Today I had the pleasure to witness the public defense of Stanley Greenstein’s Ph D dissertation on legal implications of predictive modelling: “Our humanity exposed — Predictive modelling in a legal context” for which I was a co-supervisor on technical matters.
In his dissertation, Stanley gives an inventory of several legal frameworks which might be relevant for the effects predictive modelling might have on an individual. He discusses the risk of “potential harm” — harms which an individual might not even be aware have occurred, such as a somewhat higher interest rate or insurance payment, or not being selected for a job. He examines how European regulations on data protection and human rights are applicable to understanding such harms, and focusses on the target notion of “empowerment” as a legal concept to address the information imbalance between large organisations and individuals.
Markus Östberg today gave a very convincing talk to successfully defend his Master’s Thesis “Subtopic extraction using graph based methods” on semi-supervised methods for categorising texts with respect to external knowledge sources. The thesis work was performed at Findwise and supervised by myself. In order not to disrupt his defence seminar, KTH made sure that the visit by president Obama of the US was confined to the library next door.
Maria Gerontini successfully defended her master’s thesis in computer science. Her thesis, which I supervised, “Geospatial analysis on mobile application usage”, was on places, mobility, and user behaviour and is part of an ongoing project at Ericsson. She has found interesting correlations between type of place, time of week, and demographics.
Mari-Sanna Paukkeri of the Department of Information and Computer Science at Aalto University successfully defended her dissertationLanguage- and domain-independent text mining at a public defense where I had the honour to officiate as the faculty opponent. Mari-Sanna Paukkeri’s dissertation which was a compilation of several previous publications, each with interesting and inspiring contributions to the general area of language technology and cognitive models for text mining, takes an artificial intelligence approach to learning and the role of subjectivity as an evaluation criterion for understanding text mining as a task.
Mikael Gunnarsson på Borås högskola försvarade offentligen den 29 april sin avhandling Classification along Genre Dimensions med Ragnar Nordli från Oslo som opponent och där jag hade äran vara medlem av betygsnämnden. Avhandlingen gav en teoretisk bas för studiet av genrer för informations- och biblioteksvetenskapen och samlade flera forskningsriktningars problemformuleringar varefter den redovisade en serie experiment i genrebestämning med maskininlärningsmetoder. Den kommer otvetydigt kunna utgöra en grund för mycket fortsatt arbete i informationsvetenskaperna där ofta genre tagits som en fix och färdig kategori utan vidare eftertanke. Borås var också soligt och behagligt; disputationen trespråkigt genomförd på norska, danska och svenska.