Paper by Susan Ariel Aaronson: “In the twenty-first century, data became the subject of national strategy. This paper examines these visions and strategies to better understand what policy makers hope to achieve. Data is different from other inputs: it is plentiful, easy to use and can be utilized and shared by many different people without being used up. Moreover, data can be simultaneously a commercial asset and a public good. Various types of data can be analyzed to create new products and services or to mitigate complex “wicked” problems that transcend generations and nations (a public good function). However, an economy built on data analysis also brings problems — firms and governments can manipulate or misuse personal data, and in so doing undermine human autonomy and human rights. Given the complicated nature of data and its various types (for example, personal, proprietary, public, and so on), a growing number of governments have decided to outline how they see data’s role in the economy and polity. While it is too early to evaluate the effectiveness of these strategies, policy makers increasingly recognize that if they want to build their country’s future on data, they must also focus on trust….(More)”.
How We Can Encode Human Rights In The Blockchain
Essay by Nathan Schneider: “Imagine there is a new decentralized finance app quietly spreading around the world that’s like a payday lender from hell. Call it DevilsBridge. Rather than getting it from the App Store, you access its blockchain contracts directly, using a Web browser with a crypto-wallet plugin. DevilsBridge provides small loans in cryptocurrency that “bridge” people to the next paycheck. The interest rates are far below those of conventional payday lenders, which is life-changing for many users.
But if the payments go unpaid, they grow. They balloon. They reach multiples upon multiples of the principal. As time goes on, pressure ratchets up on borrowers, who become notorious for undertaking desperate, violent crimes to pay back their exorbitant debts. The deal, after all, is that if a debt reaches the magic threshold of $1 million, the debtor becomes a target. A private market of poison-dart-shooting drones receives a bounty to assassinate the mega-debtors.
Anywhere there are laws, of course, this is all wildly illegal. But nobody knows who created DevilDAO, the decentralized autonomous organization that operates DevilsBridge, or who its members are. The identities of the drone owners also hide behind cryptographic gibberish. Sometimes local police can trace the drones back to their bases, or investigators can trace a DevilDAO member’s address to a real person. But in most places where the assassinations happen, authorities are ill-equipped for airborne chases or scrutinizing blockchain analytics.
This may sound like a cartoonish scenario, but it’s freshly plausible thanks to the advent of decentralized, autonomous systems on blockchains. Ethereum co-founder Vitalik Buterin jokingly nodded to such dystopian possibilities in early 2014, when he listed possible uses for his proposed blockchain, from crop insurance to decentralized social networks — or perhaps, he said as he walked away from the mic, it could allow for the creation of Skynet, the robot intelligence in the “Terminator” movies that tries to exterminate the human race.
The potential for blockchain-enabled human-rights abuses is real. At the same time, these technologies introduce new ways of encoding and enforcing rights. Imagine the blockchain that DevilsBridge runs on introduces a software update. It bans any smart contract that kills humans. An anonymous investigator presents evidence of what the app is doing, and an anonymous jury confirms its validity; instantly, the contracts for DevilsBridge and DevilDAO no longer function…(More)”.
AI Ethics: Global Perspectives
New Course Modules: “A Cybernetics Approach to Ethical AI Design” explores the relationship between cybernetics and AI ethics, and looks at how cybernetics can be leveraged to reframe how we think about and how we undertake ethical AI design. This module, by Ellen Broad, Associate Professor and Associate Director at the Australian National University’s School of Cybernetics, is divided into three sections, beginning with an introduction to cybernetics. Following that, we explore different ways of thinking about AI ethics, before concluding by bringing the two concepts together to understand a new approach to ethical AI design.
How should organizations put AI ethics and responsible AI into practice? Is the answer AI ethics principles and AI ethics boards or should everyone developing AI systems become experts in ethics? In “An Ethics Model for Innovation: The PiE (Puzzle-solving in Ethics) Model”, Cansu Canca, Founder and Director of the AI Ethics Lab, presents the model developed and employed at AI Ethics Lab: The Puzzle-solving in Ethics (PiE) Model. The PiE Model is a comprehensive and structured practice framework for organizations to integrate ethics into their operations as they develop and deploy AI systems. The PiE Model aims to make ethics a robust and integral part of innovation and enhance innovation through ethical puzzle-solving.
Nuria Oliver, Co-Founder and Scientific Director of the ELLIS Alicante Unit, presents “Data Science against COVID-19: The Valencian Experience”. In this module, we explore the ELLIS Alicante Foundation’s Data-Science for COVID-19 team’s work in the Valencian region of Spain. The team was founded in response to the pandemic in March 2020 to assist policymakers in making informed, evidence-based decisions. The team tackles four different work areas: modeling human mobility, building computational epidemiological models, predictive models on the prevalence of the disease, and operating one of the largest online citizen surveys related to COVID-19 in the world. This lecture explains the four work streams and shares lessons learned from their work at the intersection between data, AI, and the pandemic…(More)”.
Dynamic World
About: “The real world is as dynamic as the people and natural processes that shape it. Dynamic World is a near realtime 10m resolution global land use land cover dataset, produced using deep learning, freely available and openly licensed. It is the result of a partnership between Google and the World Resources Institute, to produce a dynamic dataset of the physical material on the surface of the Earth. Dynamic World is intended to be used as a data product for users to add custom rules with which to assign final class values, producing derivative land cover maps.
Key innovations of Dynamic World
- Near realtime data. Over 5000 Dynamic World image are produced every day, whereas traditional approaches to building land cover data can take months or years to produce. As a result of leveraging a novel deep learning approach, based on Sentinel-2 Top of Atmosphere, Dynamic World offers global land cover updating every 2-5 days depending on location.
- Per-pixel probabilities across 9 land cover classes. A major benefit of an AI-powered approach is the model looks at an incoming Sentinel-2 satellite image and, for every pixel in the image, estimates the degree of tree cover, how built up a particular area is, or snow coverage if there’s been a recent snowstorm, for example.
- Ten meter resolution. As a result of the European Commission’s Copernicus Programme making European Space Agency Sentinel data freely and openly available, products like Dynamic World are able to offer 10m resolution land cover data. This is important because quantifying data in higher resolution produces more accurate results for what’s really on the surface of the Earth…(More)”.
Beyond Data: Human Rights, Ethical and Social Impact Assessment in AI
Open Access book by Alessandro Mantelero: “…focuses on the impact of Artificial Intelligence (AI) on individuals and society from a legal perspective, providing a comprehensive risk-based methodological framework to address it. Building on the limitations of data protection in dealing with the challenges of AI, the author proposes an integrated approach to risk assessment that focuses on human rights and encompasses contextual social and ethical values.
The core of the analysis concerns the assessment methodology and the role of experts in steering the design of AI products and services by business and public bodies in the direction of human rights and societal values.
Taking into account the ongoing debate on AI regulation, the proposed assessment model also bridges the gap between risk-based provisions and their real-world implementation.
The central focus of the book on human rights and societal values in AI and the proposed solutions will make it of interest to legal scholars, AI developers and providers, policy makers and regulators…(More)”.
Global Struggle Over AI Surveillance
Report by the National Endowment for Democracy: “From cameras that identify the faces of passersby to algorithms that keep tabs on public sentiment online, artificial intelligence (AI)-powered tools are opening new frontiers in state surveillance around the world. Law enforcement, national security, criminal justice, and border management organizations in every region are relying on these technologies—which use statistical pattern recognition, machine learning, and big data analytics—to monitor citizens.
What are the governance implications of these enhanced surveillance capabilities?
This report explores the challenge of safeguarding democratic principles and processes as AI technologies enable governments to collect, process, and integrate unprecedented quantities of data about the online and offline activities of individual citizens. Three complementary essays examine the spread of AI surveillance systems, their impact, and the transnational struggle to erect guardrails that uphold democratic values.
In the lead essay, Steven Feldstein, a senior fellow at the Carnegie Endowment for International Peace, assesses the global spread of AI surveillance tools and ongoing efforts at the local, national, and multilateral levels to set rules for their design, deployment, and use. It gives particular attention to the dynamics in young or fragile democracies and hybrid regimes, where checks on surveillance powers may be weakened but civil society still has space to investigate and challenge surveillance deployments.
Two case studies provide more granular depictions of how civil society can influence this norm-shaping process: In the first, Eduardo Ferreyra of Argentina’s Asociación por los Derechos Civiles discusses strategies for overcoming common obstacles to research and debate on surveillance systems. In the second, Danilo Krivokapic of Serbia’s SHARE Foundation describes how his organization drew national and global attention to the deployment of Huawei smart cameras in Belgrade…(More)”.
Citizens of Worlds: Open-Air Toolkits for Environmental Struggle
Book by Jennifer Gabrys: “Modern environments are awash with pollutants churning through the air, from toxic gases and intensifying carbon to carcinogenic particles and novel viruses. The effects on our bodies and our planet are perilous. Citizens of Worlds is the first thorough study of the increasingly widespread use of digital technologies to monitor and respond to air pollution. It presents practice-based research on working with communities and making sensor toolkits to detect pollution while examining the political subjects, relations, and worlds these technologies generate. Drawing on data from the Citizen Sense research group, which worked with communities in the United States and the United Kingdom to develop digital-sensor toolkits, Jennifer Gabrys argues that citizen-oriented technologies promise positive change but then collide with entrenched and inequitable power structures. She asks: Who or what constitutes a “citizen” in citizen sensing? How do digital sensing technologies enable or constrain environmental citizenship? Spanning three project areas, this study describes collaborations to monitor air pollution from fracking infrastructure, to document emissions in urban environments, and to create air-quality gardens. As these projects show, how people respond to, care for, and struggle to transform environmental conditions informs the political subjects and collectives they become as they strive for more breathable worlds….(More)”.
Algorithmic monoculture and social welfare
Paper by Jon Kleinberg and Manish Raghavan: “As algorithms are increasingly applied to screen applicants for high-stakes decisions in employment, lending, and other domains, concerns have been raised about the effects of algorithmic monoculture, in which many decision-makers all rely on the same algorithm. This concern invokes analogies to agriculture, where a monocultural system runs the risk of severe harm from unexpected shocks. Here, we show that the dangers of algorithmic monoculture run much deeper, in that monocultural convergence on a single algorithm by a group of decision-making agents, even when the algorithm is more accurate for any one agent in isolation, can reduce the overall quality of the decisions being made by the full collection of agents. Unexpected shocks are therefore not needed to expose the risks of monoculture; it can hurt accuracy even under “normal” operations and even for algorithms that are more accurate when used by only a single decision-maker. Our results rely on minimal assumptions and involve the development of a probabilistic framework for analyzing systems that use multiple noisy estimates of a set of alternatives…(More)”.
Impediment of Infodemic on Disaster Policy Efficacy: Insights from Location Big Data
Paper by Xiaobin Shen, Natasha Zhang Foutz, and Beibei Li: “Infodemics impede the efficacy of business and public policies, particularly in disastrous times when high-quality information is in the greatest demand. This research proposes a multi-faceted conceptual framework to characterize an infodemic and then empirically assesses its impact on the core mitigation policy of a latest prominent disaster, the COVID-19 pandemic. Analyzing a half million records of COVID-related news media and social media, as well as .2 billion records of location data, via a multitude of methodologies, including text mining and spatio-temporal analytics, we uncover a number of interesting findings. First, the volume of the COVID information incurs an inverted-U-shaped impact on individuals’ compliance with the lockdown policy. That is, a smaller volume encourages the policy compliance, whereas an overwhelming volume discourages compliance, revealing negative ramifications of excessive information about a disaster. Second, novel information boosts policy compliance, signifying the value of offering original and distinctive, instead of redundant, information to the public during a disaster. Third, misinformation exhibits a U-shaped influence unexplored by the literature, deterring policy compliance until a larger amount surfaces, diminishing informational value, escalating public uncertainty. Overall, these findings demonstrate the power of information technology, such as media analytics and location sensing, in disaster management. They also illuminate the significance of strategic information management during disasters and the imperative need for cohesive efforts across governments, media, technology platforms, and the general public to curb future infodemics…(More)”.
How can data stop homelessness before it starts?
Article by Andrea Danes and Jessica Chamba: “When homelessness in Maidstone, England, soared by 58% over just five years, the Borough Council sought to shift its focus from crisis response to building early-intervention and prevention capacity. Working with EY teams and our UK technology partner, Xantura, the council created and implemented a data-focused tool — called OneView — that enabled the council to tackle their challenges in a new way.
Specifically, OneView’s predictive analytic and natural language generation capabilities enabled participating agencies in Maidstone to bring together their data to identify residents who were at risk of homelessness, and then to intervene before they were actually living on the street. In the initial pilot year, almost 100 households were prevented from becoming homeless, even as the COVID-19 pandemic took hold and grew. And, overall, the rate of homelessness fell by 40%.
As evidenced by the Maidstone model, data analytics and predictive modeling will play an indispensable role in enabling us to realize a very big vision — a world in which everyone has a reliable roof over their heads.
Against that backdrop, it’s important to stress that the roadmap for preventing homelessness has to contain components beyond just better avenues for using data. It must also include shrewd approaches for dealing with complex issues such as funding, standards, governance, cultural differences and informed consent to permit the exchange of personal information, among others. Perhaps most importantly, the work needs to be championed by organizational and governmental leaders who believe transformative, systemic change is possible and are committed to achieving it.
Introducing the Smart Safety Net
To move forward, human services organizations need to look beyond modernizing service delivery to transforming it, and to evolve from integration to intuitive design. New technologies provide opportunities to truly rethink and redesign in ways that would have been impossible in the past.
A Smart Safety Net can shape a bold new future for social care. Doing so will require broad, fundamental changes at an organizational level, more collaboration across agencies, data integration and greater care co-ordination. At its heart, a Smart Safety Net entails:
- A system-wide approach to addressing the needs of each individual and family, including pooled funding that supports coordination so that, for example, users in one program are automatically enrolled in other programs for which they are eligible.
- Human-centered design that genuinely integrates the recipients of services (patients, clients, customers, etc.), as well as their experiences and insights, into the creation and implementation of policies, systems and services that affect them.
- Data-driven policy, services, workflows, automation and security to improve processes, save money and facilitate accurate, real-time decision-making, especially to advance the overarching priority of nearly every program and service; that is, early intervention and prevention.
- Frontline case workers who are supported and empowered to focus on their core purpose. With a lower administrative burden, they are able to invest more time in building relationships with vulnerable constituents and act as “coaches” to improve people’s lives.
- Outcomes-based commissioning of services, measured against a more holistic wellbeing framework, from an ecosystem of public, private and not-for-profit providers, with government acting as system stewards and service integrators…(More)”.