Agriculture & Data Privacy: I Want A Hipaa(Potamus) For Christmas . . . Maybe

Technology advancements make life, work, and play easier and more enjoyable in many ways. Technology issues are also the cause of many headaches and dreams of living out the copier destruction scene from the movie “Office Space.” Whether it be user error or technological error, one key technology issue on many minds right now is how all the data produced every second of every day, in hundreds of different ways, is used by those that collect it. How much data are we talking about here? In 2018, the tech company Domo estimated that by 2020 “1.7 MB of data will be created every second” for every single person on Earth. In 2019, Domo’s annual report noted that “Americans use 4,416,720 GB of internet data including 188,000,000 emails, 18,100,000 texts and 4,497,420 Google searches every single minute.” And this was before the pandemic of 2020, which saw reliance on remote technology and the internet skyrocket. It is not just social media and working from home that generates data—the “Internet of Things” (“IoT”) is expanding exponentially. From our homes (smart appliances and thermostats), to entertainment (smart speakers and tablets), to what we wear (smartwatches and fitness devices), we are producing data constantly. Over 30 billion devices currently make up the IoT, and that number will double by 2025. The IoT is roughly defined as “devices—from simple sensors to smartphones and wearables—connected together.” That connection allows the devices to “talk” to each other across networks that stretch across the world, sharing information that in turn can be analyzed (alone or combined with data from other users) in ways that may be beneficial to the user or the broader economy. The key word in that last sentence is “may.” When it comes to the data that individuals and businesses across the world produce every second of every day, some of it—perhaps most of it—could be used in ways that are not beneficial to the user or the entire economy. Some data types can be used to cause harm in obvious ways, such as personal identifying information in cases of identity theft. While some data types may seem innocuous or harmful when viewed on their own, when combined with other data from the same user or even other users, it can be used in a wide variety of ways. While I find it beneficial to know how many steps I take in a day or how much time I sleep at night, I am not the only individual or entity with access to that information. The company that owns the device I wear also takes that information and uses it in ways that are beyond my control. Why would a company do that? In many instances, “[t]he data generated by the Internet of Things provides businesses with a wealth of information that—when properly collected, stored, and processed—gives businesses a depth of insight into user behavior never before seen.” Data security and privacy in general are issues that all companies manage as they work to protect the data we provide. Some types of data receive heightened protections, as discussed below, because they are viewed as personal, as private, or as potentially dangerous since unauthorized access to them could cause harm to the user/owner. Some states and countries have taken a step further, focusing not on industry-related data that needs particular types of protection, but in-stead looking at an individual’s overall right to privacy, particularly on the internet. Those protections are summarized below. It makes sense, you might say, to worry about financial or healthcare data remaining private and to not want every website you have ever visited to keep a file of information on you. But why might we care about the use of data in agricultural operations? Depending on who you ask, the answer may be that agricultural data needs no more care or concern than any other type of business data. Some argue that the use of “Big Data” in agriculture provides opportunities for smaller operations and shareholders. These opportunities include increased power in a market driven for many years by the mantra “bigger is better” and increased production of food staples across the world—both in a more environmentally-friendly fashion. While the benefits of technology and Big Data in the agricultural sector unarguably exist, questions remain as to how to best manage data privacy concerns in an industry where there is little specific law or regulation tied to collection, use, and ownership of this valuable agricultural production data. In the following pages, this Article discusses what types of data are currently being gathered in the agricultural sector and how some of that data can and is being used. In addition, it focuses on unique considerations tied to the use of agricultural data and why privacy concerns continue to increase for many producers. As the Article looks at potential solutions to privacy concerns, it summarizes privacy-related legislation that currently exists and ends by looking at whether any of the current privacy-related laws might be used or adapted within the agricultural sector to address potential misuse of agricultural data

The Demarcation of Land and the Role of Coordinating Institutions

This paper examines the economic effects of the two dominant land demarcation systems, metes and bounds (MB) and the rectangular system (RS). Under MB property is demarcated by its perimeter as indicated by natural features and human structures and linked to surveys within local political jurisdictions. Under RS land demarcation is governed by a common grid with uniform square shapes, sizes, alignment, and geographically-based addresses. In the U.S. MB is used principally in the original 13 states, Kentucky, and Tennessee. The RS is found elsewhere under the Land Ordinance of 1785 that divided federal lands into square-mile sections. We develop an economic framework for examining land demarcation systems and draw predictions. Our empirical analysis focuses on a 39-county area of Ohio where both MB and RS were used in adjacent areas as a result of exogenous historical factors. The results indicate that topography influences parcel shape and size under a MB system; that parcel shapes are aligned under the RS; and that the RS is associated with higher land values, more roads, more land transactions, and fewer legal disputes than MB, all else equal. The comparative limitations of MB appear to have had negative long-term effects on land values and economic activity in the sample area.

The law is spider’s web: an assessment of illegal deforestation in the Argentine Dry Chaco ten years after the enactment of the “Forest Law”

Deforestation control is one of the major challenges worldwide. The aim of this study was to analyse deforestation under the Forest Law in the Argentine Dry Chaco ecoregion a decade after its enactment and to assess compliance with forest protection standards in this region. For this purpose, we overlapped the provincial land zoning maps with an annual plot level deforestation database and, for some provinces, with the rural cadastral cartography. Deforestation exceeding the values allowed by the Forest Law and the provincial zonings during this period totalized 722,782 ha (28% of the total deforested area in this period), of which 59,732 ha were deforested in high conservation value areas, 644,396 ha in medium conservation value areas and 18,654 ha in low conservation value areas. While Santiago del Estero was the province with the highest deforested area in medium conservation value areas, Córdoba was the province with the highest deforested area in high conservation value areas. Our results are an important step towards identifying discrepancies between the legal objectives and the observed results and represent an input to think about solutions to improve the environmental governance of the region

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

Unmanning the Police Manhunt: Vertical Security as Pacification

This article provides a critique of military aerial drones being “repurposed” as domestic security technologies. Mapping this process in regards to domestic policing agencies in the United States, the case of police drones speaks directly to the importation of actual military and colonial architectures into the routine spaces of the “homeland”, disclosing insidious entwinements of war and police, metropole and colony, accumulation and securitization. The “boomeranging” of military UAVs is but one contemporary example how war power and police power have long been allied and it is the logic of security and the practice of pacification that animates both. The police drone is but one of the most nascent technologies that extends or reproduces the police’s own design on the pacification of territory. Therefore, we must be careful not to fetishize the domestic police drone by framing this development as emblematic of a radical break from traditional policing mandates – the case of police drones is interesting less because it speaks about the militarization of the police, which it certainly does, but more about the ways in which it accentuates the mutual mandates and joint rationalities of war abroad and policing at home. Finally, the paper considers how the animus of police drones is productive of a particular form of organized suspicion, namely, the manhunt. Here, the “unmanning” of police power extends the police capability to not only see or know its dominion, but to quite literally track, pursue, and ultimately capture human prey

Modelling the intelligence requirements and priorities process: the US response to the Rwandan genocide

Copyright © 2023 The Author(s). In the US, national security outcomes tend to be categorised as either the responsibility of the intelligence or policy community. Few discuss systemic outcomes emanating from the requirements and priorities (R&P) process, a top-level collaborative effort that determines national security objectives and establishes the means to address them. Here, a holistic model is introduced to examine the R&P process alongside the binary functions of intelligence and policy, and tested against two mandates of the US response to the Rwandan genocide: evacuation of American expats, and broader intervention. Such macroscopic investigations can better identify the root causes of national security outcomes