Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

We examine counterfactual explanations for explaining the decisions made by model-based AI systems. The counterfactual approach we consider defines an explanation as a set of the system's data inputs that causally drives the decision (i.e., changing the inputs in the set changes the decision) and is irreducible (i.e., changing any subset of the inputs does not change the decision). We (1) demonstrate how this framework may be used to provide explanations for decisions made by general, data-driven AI systems that may incorporate features with arbitrary data types and multiple predictive models, and (2) propose a heuristic procedure to find the most useful explanations depending on the context. We then contrast counterfactual explanations with methods that explain model predictions by weighting features according to their importance (e.g., SHAP, LIME) and present two fundamental reasons why we should carefully consider whether importance-weight explanations are well-suited to explain system decisions. Specifically, we show that (i) features that have a large importance weight for a model prediction may not affect the corresponding decision, and (ii) importance weights are insufficient to communicate whether and how features influence decisions. We demonstrate this with several concise examples and three detailed case studies that compare the counterfactual approach with SHAP to illustrate various conditions under which counterfactual explanations explain data-driven decisions better than importance weights

Uniform stabilization for linear systems with persistency of excitation. The neutrally stable and the double integrator cases

Consider the controlled system $dx/dt = Ax + \alpha(t)Bu$ where the pair $(A,B)$ is stabilizable and $\alpha(t)$ takes values in $[0,1]$ and is persistently exciting, i.e., there exist two positive constants $\mu,T$ such that, for every $t\geq 0$, $\int_t^{t+T}\alpha(s)ds\geq \mu$. In particular, when $\alpha(t)$ becomes zero the system dynamics switches to an uncontrollable system. In this paper, we address the following question: is it possible to find a linear time-invariant state-feedback $u=Kx$, with $K$ only depending on $(A,B)$ and possibly on $\mu,T$, which globally asymptotically stabilizes the system? We give a positive answer to this question for two cases: when $A$ is neutrally stable and when the system is the double integrator

La restricción externa dinámica al crecimiento de México a través de las propensiones del comercio, 1970-1999

The Post Keynesian argument that the main limitation to growth -basically of any middle income country- is due to the trade deficit. This feature, which is structural, is called -within this frame work- External Constraint to Growth, ECG, through cointegration and ECM analysis for exports and imports functions, it is empirically demonstrated the dynamic evolution of the ECG, for 1970-1999. Despite the Mexican Economy is considerably linked to the international economy, manufacturing leads the growth process and several structural reforms have been implemented since 1985, the main conclusion is that the ECG has not changed.

Un caso de estudio sobre la brecha digital en la educación superior

Ponencias de la Segunda Conferencia Internacional sobre brecha digital e inclusión social, celebrada del 28 al 30 de octubre de 2009 en la Universidad Carlos III de MadridEn 1998 la UNESCO expresa que “Los establecimientos de educación superior han de dar el ejemplo en materia de aprovechamiento de las ventajas y el potencial de las nuevas tecnologías de la información y la comunicación” [1]. Desde entonces una década ha pasado y el progreso de las universidades hacia lograr esta meta ha sido más lento de lo originalmente pensado. En particular, la Escuela de Ciencias de la Computación e Informática (ECCI) de la Universidad de Costa Rica (UCR) ha incorporado lentamente algunas herramientas de tecnologías de información y comunicaciones (TICs) en su proceso de enseñanza, pero este proceso ha sido lento y parcial y no se ha llevado de manera integral. Este estudio pretendió analizar el alcance del uso de las TICs en la Escuela de Ciencias de la Computación e Informática de la UCR, específicamente en los cursos del posgrado. Queríamos enumerar las razones de su poca incorporación al proceso educativo, así como brindar alguna luz sobre el impacto de su uso en la calidad de la educación

Sobrepeso e integración económica en México

ResumenLa obesidad en México y el mundo ha ido creciendo sistemáticamente, al grado que se ha convertido en una pandemia con fuertes consecuencias en padecimientos muy graves de salud pública como hipertensión, enfermedades cardiovasculares, diabetes y cáncer, todo lo cual tiene fuertes impactos en las finanzas públicas y en el crecimiento económico.En México, desde los años noventa, la obesidad y el sobrepeso han crecido de manera exponencial, mucho más que en Estados Unidos. A manera de hipótesis, sugerimos que la entrada en vigor del Tratado de Libre Comercio de América del Norte en 1994 no sólo modificó la estructura del comercio y de los flujos de capital. También gestó un cambio sustancial en los hábitos de consumo de la población, particularmente la infantil, que se manifestó en un incremento notable en el consumo de golosinas. Estos resultados emergen del análisis de la Encuesta Nacional Ingreso Gasto de los Hogares (enigh) para los años 1992 y 1996.AbstractThe obesity in Mexico and the world has been growing systematicly, to the degree that has turned into a pandemic with strong consequences into very serious sufferings of public health as hypertension, cardiovascular diseases, diabetes and cancer, everything which has strong impacts in the public finance and in the economic growth. In Mexico, from the nineties, the obesity and the overweight have grown in an exponential way, much more than in The United States. Like hypothesis, we suggest that the entry into force of the North American Free Trade Agreement in 1994 not only modified the structure of the trade and of the capital flows. Also it prepared a substantial change in the habits of consumption of the population, particularly the infantile one, which demonstrated in a notable increase in the consumption of delicacies. These results emerge of the analysis of the National Survey I deposit Expense of the Homes (enigh) for the year 1992 and 1996

SURE-tuned Bridge Regression

Consider the {$\ell_{\alpha}$} regularized linear regression, also termed Bridge regression. For $\alpha\in (0,1)$, Bridge regression enjoys several statistical properties of interest such as sparsity and near-unbiasedness of the estimates (Fan and Li, 2001). However, the main difficulty lies in the non-convex nature of the penalty for these values of $\alpha$, which makes an optimization procedure challenging and usually it is only possible to find a local optimum. To address this issue, Polson et al. (2013) took a sampling based fully Bayesian approach to this problem, using the correspondence between the Bridge penalty and a power exponential prior on the regression coefficients. However, their sampling procedure relies on Markov chain Monte Carlo (MCMC) techniques, which are inherently sequential and not scalable to large problem dimensions. Cross validation approaches are similarly computation-intensive. To this end, our contribution is a novel \emph{non-iterative} method to fit a Bridge regression model. The main contribution lies in an explicit formula for Stein's unbiased risk estimate for the out of sample prediction risk of Bridge regression, which can then be optimized to select the desired tuning parameters, allowing us to completely bypass MCMC as well as computation-intensive cross validation approaches. Our procedure yields results in a fraction of computational times compared to iterative schemes, without any appreciable loss in statistical performance. An R implementation is publicly available online at: https://github.com/loriaJ/Sure-tuned_BridgeRegression .Comment: 33 pages, 11 figure