Value-Sensitive Rejection of Machine Learning Predictions for Hate Speech Detection

Hate speech detection on social media platforms remains a challenging task. Manual moderation by humans is the most reliable but infeasible, and machine learning models for detecting hate speech are scalable but unreliable as they often perform poorly on unseen data. Therefore, human-AI collaborative systems, in which we combine the strengths of...

Declarative Image Generation

Generating synthetic images has wide applications in several fields such as creating datasets for machine learning or using these images to investigate the behaviour of machine learning models. An essential requirement when generating images is to control aspects such as the entities or objects in the image. Controlling this helps in creating...

Distributed Dataflow Transactions

As serverless computing grows in popularity, developers are demanding more from existing serverless models. One example is the emergence of Stateful Function as a Service (SFaaS), in which state is added to operators in existing Function as a Service (FaaS) models, to support microservice-type applications while utilising the benefits of a...

A Comparison of Auto-scaling Techniques for Distributed Stream Processing

As the world continues to embrace cloud computing, more applications are being scaled elastically. Elastic scaling allows applications to add or remove computing resources based on the load experienced by the application. When the load is high more resources are provisioned enabling the application to keep up with the load. When the load is low...

Learning Analytics of Beginner Programming Assignments for Teachers

Due to the increase in student numbers, the amount of time teachers have for each individual decreases. To keep the quality of the program the same, learning analytics can be utilized to assist teachers to give a better overview of problems which the students are struggling the most with. This work makes use of WebLab data of the Introduction to...

Towards Engineering AI Software for Fairness: A framework to help design fair, accountable and transparent algorithmic decision-making systems

Algorithmic decision-making (ADM) is becoming increasingly prevalent in society, due to the rapid technological developments in Artificial Intelligence. ADM make substantially impactful decisions about people: diagnosing whether we have a disease, what news and which ads we get to see, whether we<br/>are eligible for a job, benefits, a college...

Real-time anomaly detection in logs using rule mining and complex event processing at scale

Log data, produced from every computer system and program, are widely used as source of valuable information to monitor and understand their behavior and their health. However, as large-scale systems generate a massive amount of log data every minute, it is impossible to detect the cause of system failure by examining manually this huge size of...

Enabling Human Computation through Text-based Conversational Agents

Human Computation (HC) has established itself to be a powerful tool for carrying out certain simple and repetitive tasks in the form of microtasks, which to this day are still difficult for a machine to automate. <br/>With the latest increase in interest in machine learning, HC has similarly gotten more attention as a popular way to acquire...

On the fairness of crowdsourced training data and Machine Learning models for the prediction of subjective properties. The case of sentence toxicity: To be or not to be #$@&%*! toxic? To be or not to be fair?

Training machine learning (ML) models for natural language processing usually requires lots of data that is often acquired through crowdsourcing. In crowdsourcing, crowd workers annotate data samples according to one or more properties, such as the sentiment of a sentence, the violence of a video segment, the aesthetics of an image, ... To...

Learning Object Metadata Workflows for Description, Findability and Reusability Improvement

With the increase of online education, a good description of learning resources has become vital for educational resource sharing and reuse. Resource description has been under the spotlight in recent years. Educational platforms can benefit from good resource organisation and description, thereby providing a higher quality of services and...

Identifying memes and their interactions in online communities

Memes are theorized to be the building blocks of culture. Due to a lack of empirical validation, however, the theory of memes — memetics — remains in its infancy. We argue that one of the missing components for such empirical validation is a method for the large-scale identification of memes.<br/><br/>In this thesis, we develop a method for the...