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…