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Machine learning is often described as a tool that sacrifices transparency and simplicity in return for higher predictive power. Our cover image features progress by Faust et al. towards increased transparency of machine-learned models for digital pathology, by demonstrating how learned features in histopathologic images correlate to human-understandable patterns and groupings.
Civil liberty groups are raising the alarm over the ubiquitous use of automated facial recognition. As a society, we need to decide on the acceptable use of this technology and how to build in safeguards to protect human rights.
Artists have always been at the forefront of experimenting with digital tools. The AI: More than Human exhibition at the Barbican Centre, London (until August 26th), features some intriguing AI-inspired installations. We spoke to four artists about their work and influences.
Classical statistical analysis in many empirical sciences has lagged behind modern trends in analytics for large-scale datasets. The authors discuss the influence of more variables, larger sample sizes, open data sources for analysis and assessment, and ‘black box’ prediction methods on the empirical sciences, and provide examples from imaging neuroscience.
Artificial intelligence approaches can aid medicinal chemists to creatively look for new chemical entities with drug-like properties. A rule-based approach combined with a machine learning model was trained on successful synthetic routes described in chemical patent literature. This process produced computer-generated compounds that mimic known medicines.
Neural networks are a promising digital pathology tool but are often criticized for their limited explainability. Faust and others demonstrate how machine-learned features correlate with human-understandable histological patterns and groupings, permitting increased transparency of deep learning tools in medicine.
Classifying individual responses in open-ended surveys can be subjective and time-consuming. A network-based survey framework automatically classifies responses in a statistically principled manner.
Could this be the year that AI is going to surpass human performance in playing the popular video game Angry Birds? The organizers of the annual AIBIRDS competition discuss the challenges involved.