-things-against-the-wall-and-see-if-they-work/ Most system development I see now uses agile principles: short, iterative cycles of development, and an emphasis on learning, preferably alongside the system’s users, and adapting their systems to increase some measure of customer or user value. Lean is a similar idea at the company level, based around learning quickly about what works through prototyping and measurement (aka the “build-measure-learn” cycle). Lean Startup is the small-scale version of this; Lean Enterprise is the large-organisation one. I’m going to focus on Lean Enterprise because it’s more complex. In an established organization, Lean’s usually a combination of learning and adapting existing business, and exploring new…

Software

Mixing human and computational belief

[cross-post from Medium] This is part 1 of a talk I gave recently on hacking belief systems using old AI techniques. I have a thing about belief systems. Not religious belief, but what it means to believe something, when accuracy does and doesn’t matter, and why “strongly held belief” is a better concept to aim at than “true”. It’s something I’ve been thinking about for a while, and I believe (!) it’s a conversation we need to have both as technologists who base many of our work decisions on beliefs, and often work on a belief-based system (the internet), and in the current climate of “fake news”, uncertainty and deliberate disinformation. I care about belief because I care a lot about autonomy: the ways that humans and machines can work together, sharing control, responsibility and as teams, and we don’t talk enough yet about the human-machine sharing of belief systems…

Software

Hacking elections with data

[cross-post from Medium] Cambridge Analytica basically used customer segmentation and targeting: standard advertising stuff (and some cynicism about that: iirc one of the other campaigns ditched them) that will probably become standard for campaigns if it hasn’t already (full disclosure: am helping out on a campaign). Cool (if unethical) use of surveys as probes though. Get the feeling they didn’t do as much as they could have done, but that was enough. Not sure how I feel about gaming elections right now: part of me says bad, another part that it’s politics as normal, just scaled and personalised. Meanwhile, on the Democratic side, big data seems to be a problem. We need to fix this. So repeat after me “big data is not data science”. Get the data, study the data, but understand that exploring data is just part of the arc between questions and storytelling, that humans are complex…

Software

Bursting the right bubbles

[cross-post from Medium] First, understand the bubble It’s hard to argue with people if you don’t know where they’re coming from. One way is to ask: engage with people who are vehemently disagreeing with you, find out more about them as people, about their environments and motives. Which definitely should be done, but it also helps to do some background reading… The Guardian’s started in on this: a round-up of 5 non-liberal articles every week, complete with backgrounder on each author and why the article is important. It doesn’t hurt that some of these authors are friends of friends and therefore maybe approachable with some questions. It’s also worth checking out things like BlueFeed RedFeed. I’ve taken some flack lately for trying to understand Trump supporters. I’m slowly coming round to amending that to trying to understand Trump voters — especially the ones who voted with their noses held. Us vs Them…

Software

Fake News Isn’t About Truth, It’s About Gaming Belief Systems

[cross-post from Medium] Thinking about #fakenews. Starting with “what is it”. * We’re not dealing with truth here: we’re dealing with gaming belief systems. That’s what fake news does (well, one of the things; another thing it does is make money from people reading it), and just correcting fake news is aiming at the wrong thing. Because… * Information leaves traces in our heads, even when we know what’s going on. If I jokingly tell you that I’ve crashed your car, then go ‘ha ha’, you know that I didn’t crash your car, but I’ve left a trace in your head that I’m an unsafe driver. The bigger the surprise of the thing you initially believe, the bigger the trace it leaves (this is why I never make jokes like that). * That’s important because #fakenews isn’t about the thing that’s being said. It’s about the things that are being…