Now we must cross a sea: remarks on transformational leadership and the Civil Rights Movement

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Negotiating with the Bandits and Endless Security Challenges in Katsina State, Nigeria (2019-2020)

The activities of criminals have been on the rise and the security situation deteriorated after negotiations between the State Government and the criminals in Nigeria. This paper assesses the context of armed banditry, cattle rustling, and kidnappings in Katsina State. The researchers adopted a cross-sectional study design and explanatory research type. A field survey was conducted in Batsari town and two villages: Zamfarawa and Bakiyawa. In-Depth Interviews (IDI) were conducted with some residents of the villages and some armed bandits. A non-probability sampling and snowballing technique were adopted to sample the research participants for the interviews. The study found that the Katsina State Government has not understand fully the security challenge and hence identified the wrong leaders of the criminals for negotiation, this is because there are three categories of criminals in the areas. This incensed some of the groups of criminals to intensify their attacks, kidnapping, and the rustling of livestock

Beyond Ads: Sequential Decision-Making Algorithms in Law and Public Policy

We explore the promises and challenges of employing sequential decision-making algorithms - such as bandits, reinforcement learning, and active learning - in law and public policy. While such algorithms have well-characterized performance in the private sector (e.g., online advertising), their potential in law and the public sector remains largely unexplored, due in part to distinct methodological challenges of the policy setting. Public law, for instance, can pose multiple objectives, necessitate batched and delayed feedback, and require systems to learn rational, causal decision-making policies, each of which presents novel questions at the research frontier. We highlight several applications of sequential decision-making algorithms in regulation and governance, and discuss areas for needed research to render such methods policy-compliant, more widely applicable, and effective in the public sector. We also note the potential risks of such deployments and describe how sequential decision systems can also facilitate the discovery of harms. We hope our work inspires more investigation of sequential decision making in law and public policy, which provide unique challenges for machine learning researchers with tremendous potential for social benefit.Comment: Version 1 presented at Causal Inference Challenges in Sequential Decision Making: Bridging Theory and Practice, a NeurIPS 2021 Worksho

The Violent and the Weak: When Dictators Care About Social Contracts

This paper explores the conditions under which compliance with a social contract establishes an equilibrium in a society. It is assumed that society consists of two groups, one of which has a comparative advantage in using violence, whereas the other one has a comparative advantage in producing a private good. Violence can be used to produce security as well as to exploit the weaker group. Yet, exploitation is limited: it reduces the incentives of the exploited group to produce the private good and increases the chances of a revolution. A social contract consists of the exchange of security against a share of the private good, produced at a high level of effort. The model not only allows the derivation of conditions for either compliance or exploitation to occur, but also sheds light on the transition from one form of government to the other. Hence, it contributes to Positive Constitutional Economics, i.e., the research program that is interested in explaining the emergence and the change of constitutions. -- Das Paper zeigt die Bedingungen auf, unter denen die Einhaltung eines Sozialvertrages ein Gleichgewicht ist. Dabei wird angenommen, daß die Gesellschaft aus zwei Gruppen besteht: Die eine hat einen komparativen Kostenvorteil bei der Anwendung von Gewalt, die andere beim Herstellen eines privaten Gutes. Gewalt kann sowohl zur Produktion von Sicherheit benutzt werden, als auch zur Ausbeutung der schwächeren Gruppe. Ausbeutung ist jedoch nur begrenzt möglich, weil sie zum einen die Anreize der ausgebeuteten Gruppe zur Produktion des privaten Gutes senkt, zum anderen die Chancen einer erfolgreichen Revolution erhöht. Der Sozialvertrag sieht den Austausch von Sicherheit gegen einen Anteil am privaten Gut vor, das auf hohem Anstrengungsniveau produziert wird. Das Modell ermöglicht es nicht nur, die Bedingungen für Sozialvertragstreue bzw. Ausbeutungsdiktatur herzuleiten, sondern beleuchtet auch den Übergang von einer Regierungsform zur anderen. So leistet es einen Beitrag zur Positiven Konstitutionenökonomik, also dem Forschungsprogramm, das die Entstehung und den Wandel von Verfassungen erklärt.self-enforcing contracts,rule of law,dictatorship,autocracy,Positive Constitutional Economics

Lack of Cross-Scale Linkages Reduces Robustness of Community-Based Fisheries Management

Community-based management and the establishment of marine reserves have been advocated worldwide as means to overcome overexploitation of fisheries. Yet, researchers and managers are divided regarding the effectiveness of these measures. The “tragedy of the commons” model is often accepted as a universal paradigm, which assumes that unless managed by the State or privatized, common-pool resources are inevitably overexploited due to conflicts between the self-interest of individuals and the goals of a group as a whole. Under this paradigm, the emergence and maintenance of effective community-based efforts that include cooperative risky decisions as the establishment of marine reserves could not occur. In this paper, we question these assumptions and show that outcomes of commons dilemmas can be complex and scale-dependent. We studied the evolution and effectiveness of a community-based management effort to establish, monitor, and enforce a marine reserve network in the Gulf of California, Mexico. Our findings build on social and ecological research before (1997–2001), during (2002) and after (2003–2004) the establishment of marine reserves, which included participant observation in >100 fishing trips and meetings, interviews, as well as fishery dependent and independent monitoring. We found that locally crafted and enforced harvesting rules led to a rapid increase in resource abundance. Nevertheless, news about this increase spread quickly at a regional scale, resulting in poaching from outsiders and a subsequent rapid cascading effect on fishing resources and locally-designed rule compliance. We show that cooperation for management of common-pool fisheries, in which marine reserves form a core component of the system, can emerge, evolve rapidly, and be effective at a local scale even in recently organized fisheries. Stakeholder participation in monitoring, where there is a rapid feedback of the systems response, can play a key role in reinforcing cooperation. However, without cross-scale linkages with higher levels of governance, increase of local fishery stocks may attract outsiders who, if not restricted, will overharvest and threaten local governance. Fishers and fishing communities require incentives to maintain their management efforts. Rewarding local effective management with formal cross-scale governance recognition and support can generate these incentives

von Neumann-Morgenstern and Savage Theorems for Causal Decision Making

Causal thinking and decision making under uncertainty are fundamental aspects of intelligent reasoning. Decision making under uncertainty has been well studied when information is considered at the associative (probabilistic) level. The classical Theorems of von Neumann-Morgenstern and Savage provide a formal criterion for rational choice using purely associative information. Causal inference often yields uncertainty about the exact causal structure, so we consider what kinds of decisions are possible in those conditions. In this work, we consider decision problems in which available actions and consequences are causally connected. After recalling a previous causal decision making result, which relies on a known causal model, we consider the case in which the causal mechanism that controls some environment is unknown to a rational decision maker. In this setting we state and prove a causal version of Savage's Theorem, which we then use to develop a notion of causal games with its respective causal Nash equilibrium. These results highlight the importance of causal models in decision making and the variety of potential applications.Comment: Submitted to Journal of Causal Inferenc

Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting

Restless and collapsing bandits are commonly used to model constrained resource allocation in settings featuring arms with action-dependent transition probabilities, such as allocating health interventions among patients [Whittle, 1988; Mate et al., 2020]. However, state-of-the-art Whittle-index-based approaches to this planning problem either do not consider fairness among arms, or incentivize fairness without guaranteeing it [Mate et al., 2021]. Additionally, their optimality guarantees only apply when arms are indexable and threshold-optimal. We demonstrate that the incorporation of hard fairness constraints necessitates the coupling of arms, which undermines the tractability, and by extension, indexability of the problem. We then introduce ProbFair, a probabilistically fair stationary policy that maximizes total expected reward and satisfies the budget constraint, while ensuring a strictly positive lower bound on the probability of being pulled at each timestep. We evaluate our algorithm on a real-world application, where interventions support continuous positive airway pressure (CPAP) therapy adherence among obstructive sleep apnea (OSA) patients, as well as simulations on a broader class of synthetic transition matrices.Comment: 27 pages, 19 figure