DISCOVER DATA ACTIVISM

Introduction I actually enjoy debating politics — especially with people who come in hot on emotion but light on evidence. You’d think they’d conserve their energy once they realize I don’t tire out in arguments; I get sharper. My baseline rule is simple: I’m not interested in feelings — mine or yours. Show me independently verifiable evidence. That’s usually the moment the conversation shifts from substance to name-calling, and eventually it fades out. Recently, though, som

I. Political Rhetoric and Social Division Political rhetoric has measurable effects on democratic trust and social cohesion. Research by the Pew Research Center documents increasing political polarization during the Trump era, with partisan hostility reaching historic highs and trust in institutions declining significantly.¹ Critics argue that Trump’s rhetoric — particularly regarding immigrants, political opponents, and media institutions — intensified social division, thoug

I. Political Rhetoric and Social Division Political rhetoric shapes public perception, institutional trust, and social cohesion. Scholars note that polarizing political language can: Increase distrust in democratic institutions Heighten social conflict Normalize extreme political framing While rhetoric analysis is inherently interpretive, critics argue that Trump’s political messaging has often relied on strong antagonistic framing toward opponents, immigrants, and minority g

I) Possible Constructive Uses But Still Invasive A) Smart Home Automation — The Helpful Side If AI can interact with local devices, it could: Control smart lights, thermostats, appliances, TVs, speakers Coordinate security cameras or sensors Optimize energy usage or routines This is already happening through Internet-of-Things (IoT) ecosystems where AI processes device data locally (“edge AI”) to reduce cloud data sharing while improving responsiveness. Example:AI adjusting t

Overview A well-crafted estate plan always includes a will. Even when trusts, beneficiary designations, or joint ownership play a primary role, the will remains the legal foundation that ensures a person’s final wishes are honored. For estate planning attorneys—and for anyone seeking to understand how estate plans actually work—grasping the purpose, structure, and legal requirements of wills is essential. This article provides a practical, high-level guide to wills: what they

Introduction Artificial intelligence systems increasingly make decisions impacting human welfare, yet many have exhibited unfair biases and disparities in outcomes [1] . To address this, we propose a justice-oriented AI design  that draws on John Rawls’ Theory of Justice  and uses Neural Architecture Search (NAS)  to embed fairness into the very structure of AI models. The core idea is to optimize worst-case utility  across demographic groups – as if a decision-maker were act

Stop Using Our Military As Thieves A modern economy is an information system. Markets are the dashboards. Prices are the signals. And wealth, especially billionaire wealth, is what happens when the system’s signals compound in one direction for long enough. By that measure, 2025 reads like a record year for the very top —not as a moral claim, but as a measurable outcome. UBS reports that global billionaire wealth reached an all-time high in 2025 (about $15.8 trillion, up 13%)

Introduction This analysis compares ten advanced democracies—Sweden, Norway, Finland, Denmark, Iceland, Germany, the Netherlands, France, Canada, and the United States—across twelve widely recognized quality-of-life metrics. Drawing on the most recent international data from institutions such as the United Nations, OECD, World Bank, Freedom House, Yale’s Environmental Performance Index, and the World Happiness Report, the rankings aim to capture how effectively each country c

Proposition 1 (Rawlsian Maximin as a Scalar Optimization Objective)   Let G be a finite set of groups and let m_g: Θ → R be a real-valued performance function for group g ∈ G, where θ ∈ Θ denotes the parameters of a model or architecture.   Define the Rawlsian performance of θ as: R(θ) = min_{g∈G} m_g(θ).   Then maximizing Rawlsian performance, max_{θ∈Θ} R(θ), is equivalent to the constrained optimization problem: max_{θ,t} t subject to m_g(θ) ≥ t for all g ∈ G.   In particul

Voting in the United States is administered at the state and local level , which means registration rules, deadlines, and voting methods vary depending on where you live. To ensure accuracy, it is important to rely on official government sources  rather than social media or third-party summaries. Step 1: Find Your State’s Official Election Office The most reliable starting point is Vote.gov , the official federal portal for election information. Visit: https://vote.gov Select

Below is a civic—not partisan—essay designed to persuade no one toward any candidate or ideology , but toward participation itself . It is framed for educated readers, grounded in constitutional structure and democratic theory, and written to be compelling without being targeted or tailored to any demographic group. Why Voting Still Matters—Even When You’re Tired, Cynical, or Disappointed Democracy does not fail all at once. It erodes quietly, through disuse. The right to vo

Artificial Intelligence (AI) systems increasingly shape decisions in employment, lending, healthcare, criminal justice, and other vital domains. These systems must not only be intelligent but also just – their actions should be ethical towards all human beings and defensible as fair by anyone affected. This article proposes a comprehensive framework for “ethical by design” AI by combining advances in Neural Architecture Search (NAS) technology with the philosophical principal

Abstract Artificial intelligence (AI) systems increasingly make high-stakes decisions in areas ranging from finance and employment to criminal justice. Ensuring these algorithmic decisions are fair and ethical  has become a pressing concern for policymakers and technologists alike. This Article explores a novel interdisciplinary approach to algorithmic fairness  by combining Neural Architecture Search  (NAS) technology with John Rawls’s conception of justice as fairness . NAS

I. Introduction & Scope Over the past five decades, the United States and a group of advanced social-democratic nations have taken fundamentally different approaches to criminal justice . While the U.S. has emphasized deterrence, long sentences, and incapacitation, many peer democracies—particularly in Northern and Western Europe—have adopted rehabilitative and reintegrative models  grounded in proportional punishment, social support, and post-release reintegration. This pape

Introduction and Health System Overview The United States stands out among high-income nations for lacking universal health coverage , whereas countries like Sweden, Norway, Finland, Denmark, Iceland, Germany, the Netherlands, France, Spain, Portugal, Canada, and New Zealand all achieved universal or near-universal coverage decades ago. For example, New Zealand established a public health system in the late 1930s (≈85 years ago), Canada in the 1960s (≈60 years ago), and many

I. Executive Summary The advent of Artificial Intelligence (AI) marks a pivotal moment in the evolution of learning, presenting both unprecedented opportunities and significant challenges. This report outlines a comprehensive 3-day, 18-hour course designed to equip learners with the strategic competencies required to harness AI not as a shortcut, but as a powerful amplifier for intellectual growth. The core philosophy underpinning this program is "Learn Faster, Not Think Less

Figure 1 There is nothing in The Big Beautiful Bill about providing benefits to people here illegally. There is nothing in The Big Beautiful Bill to address waste or fraud. The Bill just performs across the board cuts to America's poor, elderly, and disabled. Here is what is actually in the Bill. Of course, you can Read The Bill yourself now. We all can we have AI. Title II – Summary Figure 2 This title provides sweeping increases in funding across nearly every operational an

Artificial intelligence isn’t “coming to” business and law—it’s already embedded in them. It drafts. It predicts. It hires. It prices. It recommends medical care. It decides who gets a loan, who gets flagged, and who gets fired. And because AI systems increasingly act  (or appear to act) with autonomy, the legal system is being forced to answer a blunt question: When an algorithm causes harm, who pays—and under what theory? What follows is a practical, lawyer-friendly map of