European Union regulations on algorithmic decision-making and a "right to explanation"

We summarize the potential impact that the European Union's new General Data Protection Regulation will have on the routine use of machine learning algorithms. Slated to take effect as law across the EU in 2018, it will restrict automated individual decision-making (that is, algorithms that make decisions based on user-level predictors) which "significantly affect" users. The law will also effectively create a "right to explanation," whereby a user can ask for an explanation of an algorithmic decision that was made about them. We argue that while this law will pose large challenges for industry, it highlights opportunities for computer scientists to take the lead in designing algorithms and evaluation frameworks which avoid discrimination and enable explanation.Comment: presented at 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), New York, N

Clustering with shallow trees

We propose a new method for hierarchical clustering based on the optimisation of a cost function over trees of limited depth, and we derive a message--passing method that allows to solve it efficiently. The method and algorithm can be interpreted as a natural interpolation between two well-known approaches, namely single linkage and the recently presented Affinity Propagation. We analyze with this general scheme three biological/medical structured datasets (human population based on genetic information, proteins based on sequences and verbal autopsies) and show that the interpolation technique provides new insight.Comment: 11 pages, 7 figure

Proximate Cause in Constitutional Torts: Holding Interrogators Liable for Fifth Amendment Violations at Trial

This Note argues for the approach taken by the Sixth Circuit in McKinley: a proper understanding of the Fifth Amendment requires holding that an officer who coerces a confession that is used at trial to convict a defendant in violation of the right against self-incrimination should face liability for the harm of conviction and imprisonment. Part I examines how the Supreme Court and the circuits have applied the concept of common law proximate causation to constitutional torts and argues that lower courts are wrong to blindly adopt common law rules without reference to the constitutional rights at stake. It suggests a different approach that is more faithful to Supreme Court precedent and better explains the variety of holdings among lower courts. Part II examines the conflicting opinions of the Fifth and Sixth Circuits in more detail and argues that the analysis of the Sixth Circuit is preferable because it more closely tracks Supreme Court precedent and the framework developed in Part I

Detecting and quantifying causal associations in large nonlinear time series datasets

Identifying causal relationships and quantifying their strength from observational time series data are key problems in disciplines dealing with complex dynamical systems such as the Earth system or the human body. Data-driven causal inference in such systems is challenging since datasets are often high dimensional and nonlinear with limited sample sizes. Here, we introduce a novel method that flexibly combines linear or nonlinear conditional independence tests with a causal discovery algorithm to estimate causal networks from large-scale time series datasets. We validate the method on time series of well-understood physical mechanisms in the climate system and the human heart and using large-scale synthetic datasets mimicking the typical properties of real-world data. The experiments demonstrate that our method outperforms state-of-the-art techniques in detection power, which opens up entirely new possibilities to discover and quantify causal networks from time series across a range of research fields

Stevens\u27s Ratchet: When the Court Should Decide Not to Decide

Hidden underneath the racy death penalty issues in Kansas v. Marsh lurks a seemingly dull procedural issue addressed only in separate opinions by Justices Stevens and Scalia: whether the Court should have heard the case in the first place. As he did in three cases from the Court’s 2005 term, Justice Stevens argued in Marsh that the Court has no legitimate interest in reviewing state court decisions that overprotect federal constitutional rights. Instead, the Supreme Court should exercise its certiorari power to tip the scales against states and in favor of individuals. Granting certiorari in Marsh, Stevens argued, was not motivated by a desire to create uniformity in interpretation of federal law, but was motivated by “[n]othing more than an interest in facilitating the imposition of the death penalty.” Justice Scalia vehemently disagreed, writing that Stevens’s argument rested on a “misguided view of federalism” and ignored the need for integ-rity and uniformity of federal law. He believes that would create a “crazy quilt,” in which each state could interpret the federal Constitution as it saw fit so long each such interpretation gave individuals more protection than necessary