Augmented Intelligence

The Ethics of Algorithms

I opened a discussion on the ethics of algorithms recently, with a small thing about what algorithms are, what can be unethical about them and how we might start mitigating that. I kinda sorta promised a blogpost off that, so here it is. Algorithm? Wassat? Al-Khwarizmi (wikipedia image) Let’s start by demystifying this ‘algorithm’ thing. An algorithm (from Al-Khwārizmī, a 9th-century Persian mathematician, above) is a sequence of steps to solve a problem. Like the algorithm to drink coffee is to get a mug, add coffee to the mug, put the mug to your mouth, and repeat. An algorithm doesn’t have to be run a computer: it might be the processes that you use to run a business, or the set of steps used to catch a train. But the algorithms that the discussion organizers were concerned about aren’t the ones used to not spill coffee all over my face….


Infosec, meet data science

I know you’ve been friends for a while, but I hear you’re starting to get closer, and maybe there are some things you need to know about each other. And since part of my job is using my data skills to help secure information assets, it’s time that I put some thoughts down on paper… er… pixels. Infosec and data science have a lot in common: they’re both about really really understanding systems, and they’re both about really understanding people and their behaviors, and acting on that information to protect or exploit those systems.  It’s no secret that military infosec and counterint people have been working with machine learning and other AI algorithms for years (I think I have a couple of old papers on that myself), or that data scientists and engineers are including practical security and risk in their data governance measures, but I’m starting to see more profound crossovers between the two….


Notes from John Sarapata’s talk on online responses to organised adversaries

John Sarapata (@JohnSarapata) = head of engineering at Jigsaw  (= new name for Google Ideas).  Jigsaw = “the group at Google that tries to help users facing organized violence and oppression”.  A common thread in their work is that they’re dealing with the outputs from organized adversaries, e.g. governments, online mobs, extremist groups like ISIS. One example project is, which looks for people who are searching for extremist connections (e.g. ISIS) and shows them content from a different point of view, e.g. a user searching for travel to Aleppo might be shown realistic video of conditions there. [IMHO this is a useful application of social engineering in a clear-cut situation; threats and responses in other situations may be more subtle than this (e.g. what does ‘realistic’ mean in a political context?).] The Jigsaw team is looking at threats and counters at 3 levels of the tech stack: device/user: activities are consume and create content; threats include attacks by governments, phishing, surveillance,…