Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR

There has been much discussion of the right to explanation in the EU General Data Protection Regulation, and its existence, merits, and disadvantages. Implementing a right to explanation that opens the black box of algorithmic decision-making faces major legal and technical barriers. Explaining the functionality of complex algorithmic decision-making systems and their rationale in specific cases is a technically challenging problem. Some explanations may offer little meaningful information to data subjects, raising questions around their value. Explanations of automated decisions need not hinge on the general public understanding how algorithmic systems function. Even though such interpretability is of great importance and should be pursued, explanations can, in principle, be offered without opening the black box. Looking at explanations as a means to help a data subject act rather than merely understand, one could gauge the scope and content of explanations according to the specific goal or action they are intended to support. From the perspective of individuals affected by automated decision-making, we propose three aims for explanations: (1) to inform and help the individual understand why a particular decision was reached, (2) to provide grounds to contest the decision if the outcome is undesired, and (3) to understand what would need to change in order to receive a desired result in the future, based on the current decision-making model. We assess how each of these goals finds support in the GDPR. We suggest data controllers should offer a particular type of explanation, unconditional counterfactual explanations, to support these three aims. These counterfactual explanations describe the smallest change to the world that can be made to obtain a desirable outcome, or to arrive at the closest possible world, without needing to explain the internal logic of the system

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

Losing the War Against Dirty Money: Rethinking Global Standards on Preventing Money Laundering and Terrorism Financing

Following a brief overview in Part I.A of the overall system to prevent money laundering, Part I.B describes the role of the private sector, which is to identify customers, create a profile of their legitimate activities, keep detailed records of clients and their transactions, monitor their transactions to see if they conform to their profile, examine further any unusual transactions, and report to the government any suspicious transactions. Part I.C continues the description of the preventive measures system by describing the government\u27s role, which is to assist the private sector in identifying suspicious transactions, ensure compliance with the preventive measures requirements, and analyze suspicious transaction reports to determine those that should be investigated. Parts I.D and I.E examine the effectiveness of this system. Part I.D discusses successes and failures in the private sector\u27s role. Borrowing from theory concerning the effectiveness of private sector unfunded mandates, this Part reviews why many aspects of the system are failing, focusing on the subjectivity of the mandate, the disincentives to comply, and the lack of comprehensive data on client identification and transactions. It notes that the system includes an inherent contradiction: the public sector is tasked with informing the private sector how best to detect launderers and terrorists, but to do so could act as a road map on how to avoid detection should such information fall into the wrong hands. Part I.D discusses how financial institutions do not and cannot use scientifically tested statistical means to determine if a particular client or set of transactions is more likely than others to indicate criminal activity. Part I.D then turns to a discussion of a few issues regarding the impact the system has but that are not related to effectiveness, followed by a summary and analysis of how flaws might be addressed. Part I.E continues by discussing the successes and failures in the public sector\u27s role. It reviews why the system is failing, focusing on the lack of assistance to the private sector in and the lack of necessary data on client identification and transactions. It also discusses how financial intelligence units, like financial institutions, do not and cannot use scientifically tested statistical means to determine probabilities of criminal activity. Part I concludes with a summary and analysis tying both private and public roles together. Part II then turns to a review of certain current techniques for selecting income tax returns for audit. After an overview of the system, Part II first discusses the limited role of the private sector in providing tax administrators with information, comparing this to the far greater role the private sector plays in implementing preventive measures. Next, this Part turns to consider how tax administrators, particularly the U.S. Internal Revenue Service, select taxpayers for audit, comparing this to the role of both the private and public sectors in implementing preventive measures. It focuses on how some tax administrations use scientifically tested statistical means to determine probabilities of tax evasion. Part II then suggests how flaws in both private and public roles of implementing money laundering and terrorism financing preventive measures might be theoretically addressed by borrowing from the experience of tax administration. Part II concludes with a short summary and analysis that relates these conclusions to the preventive measures system. Referring to the analyses in Parts I and II, Part III suggests changes to the current preventive measures standard. It suggests that financial intelligence units should be uniquely tasked with analyzing and selecting clients and transactions for further investigation for money laundering and terrorism financing. The private sector\u27s role should be restricted to identifying customers, creating an initial profile of their legitimate activities, and reporting such information and all client transactions to financial intelligence units

Expressiveness and Instrumentality of Crime Scene Behavior in Spanish Homicides

One of the current trends in the study of criminal profiling consists of developing theoretical and methodological typologies to offer information of operational use in police investigations. The objective of this work was to verify the validity of the instrumental/expressive model, so as to establish homicide typologies based on modus operandi relationships, characteristics of the victims, and characteristics of perpetrators. The sample consisted of 448 homicide cases registered in the database of the Homicide Revision Project of the Office of Coordination and Studies of the Spanish Secretary of State and Security. Through multidimensional scaling and cluster analysis, three expressive homicide subtypes were identified (expressive-impulsive, expressive-distancing, and expressive-family), as well as two instrumental homicide subtypes (instrumental-opportunist and instrumental-gratification). The expressive homicide typologies accounted for almost 95% of all of the studied cases, and most of the homicides occurring in Spain were found to take place between individuals who know one another (friends, family members, intimate couples/ex-couples). The findings from this study suggest that the instrumental/expressive model may be a useful framework for understanding the psychological processes underlying homicides, based on the study of relationships between the crime and aggressor characteristics, which may be very helpful in the prioritization of suspect

Character analysis of oral activity: contact profiling

The article presents the results of our observations on syntactic, semantic and plot peculiarities of oral language activity, we find it justified to consider the above mentioned parameters as identification criteria for discovering characterological differences of Ukrainian-speaking and Russian-speaking objects of contact profiling. It describes the connection between mechanisms of psychological defenses as the character structural components, and agentive and non-agentive speech constructions, internal and external predicates. Localized and described plots of oral narratives inherent to representatives of different character types