Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead Rudin et al., arXiv 2019 With thanks to Glyn Normington for pointing out this paper to me. It’s pretty clear from the title alone what Cynthia Rudin would like us to do! The paper is a mix of technical ... Continue Reading

Futzing and moseying: interviews with professional data analysts on exploration practices

Futzing and moseying: interviews with professional data analysts on exploration practices Alspaugh et al., VAST'18 What do people actually do when they do ‘exploratory data analysis’ (EDA)? This 2018 paper reports on the findings from interviews with 30 professional data analysts to see what they get up to in practice. The only caveat to the ... Continue Reading

Invisible mask: practical attacks on face recognition with infrared

Invisible mask: practical attacks on face recognition with infrared Zhou et al., arXiv’18 You might have seen selected write-ups from The Morning Paper appearing in ACM Queue. The editorial board there are also kind enough to send me paper recommendations when they come across something that sparks their interest. So this week things are going ... Continue Reading