Privacy-preserving scoring of tree ensembles : a novel framework for AI in healthcare

Machine Learning (ML) techniques now impact a wide variety of domains. Highly regulated industries such as healthcare and finance have stringent compliance and data governance policies around data sharing. Advances in secure multiparty computation (SMC) for privacy-preserving machine learning (PPML) can help transform these regulated industries by allowing ML computations over encrypted data with personally identifiable information (PII). Yet very little of SMC-based PPML has been put into practice so far. In this paper we present the very first framework for privacy-preserving classification of tree ensembles with application in healthcare. We first describe the underlying cryptographic protocols that enable a healthcare organization to send encrypted data securely to a ML scoring service and obtain encrypted class labels without the scoring service actually seeing that input in the clear. We then describe the deployment challenges we solved to integrate these protocols in a cloud based scalable risk-prediction platform with multiple ML models for healthcare AI. Included are system internals, and evaluations of our deployment for supporting physicians to drive better clinical outcomes in an accurate, scalable, and provably secure manner. To the best of our knowledge, this is the first such applied framework with SMC-based privacy-preserving machine learning for healthcare

Valuing Ecosystem Services from Private Forests

Non-market valuation, ecosystem services, Environmental Economics and Policy,

The role of trees for sustainable management of less-favored lands: the case of eucalyptus in Ethiopia

In recent years the planting of eucalyptus trees in Ethiopia has expanded from State owned plantations to community woodlots and household compounds. In an environment suffering from severe woody biomass shortages water scarcity, erosion and land degradation, fast growing and resilient eucalyptus species perform better than most indigenous woodland and forest tree species (as well as most crops). In addition to increasing biomass and providing ground cover, the sale of eucalyptus poles and products has substantial potential to raise farm incomes, reduce poverty, increase food security and diversify smallholder-farming systems in less-favored areas of northern Ethiopia. Despite the potential for eucalyptus to improve rural livelihoods in northern Ethiopia in 1997, the regional government of Tigray imposed a ban on eucalyptus tree planting on farmlands. The regional government promotes planting of eucalyptus and other species in community woodlots, and has recently begun to allow private planting of eucalyptus on community wasteland and steep hillsides. In this paper, we review the debate about the ecological impacts of eucalyptus trees, as well as the economic factors that influence whether smallholders invest in these trees. Ex ante benefit-cost analysis based on community level survey data from Tigray illustrates that under most conditions planting eucalyptus trees yields high rates of return, well above 20% under most circumstances. The effect of variable harvest rates, the costs of decreased crop production when eucalyptus trees are planted on farmlands, and differences between administrative zones are considered relative to our base case in our rate of return estimates. The importance of fast growing tree species that can accommodate the high discount rates associated with smallholders in this region is emphasized.Tree planting., Ecology., Ethiopia., Land degradation.,

Late-successional and old-growth forests in the northeastern United States: Structure, dynamics, and prospects for restoration.

Abstract Restoration of old-growth forest structure is an emerging silvicultural goal, especially in those regions where old-growth abundance falls below the historic range of variability. However, longitudinal studies of old-growth dynamics that can inform silvicultural and policy options are few. We analyzed the change in structure, including stand density, diameter distribution, and the abundance of large live, standing dead, and downed dead trees on 58 late-successional and old-growth plots in Maine, USA, and compared these to regional data from the U.S. Forest Inventory and Analysis program. Structural dynamics on the late-successional plots reflected orderly change associated with density-dependent growth and mortality, but dynamics on the old-growth plots were more variable. Some plots experienced heavy mortality associated with beech bark disease. Diameter distributions conformed poorly to a classic exponential distribution, and did not converge toward such a distribution at the plot scale. Although large live trees showed a broad trend of increasing density in regional forests, recent harvesting patterns offset a considerable fraction of those gains, while mean diameter was static and the number of large dead trees was weakly declining. Even though forests of the northeast are aging, changes in silviculture and forest policy are necessary to accelerate restoration of old-growth structure

Evaluating the welfare effects of biodiversity on private lands: A choice modelling application

Biodiversity loss is a global problem, especially in reference to private lands. In response, we investigated whether private land biodiversity may be attained by developing incentives which include funding landholders through the provision of native trees to enhance biodiversity on their own properties. Using choice modelling, we tested this hypothesis. A typical respondent was found to be better off, in terms of welfare, if there would be a biodiversity enhancing scheme in their locality. We also found that respondents in the upper northern regions of New Zealand were relatively more receptive in supporting biodiversity enhancement programmes on their properties, compared to those residing in the southern regions of the country

Forest incomes after Uganda's forest sector reform: Are the rural poor gaining?

"Forest sector governance reform is frequently promoted as a policy tool for achieving favorable livelihood outcomes in the low income tropics. However, there is a dearth of empirical evidence to support this claim, particularly at the household level. Drawing on the case of a major forest sector governance reform implemented in Uganda in 2003, this study seeks to fill that gap. The research employs a quasi-experimental research design utilizing pre and post reform income portfolio data for a large sample of households surrounding three major forests in western Uganda; a control group is included in the design. On private forest land overseen by the decentralized District Forestry Service there has been no significant change in average annual household income from forests, and the share of total income from forests has only slightly increased. For households living adjacent to Budongo Central Forest Reserve, overseen by the parastatal National Forestry Authority, there have been significant gains in average annual household income from forests, as well as the share of total income from forests. However, increases are limited to households in the highest income quartile and are primarily attributed to the sale of illegally harvested timber. The findings from this study challenge the view that governance reforms result in favorable livelihood outcomes for the poorest. Policy makers should carefully consider the incentives facing both forestry officials and local resource users with particular attention to increasing awareness of the value of trees and forests, and facilitating legal opportunities for rural smallholders across all income categories to sustainably engage in forest product harvesting and value addition." authors' abstractforest sector reform, Decentralization, Livelihoods,

On trade-offs between timber and biodiversity

For a long time the primary aim of forestry in Sweden has been the production of timber, but in recent decades other functions, such as biodiversity, have been increasingly recognised by society. Sweden has ambitious goals for forest management, aimed at serving public interests, providing valuable timber yields and preserving biodiversity. Achieving the level of various goods that forests shall provide, under such goals, is thus rather complex. This thesis focuses on trade-offs between production of timber and the maintenance of biodiversity in forests, and the effects of information on benefits, costs and biological traits. In Paper I the benefit of forest land protection was estimated based on a nation wide contingent valuation survey. Paper II examined and compared, through survey data, the attitudes among private forest owners and forest officers. Papers III and IV used data from a field inventory in old growth forests (>110 years of age) of Norway spruce (Picea abies [L.] Karst.) in the county of Gävleborg, Sweden. In Paper III the relative importance of information about costs and biological traits in reserve selection was examined. In Paper IV the cost-efficiency of different strategies for setting aside forests, using different biodiversity targets, were analysed. The thesis revealed a positive willingness to pay for forest land protection among Swedish citizens, and also a positive attitude among private forest owners to biodiversity as well as timber production. The views of forest owners and forest officers did not always coincide. Moreover, the relative importance of including data on costs and conservation benefits depended on how the conservation goal of the reserve network was formulated. There was also a difference in cost-effectiveness between different nature conservation strategies and biodiversity targets. The results emphasise the importance of achieving cost-effective solutions in biodiversity conservation through the proper use of information about biological traits and costs, as well as considering values and attitudes held by different interest groups in society

Incentive Payment Programs for Environmental Protection: A Framework for Eliciting and Estimating Landowners' Willingness to Participate

This paper considers the role of incentive payment programs in eliciting, estimating, and predicting landowners’ conservation enrollments. Using both program participation and the amount of land enrolled, we develop two econometric approaches for predicting enrollments. The first is a multivariate censored regression model that handles zero enrollments and heterogeneity in the opportunity cost of enrollments by combining an inverse hyperbolic sine transformation of enrollments with alternative-specific correlation and random parameters. The second is a beta-binomial model, which recognizes that in practice elicited enrollments are essentially integer valued. We apply these approaches to Finland, where the protection of private nonindustrial forests is an important environmental policy problem. We compare both econometric approaches via cross-validation and find that the beta-binomial model predicts as well as the multivariate censored model yet has fewer parameters. The beta-binomial model also facilitates policy predictions and simulations, which we use to illustrate the framework.protection, endangered, voluntary, incentive, tobit, beta-binomial, stated preferences

Secure Outsourced Computation on Encrypted Data

Homomorphic encryption (HE) is a promising cryptographic technique that supports computations on encrypted data without requiring decryption first. This ability allows sensitive data, such as genomic, financial, or location data, to be outsourced for evaluation in a resourceful third-party such as the cloud without compromising data privacy. Basic homomorphic primitives support addition and multiplication on ciphertexts. These primitives can be utilized to represent essential computations, such as logic gates, which subsequently can support more complex functions. We propose the construction of efficient cryptographic protocols as building blocks (e.g., equality, comparison, and counting) that are commonly used in data analytics and machine learning. We explore the use of these building blocks in two privacy-preserving applications. One application leverages our secure prefix matching algorithm, which builds on top of the equality operation, to process geospatial queries on encrypted locations. The other applies our secure comparison protocol to perform conditional branching in private evaluation of decision trees. There are many outsourced computations that require joint evaluation on private data owned by multiple parties. For example, Genome-Wide Association Study (GWAS) is becoming feasible because of the recent advances of genome sequencing technology. Due to the sensitivity of genomic data, this data is encrypted using different keys possessed by different data owners. Computing on ciphertexts encrypted with multiple keys is a non-trivial task. Current solutions often require a joint key setup before any computation such as in threshold HE or incur large ciphertext size (at best, grows linearly in the number of involved keys) such as in multi-key HE. We propose a hybrid approach that combines the advantages of threshold and multi-key HE to support computations on ciphertexts encrypted with different keys while vastly reducing ciphertext size. Moreover, we propose the SparkFHE framework to support large-scale secure data analytics in the Cloud. SparkFHE integrates Apache Spark with Fully HE to support secure distributed data analytics and machine learning and make two novel contributions: (1) enabling Spark to perform efficient computation on large datasets while preserving user privacy, and (2) accelerating intensive homomorphic computation through parallelization of tasks across clusters of computing nodes. To our best knowledge, SparkFHE is the first addressing these two needs simultaneously