Contestable Camera Cars:: A Speculative Design Exploration of Public AI That Is Open and Responsive to Dispute

Local governments increasingly use artificial intelligence (AI) for automated decision-making. Contestability, making systems responsive to dispute, is a way to ensure they respect human rights to autonomy and dignity. We investigate the design of public urban AI systems for contestability through the example of camera cars: human-driven...

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...

A Machine learning approach for rapid disaster response based on multi- modal data: The case of housing & shelter needs

Along with climate change, more frequent extreme events, such as flooding and tropical cyclones, threaten the livelihoods and wellbeing of poor and vulnerable populations. One of the most immediate needs of people affected by a disaster is finding shelter. While the proliferation of data on disasters is already helping to save lives, identifying...

AI Model Lifecycle Management: Systematic Mapping Study and Solution for AI Democratisation

The development of artificial intelligence (AI) has made various industries eager to realise and obtain the benefits of AI. There is an increasing amount of research surrounding AI, most of which is centred on the development of new AI algorithms and techniques, thereby, however, ignoring an increasing set of practical problems related to AI...

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...

Photovoltaic Yield Nowcasting: For Residential Solar Systems in the Netherlands Using a Machine Learning Approach

An increasing number of photovoltaic (PV) systems are being installed worldwide and residential sector is responsible for a large part of this growth. Small scale PV systems do not have complex measuring devices and their breakdowns are not spotted immediately by the system owners. This might lead to prolonged time without generating power and...

Fuzzy Probabilistic Learning and Reasoning, Rule Induction for Decision-Support Systems in Exacting Environments