Methods for Interpreting and Understanding Deep Neural Networks

This paper provides an entry point to the problem of interpreting a deep neural network model and explaining its predictions. It is based on a tutorial given at ICASSP 2017. It introduces some recently proposed techniques of interpretation, along with theory, tricks and recommendations, to make most efficient use of these techniques on real data. It also discusses a number of practical applications.Comment: 14 pages, 10 figure

The Impact of Market Advisory Service Recommendations on Producers' Marketing Decisions

A conceptual framework is developed which provides insight into the factors affecting the impact of market advisory service (MAS) recommendations on producer pricing decisions. Data from a survey of 656 U.S. producers reveal that the perceived performance of the MAS, the way in which MAS recommendations are delivered, as well as the match between MAS and producers' marketing philosophy, are important factors explaining the impact of MAS recommendations. Risk attitude does not affect the impact of MAS recommendations on producers' decisions, suggesting producers are more interested in the price-enhancing characteristics of MAS advice than in its risk-reducing features. Key words: market advisory services, ordered probit model, producers' marketing decisionsmarket advisory services, ordered probit model, producers' marketing decisions, Marketing,

Explaining recommendations in an interactive hybrid social recommender

Hybrid social recommender systems use social relevance from multiple sources to recommend relevant items or people to users. To make hybrid recommendations more transparent and controllable, several researchers have explored interactive hybrid recommender interfaces, which allow for a user-driven fusion of recommendation sources. In this field of work, the intelligent user interface has been investigated as an approach to increase transparency and improve the user experience. In this paper, we attempt to further promote the transparency of recommendations by augmenting an interactive hybrid recommender interface with several types of explanations. We evaluate user behavior patterns and subjective feedback by a within-subject study (N=33). Results from the evaluation show the effectiveness of the proposed explanation models. The result of post-treatment survey indicates a significant improvement in the perception of explainability, but such improvement comes with a lower degree of perceived controllability

Understanding the Role of Willingness to Cannibalize in New Service Development

The objective of the present study is to develop a model of explaining new service development behavior using the concept of willingness to cannibalize existing sales, current capabilities and prior investments. The paper is structured as follows. First, we review the literature relevant for our work. Second, we explain our conceptual model. Next, we report on the research method used and present empirical evidence from 217 service firms. We close with a discussion and recommendations for future research.

Explaining Social Recommendations to Casual Users: Design Principles and Opportunities

Recommender systems have become popular in recent years, and ordinary users are more likely to rely on such service when completing various daily tasks. The need to design and build explainable recommender interfaces is increasing rapidly. Most of the designs of such explanations are intended to reflect the underlying algorithms by which the recommendations are computed. These approaches have been shown to be useful for obtaining system transparency and trust. However, little is known about how to design explanation interfaces for causal (non-expert) users to achieve different explanatory goals. As a first step toward understanding the user interface design factors, we conducted an international (across 13 countries) online survey of 14 active users of a social recommender system. This study captures user feedback in the field and frames it in terms of design principles and opportunities

Aboriginal Education in Quebec: A Benchmarking Exercise

Quebec’s Aboriginal poverty is severe, and the large gap between Aboriginal and non-Aboriginal education levels is the most important factor in explaining it. In the report, the author examines the relationship between education levels and employment for Quebec Aboriginals. Comparing outcomes within the province’s Aboriginal identity groups to results for other Quebecers, and for Canadians overall, Richards finds that the province’s Aboriginal education outcomes rank below the Canadian average, which itself is disturbingly low. Richards makes six broad recommendations to address the crisis in Aboriginal education – in Quebec and the rest of Canada.The Education Papers, Canada, Quebec, Aboriginals, education, employment

The reluctant analyst

We estimate the dynamics of recommendations by financial analysts, uncovering the determinants of inertia in their recommendations. We provide overwhelming evidence that analysts revise recommendations reluctantly, introducing frictions to avoid frequent revisions. More generally, we characterize the sources underlying the infrequent revisions that analysts make. Publicly available data matter far less for explaining recommendation dynamics than do the recommendation frictions and the long-lived information that analysts acquire but the econometrician does not observe. Estimates suggest that analysts structure recommendations strategically to generate a profitable order flow from retail traders. We provide extensive evidence that our model describes how investors believe analysts make recommendations, and that investors value private information revealed by analysts' recommendations

Defining "We" In Environmental Advocacy

Explores the importance of language in explaining and advancing advocacy work at environmental organizations. Provides recommendations for communicating more effectively when advocating for change in environmental policy