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Posts relating to “Artificial Intelligence”: not defined in any more precise way than the duck test…
Looking at discussions of Regulating Artificial Intelligence it struck me that a lot isn’t new, and a lot isn’t specific to AI. Jisc already has a slightly formal Pathway document to help you identify issues with activities that might involve AI. But here are some topics that seem to often come up in those discussions. […]
Whether you refer to your technology as “data-driven”, “machine learning” or “artificial intelligence”, questions about “algorithmic transparency” are likely to come up. The finest example is perhaps the ICO’s heroic analysis of different statistical techniques. But it seems to me that there’s a more fruitful aspect of transparency earlier in the adoption process: why was […]
When the Internet first came to legislators’ notice, there was a tendency to propose all-encompassing “laws of internet” for this apparently new domain. A celebrated paper by Frank Easterbrook argued that (my summary) there wasn’t a separate body of new harms to address and that existing laws might well prove sufficiently flexible to deal with […]
The European legislative process on Artificial Intelligence has moved on one step with the Council of Ministers (representatives of national governments) agreeing on their response to the text proposed by the European Commission last year. The main focus of the proposed law is makers of products that use “AI”: where these are designed for a […]
One promising application of Machine Learning in education is marking support. Colleagues in Jisc’s National Centre for AI have identified several products that implement a similar process, where a program “watches” a human marking assessments, learns in real time, and suggests how the quality and consistency of marking can be maintained or even improved. This […]
One of the major causes of disruption on the Internet is Distributed Denial of Service (DDoS) attacks. Unlike “hacking”, these don’t require there to be any security weakness in the target system: they simply aim to overload it with more traffic than it (or its network connection) can handle. Often such attacks are launched from […]
The latest draft part of the ICOs guidance on data protection technologies covers Privacy Enhancing Technologies (PETs). This is a useful return to a topic covered in a very early factsheet, informed both by technical developments and a better understanding of how technologies can (and cannot) contribute to data protection. Perhaps the most important message […]
Sophos have recently released a tool that uses Machine Learning to propose simple rules that can be used to identify malware. The output from YaraML has many potential uses, but here I’m considering it as an example of how automation might help end devices identify hostile files in storage (a use-case described by Sophos) and […]
I’m hoping my generic model of a security automat (Levers, Data, Malice, Controls, Signals) will help me think about how tools can contribute to network security and operations. It produces the ideas I’d expect when applied to areas that I already know about, but the acid test is what happens when I use it to […]
Earlier in the year, Networkshop included a presentation on Juniper’s Mist AI system for managing wifi networks. I was going to look at it – as an application I don’t know – as a test for my model for thinking about network/security automation. That may still happen, but first it has taken me down an […]