How can I logically manage to deceive myself? Buddhist thought offers a way out of the philosophical paradox

When the United States entered the Gilded Age after the Civil War, argues cultural historian Christopher Benfey, the nation lost its philosophical moorings and looked eastward to “Old Japan,” with its seemingly untouched indigenous culture, for balance and perspective. Japan, meanwhile, was trying to reinvent itself as a more cosmopolitan, modern state, ultimately transforming itself, in the course of twenty-five years, from a feudal backwater to an international power. This great wave of historical and cultural reciprocity between the two young nations, which intensified during the late 1800s, brought with it some larger-than-life personalities, as the lure of unknown foreign cultures prompted pilgrimages back and forth across the Pacific.In The Great Wave, Benfey tells the story of the tightly knit group of nineteenth-century travelers—connoisseurs, collectors, and scientists—who dedicated themselves to exploring and preserving Old Japan. As Benfey writes, “A sense of urgency impelled them, for they were convinced—Darwinians that they were—that their quarry was on the verge of extinction.”These travelers include Herman Melville, whose Pequod is “shadowed by hostile and mysterious Japan”; the historian Henry Adams and the artist John La Farge, who go to Japan on an art-collecting trip and find exotic adventures; Lafcadio Hearn, who marries a samurai’s daughter and becomes Japan’s preeminent spokesman in the West; Mabel Loomis Todd, the first woman to climb Mt. Fuji; Edward Sylvester Morse, who becomes the world’s leading expert on both Japanese marine life and Japanese architecture; the astronomer Percival Lowell, who spends ten years in the East and writes seminal works on Japanese culture before turning his restless attention to life on Mars; and President (and judo enthusiast) Theodore Roosevelt. As well, we learn of famous Easterners come West, including Kakuzo Okakura, whose The Book of Tea became a cult favorite, and Shuzo Kuki, a leading philosopher of his time, who studied with Heidegger and tutored Sartre.Finally, as Benfey writes, his meditation on cultural identity “seeks to capture a shared mood in both the Gilded Age and the Meiji Era, amid superficial promise and prosperity, of an overmastering sense of precariousness and impending peril.”

Recently, LLM-based agents have been all the rage – with projects like AutoGPT showing how easy it is to wrap an LLM in a simple agentic loop and prompt it to achieve real-world tasks. More generally, we can think about the class of ‘scaffolded’ 1 LLM systems – which wrap...

Even after fine-tuning and reinforcement learning, large language models (LLMs) can be difficult, if not impossible, to control reliably with prompts alone. We propose a new inference-time approach to enforcing syntactic and semantic constraints on the outputs of LLMs, called sequential Monte Carlo (SMC) steering. The key idea is to specify language generation tasks as posterior inference problems in a class of discrete probabilistic sequence models, and replace standard decoding with sequential Monte Carlo inference. For a computational cost similar to that of beam search, SMC can steer LLMs to solve diverse tasks, including infilling, generation under syntactic constraints, and prompt intersection. To facilitate experimentation with SMC steering, we present a probabilistic programming library, LLaMPPL (https://github.com/probcomp/LLaMPPL), for concisely specifying new generation tasks as language model probabilistic programs, and automating steering of LLaMA-family Transformers.

Predicting future outcomes is a prevalent application of machine learning in social impact domains. Examples range from predicting student success in education to predicting disease risk in healthcare. Practitioners recognize that the ultimate goal is not just to predict but to act effectively. Increasing evidence suggests that relying on outcome predictions for downstream interventions may not have desired results. In most domains there exists a multitude of possible interventions for each individual, making the challenge of taking effective action more acute. Even when causal mechanisms connecting the individual's latent states to outcomes is well understood, in any given instance (a specific student or patient), practitioners still need to infer -- from budgeted measurements of latent states -- which of many possible interventions will be most effective for this individual. With this in mind, we ask: when are accurate predictors of outcomes helpful for identifying the most suitable intervention? Through a simple model encompassing actions, latent states, and measurements, we demonstrate that pure outcome prediction rarely results in the most effective policy for taking actions, even when combined with other measurements. We find that except in cases where there is a single decisive action for improving the outcome, outcome prediction never maximizes "action value", the utility of taking actions. Making measurements of actionable latent states, where specific actions lead to desired outcomes, considerably enhances the action value compared to outcome prediction, and the degree of improvement depends on action costs and the outcome model. This analysis emphasizes the need to go beyond generic outcome prediction in interventional settings by incorporating knowledge of plausible actions and latent states.

This is the definitive work on the first and greatest of Japan's twentieth-century philosophers, Nishida Kitaro (1870-1945). Interspersed throughout the narrative of Nishida's life and th…

Recently, LLM-based agents have been all the rage – with projects like AutoGPT showing how easy it is to wrap an LLM in a simple agentic loop and prompt it to achieve real-world tasks. More generally, we can think about the class of ‘scaffolded’ 1 LLM systems – which wrap...

Text: English (translation) Original Language: Japanese

""As we go about our daily lives, caste is the wordless usher in a darkened theater, flashlight cast down in the aisles, guiding us to our assigned seats for a performance. The hierarchy of caste is not about feelings or morality. It is about power--which groups have it and which do not." In this brilliant book, Isabel Wilkerson gives us a masterful portrait of an unseen phenomenon in America as she explores, through an immersive, deeply researched narrative and stories about real people, how America today and throughout its history has been shaped by a hidden caste system, a rigid hierarchy of human rankings. Beyond race, class, or other factors, there is a powerful caste system that influences people's lives and behavior and the nation's fate. Linking the caste systems of America, India, and Nazi Germany, Wilkerson explores eight pillars that underlie caste systems across civilizations, including divine will, bloodlines, stigma, and more. Using riveting stories about people--including Martin Luther King, Jr., baseball's Satchel Paige, a single father and his toddler son, Wilkerson herself, and many others--she shows the ways that the insidious undertow of caste is experienced every day. She documents how the Nazis studied the racial systems in America to plan their out-cast of the Jews; she discusses why the cruel logic of caste requires that there be a bottom rung for those in the middle to measure themselves against; she writes about the surprising health costs of caste, in depression and life expectancy, and the effects of this hierarchy on our culture and politics. Finally, she points forward to ways America can move beyond the artificial and destructive separations of human divisions, toward hope in our common humanity. Beautifully written, original, and revealing, Caste: The Origins of Our Discontents is an eye-opening story of people and history, and a reexamination of what lies under the surface of ordinary lives and of America life today"--

"This book focuses on cooking equipment, techniques, and recipes"--P. xvii

"Thomas Piketty's bestselling Capital in the Twenty-First Century galvanized global debate about inequality. In this audacious follow-up, Piketty challenges us to revolutionize how we think about politics, ideology, and history. He exposes the ideas that have sustained inequality for the past millennium, reveals why the shallow politics of right and left are failing us today, and outlines the structure of a fairer economic system. Our economy, Piketty observes, is not a natural fact. Markets, profits, and capital are all historical constructs that depend on choices. Piketty explores the material and ideological interactions of conflicting social groups that have given us slavery, serfdom, colonialism, communism, and hypercapitalism, shaping the lives of billions. He concludes that the great driver of human progress over the centuries has been the struggle for equality and education and not, as often argued, the assertion of property rights or the pursuit of stability. The new era of extreme inequality that has derailed that progress since the 1980s, he shows, is partly a reaction against communism, but it is also the fruit of ignorance, intellectual specialization, and our drift toward the dead-end politics of identity. Once we understand this, we can begin to envision a more balanced approach to economics and politics. Piketty argues for a new "participatory" socialism, a system founded on an ideology of equality, social property, education, and the sharing of knowledge and power"--

Exchange between East and West, spirit and science examines such questions as why seemingly rational people commit acts of cruelty and violence, what are the root causes of destructive behavior, and whether we can learn to control the emotions that drive these impulses.

"Today considered a landmark of twentieth-century intellectual history, I and Thou is also one of the most important books of Western theology. In it, Martin Buber, heavily influenced by the writings of Frederich Nietzsche, united the proto-Existentialists currents of modern German thought with the Judeo-Christian tradition, powerfully updating faith for modern times. Since its first appearance in German in 1923, this slender volume has become one of the epoch-making works of our time. Not only does it present the best thinking of one of the greatest Jewish minds in centuries, but has helped to mold approaches to reconciling God with the workings of the modern world and the consciousness of its inhabitants. This work is the centerpiece of Buber's groundbreaking philosophy. It lays out a view of the world in which human beings can enter into relationships using their innermost and whole being to form true partnerships. These deep forms of rapport contrast with those that spring from the Industrial Revolution, namely the common, but basically unethical, treatment of others as objects for our use and the incorrect view of the universe as merely the object of our senses, experiences. Buber goes on to demonstrate how these interhuman meetings are a reflection of the human meeting with God. For Buber, the essence of biblical religion consists in the fact that -- regardless of the infinite abyss between them -- a dialogue between man and God is possible. Ecumenical in its appeal, I and Thou nevertheless reflects the profound Talmudic tradition from which it has emerged. For Judaism, Buber's writings have been of revolutionary importance. No other writer has so shaken Judaism from parochialism and applied it so relevantly to the problems and concerns of contemporary men. On the other hand, the fundamentalist Protestant movement in this country has appropriated Buber's "I and Thou encounter" as the implicit basis of its doctrine of immediate faith-based salvation. In this light, Martin Buber has been viewed as the Jewish counterpart to Paul Tillich."--Publisher description.

During the past two decades, mindfulness meditation has gone from being a fringe topic of scientific investigation to being an occasional replacement for psycho...

In this ... guide, [the author] offers gentle anecdotes and practical exercises as a means of learning the skills of mindfulness - being awake and fully aware. From washing the dishes to answering the phone to peeling an orange, he reminds us that each moment holds within it an opportunity to work toward greater self-understanding and peacefulness.-Back cover.

With the ongoing COVID-19 pandemic, and in response to high demand, a multitude of diagnostic tests for the detection and monitoring of the spread of the SARS-CoV-2 virus have been developed. This living document aims to survey the technical aspects of these diagnostic tests, outline the features and current limitations of their underlying technologies, formulate a modular framework for the assessment of the existing (and upcoming) tests workflows, and help depict a clearer and more comprehensive picture of this rapidly evolving space. With this manuscript as a starting point, we aim to help orchestrate a community effort to identify potential pitfalls and bottlenecks in the existing testing workflows---with the ultimate goal of paving the way to more sensitive, robust, scalable, and widespread tests for maximal social impact.

""One of the most visionary, original, and quietly influential writers currently working" (The Boston Globe) returns with a sequel to the New York Times bestselling The Peripheral. Verity Jane, gifted app-whisperer, has been out of work since her exit from a brief but problematic relationship with a Silicon Valley billionaire. Then she signs the wordy NDA of a dodgy San Francisco start-up, becoming the beta tester for their latest product: a digital assistant, accessed through a pair of ordinary-looking glasses. "Eunice," the disarmingly human AI in the glasses, soon manifests a face, a fragmentary past, and an unnervingly canny grasp of combat strategy. Verity, realizing that her cryptic new employers don't yet know this, instinctively decides that it's best they don't. Meanwhile, a century ahead, in London, in a different timeline entirely, Wilf Netherton works amid plutocrats and plunderers, survivors of the slow and steady apocalypse known as the jackpot. His employer, the enigmatic Ainsley Lowbeer, can look into alternate pasts and nudge their ultimate directions. Verity and Eunice have become her current project. Wilf can see what Verity and Eunice can't: their own version of the jackpot, just around the corner. And something else too: the roles they both may play in it"--

Diagnostic testing to identify persons infected with severe acute respiratory syndrome–related coronavirus-2 (SARS–CoV-2) infection is central to control the global pandemic of COVID-19 that began in late 2019. In a few countries, the use of diagnostic testing on a massive scale has been a cornerstone of successful containment strategies. In contrast, the United States, hampered by limited testing capacity, has prioritized testing for specific groups of persons. Real-time reverse transcriptase polymerase chain reaction–based assays performed in a laboratory on respiratory specimens are the reference standard for COVID-19 diagnostics. However, point-of-care technologies and serologic immunoassays are rapidly emerging. Although excellent tools exist for the diagnosis of symptomatic patients in well-equipped laboratories, important gaps remain in screening asymptomatic persons in the incubation phase, as well as in the accurate determination of live viral shedding during convalescence to inform decisions to end isolation. Many affluent countries have encountered challenges in test delivery and specimen collection that have inhibited rapid increases in testing capacity. These challenges may be even greater in low-resource settings. Urgent clinical and public health needs currently drive an unprecedented global effort to increase testing capacity for SARS–CoV-2 infection. Here, the authors review the current array of tests for SARS–CoV-2, highlight gaps in current diagnostic capacity, and propose potential solutions.

"William Gibson returns with his first novel since 2010's New York Times-bestselling Zero History. Where Flynne and her brother, Burton, live, jobs outside the drug business are rare. Fortunately, Burton has his veteran's benefits, for neural damage he suffered from implants during his time in the USMC's elite Haptic Recon force. Then one night Burton has to go out, but there's a job he's supposed to do-a job Flynne didn't know he had. Beta-testing part of a new game, he tells her. The job seems to be simple: work a perimeter around the image of a tower building. Little buglike things turn up. He's supposed to get in their way, edge them back. That's all there is to it. He's offering Flynne a good price to take over for him. What she sees, though, isn't what Burton told her to expect. It might be a game, but it might also be murder"--Provided by publisher.

Welcome! Material was last updated on 3/27/2020, unless otherwise specified.

The global impact of COVID-19 has been profound, and the public health threat it represents is the most serious seen in a respiratory virus since the 1918 H1N1 influenza pandemic. Here we present the results of epidemiological modelling which has informed policymaking in the UK and other countries in recent weeks. In the absence of a COVID-19 vaccine, we assess the potential role of a number of public health measures – so-called non-pharmaceutical interventions (NPIs) – aimed at reducing contact rates in the population and thereby reducing transmission of the virus. In the results presented here, we apply a previously published microsimulation model to two countries: the UK (Great Britain specifically) and the US. We conclude that the effectiveness of any one intervention in isolation is likely to be limited, requiring multiple interventions to be combined to have a substantial impact on transmission. Two fundamental strategies are possible: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread – reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. Each policy has major challenges. We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over. For countries able to achieve it, this leaves suppression as the preferred policy option. We show that in the UK and US context, suppression will minimally require a combination of social distancing of the entire population, home isolation of cases and household quarantine of their family members. This may need to be supplemented by school and university closures, though it should be recognised that such closures may have negative impacts on health systems due to increased absenteeism. The major challenge of suppression is that this type of intensive intervention package – or something equivalently effective at reducing transmission – will need to be maintained until a vaccine becomes available (potentially 18 months or more) – given that we predict that transmission will quickly rebound if interventions are relaxed. We show that intermittent social distancing – triggered by trends in disease surveillance – may allow interventions to be relaxed temporarily in relative short time windows, but measures will need to be reintroduced if or when case numbers rebound. Last, while experience in China and now South Korea show that suppression is possible in the short term, it remains to be seen whether it is possible long-term, and whether the social and economic costs of the interventions adopted thus far can be reduced.

How neural networks build up their understanding of images

"The bestselling author of Daemon returns with a near-future technological thriller, in which a charismatic billionaire recruits a team of adventurers to launch the first deep space mining operation--a mission that could alter the trajectory of human civilization. When itinerant cave diver James Tighe receives an invitation to billionaire Nathan Joyce's private island, he thinks it must be a mistake. But Tighe's unique skill set makes him a prime candidate for Joyce's high-risk venture to mine a near-earth asteroid--with the goal of kick-starting an entire off-world economy. The potential rewards and personal risks are staggering, but the competition is fierce and the stakes couldn't be higher. Isolated and pushed beyond their breaking points, Tighe and his fellow twenty-first century adventurers--ex-soldiers, former astronauts, BASE jumpers, and mountain climbers--must rely on each other to survive not only the dangers of a multi-year expedition but the harsh realities of business in space. They're determined to transform humanity from an Earth-bound species to a space-faring one--or die trying"--

"A bold, epic debut novel set during the war and financial crisis that defined the beginning of our century. An investment banker approaching forty, his career collapsing and his marriage unraveling, receives a surprise visitor at his West London town house. Confronting the disheveled figure of a South Asian male carrying a backpack, the banker recognizes a long-lost college friend, a mathematics prodigy who disappeared many years earlier under mysterious circumstances. The friend has resurfaced with a confession of unsettling power. Zia Haider Rahman takes us on a journey of exhilarating scope, ranging over Kabul, London, New York, Islamabad, Oxford, Princeton, and Sylhet, and dealing with love, belonging, finance, cognitive science, and war. Its framework is an age-old story: the friendship of two men and the betrayal of one by the other, both of them desperate in their different ways to climb clear of their wrong beginnings. Set against the breaking of nations and beneath the clouds of economic recession, the novel chronicles the lives of people carrying unshakable legacies of class, culture, and faith as they struggle to tame their futures. In the Light of What We Know is by turns tender, intimate, and panoramic, telescoping the great upheavals of our young century into a first novel of rare ambition and profundity. "--

Journalist "explores why we find it so gratifying to be right and so maddening to be mistaken, and how this attitude toward error corrodes relationships." She claims that "error is both a given and a gift -- one that can transform our worldviews, our relationships, and, most profoundly, ourselves

Overreliance on artificial intelligence may put us in intellectual debt.

A new paper explains why disinformation campaigns that act as a stabilizing influence in Russia are destabilizing in the United States.

At its heart, privacy is about how data is used to take away our control.

Opinion: Silicon Valley culture often reveals the optimism of organized ignorance. Rather than lauding "new" experts, we need to respect, sustain, and strengthen the ones we already have.

On the latest Recode Decode, MIT Media Lab director Joi Ito says we need to resist the urge to oversimplify the problems we’re solving.

"If you had told Roger McNamee even three years ago that he would soon be devoting himself to stopping Facebook from destroying our democracy, he would have howled with laughter. He had mentored many tech leaders in his illustrious career as an investor, but few things had made him prouder, or been better for his fund's bottom line, than his early service to Mark Zuckerberg. Still a large shareholder in Facebook, he had every good reason to stay on the bright side. Until he simply couldn't. ZUCKED is McNamee's intimate reckoning with the catastrophic failure of the head of one of the world's most powerful companies to face up to the damage he is doing. It's a story that begins with a series of rude awakenings. First there is the author's dawning realization that the platform is being manipulated by some very bad actors. Then there is the even more unsettling realization that Zuckerberg and Sheryl Sandberg are unable or unwilling to share his concerns, polite as they may be to his face"--

ImportanceRandomized clinical trials (RCTs) currently apply the same statistical threshold of alpha = 2.5% for controlling for false-positive results or type 1 error, regardless of the burden of disease or patient preferences. Is there an objective and systematic framework for designing RCTs that incorporates these considerations on a case-by-case basis?ObjectiveTo apply Bayesian decision analysis (BDA) to cancer therapeutics to choose an alpha and sample size that minimize the potential harm to current and future patients under both null and alternative hypotheses.Data SourcesWe used the National Cancer Institute (NCI) Surveillance, Epidemiology, and End Results (SEER) database and data from the 10 clinical trials of the Alliance for Clinical Trials in Oncology.Study SelectionThe NCI SEER database was used because it is the most comprehensive cancer database in the United States. The Alliance trial data was used owing to the quality and breadth of data, and because of the expertise in these trials of one of us (D.J.S.).Data Extraction and SynthesisThe NCI SEER and Alliance data have already been thoroughly vetted. Computations were replicated independently by 2 coauthors and reviewed by all coauthors.Main Outcomes and MeasuresOur prior hypothesis was that an alpha of 2.5% would not minimize the overall expected harm to current and future patients for the most deadly cancers, and that a less conservative alpha may be necessary. Our primary study outcomes involve measuring the potential harm to patients under both null and alternative hypotheses using NCI and Alliance data, and then computing BDA-optimal type 1 error rates and sample sizes for oncology RCTs.ResultsWe computed BDA-optimal parameters for the 23 most common cancer sites using NCI data, and for the 10 Alliance clinical trials. For RCTs involving therapies for cancers with short survival times, no existing treatments, and low prevalence, the BDA-optimal type 1 error rates were much higher than the traditional 2.5%. For cancers with longer survival times, existing treatments, and high prevalence, the corresponding BDA-optimal error rates were much lower, in some cases even lower than 2.5%.Conclusions and RelevanceBayesian decision analysis is a systematic, objective, transparent, and repeatable process for deciding the outcomes of RCTs that explicitly incorporates burden of disease and patient preferences.

Jed Emerson has never been afraid to tell it like it is. Now, after 30-odd years of exploring impact and purpose-driven capital – and eight books later – he believes the field has become ‘lazy’, offering superficial answers to humanity’s most difficult questions as we skip straight to the ‘how’ of tactics and strategy. The advisor, author and (former) keynote speaker tells us why he’s ready to stop talking – and why he hopes the rest of us will do the same

The Impact Classes of Investment What are the different kinds of impact that investments have on people and the planet? PGGM

It is March 2017, and TPG, a global alternative investment firm with $74 billion assets under management, has recently launched its inaugural impact-investing fund—the $2 billion Rise Fund. In an effort to “take the religion out of impact investing,” Bill McGlashan, founder and managing partner of TPG Growth, an arm of TPG focused on growth equity investments and middle-market buyouts and co-founder and CEO of the Rise Fund, has partnered with The Bridgespan Group, a nonprofit consultancy, to develop an evidence-based methodology for quantifying the impact of prospective Rise investments. Together, they have come up with a framework that ultimately generates an impact multiple of money (IMM), a measure of the social value created by a company per equity dollar invested. If a company fails to meet the IMM threshold, Rise will not invest in it. The case finds McGlashan and Maya Chorengel (HBS MBA ’97), Rise’s senior partner for impact, debating whether to make Rise’s first investment in EverFi, an educational technology company that offers a range of online educational programming to its K-12 school, university, and corporate clients.

As impact investing grows, investors are beginning to better understand the relationship between risk, return, and impact. Beyond Trade-offs includes research from the Economist Intelligence Unit on the factors driving this growth, and perspectives from leading investors who have moved beyond the trade-off debate to invest across the returns continuum.

Many human societies feature institutions for redistributing resources from some individuals to others, but preferred levels of redistribution vary greatly within and between populations. We postulate that support for redistribution is the output of moral computations that are sensitive to perceived features of the social situation. We develop a within-subjects experimental approach in which participants prescribe appropriate redistribution for hypothetical villages whose features vary. Over six experiments involving 600 adults from the UK, we show that participants shift their preferences markedly from village to village. Support for redistribution is better predicted by the social features of the village than by individual differences in participants' political orientations. Higher levels of redistribution are systematically favoured when luck is more important in the initial distribution of resources; when social groups are more homogeneous; when the group is at war; and when resources are abundant rather than scarce. Participants have systematic intuitions about when the implementation of redistribution will prove problematic, that are distinct from their intuitions about when redistribution is desirable. We argue that the operation of flexible, context-sensitive moral computations may explain variation and change in support for, and hence existence of, redistributive institutions across societies and over time. The reasons different people come to different conclusions about redistribution may lie mostly in different appraisals about what their social group is like, rather than differences in values.

My blurb: In classic Lessig fashion,They Don’t Represent Us connects one of society’s biggest challenges - the impact of technology on our society and democracy - to the evolution of our constitution to show how we’ve lost our voice in our system of government. But as the reader descends into a spiral of despair, he pulls them up with the hope of potential interventions that could successfully enact positive change.

Modern science, the Internet, big data, and AI are each saying the same thing to us: the world is -- and always has been -- far more complex and unpredictable than we've allowed ourselves to see. As a result we're undergoing a sea change in our understanding of how things happen, and in our deepest strategies for predicting, preparing for, and managing our lives and our businesses. For example, machine learning allows us to make better predictions (think the weather, stock performance, online clicks) but we know less about why those predictions are right--and we need to get used to that. And in fact, over the past twenty years we've been unintentionally developing strategies that avoid anticipating what will happen so we don't have to depend on unreliable revenue forecasts, assumptions about customer needs, and hypotheses about how a product will be used. By embracing these strategies, we're flourishing by creating yet more possibilities and yet more unpredictability. In wide-ranging stories and characteristically all-encompassing syntheses, technology researcher, internet expert, and philosopher David Weinberger reveals the trends that hide in so many aspects of our lives--and shows us how they matter.--

I argue that explanation should be thought of as the phenomenological mark of the operation of a particular kind of cognitive system, the theory-formation system. The theory-formation system operates most clearly in children and scientists but is also part of our everyday cognition. The system is devoted to uncovering the underlying causal structure of the world. Since this process often involves active intervention in the world, in the case of systematic experiment in scientists, and play in children, the cognitive system is accompanied by a ‘theory drive’, a motivational system that impels us to interpret new evidence in terms of existing theories and change our theories in the light of new evidence. What we usually think of as explanation is the phenomenological state that accompanies the satisfaction of this drive. However, the relation between the phenomenology and the cognitive system is contingent, as in similar cases of sexual and visual phenomenology. Distinctive explanatory phenomenology may also help us to identify when the theory-formation system is operating.

In three decades of advocating for prison abolition, the activist and scholar has helped transform how people think about criminal justice.

Predictive policing systems are used increasingly by law enforcement to try to prevent crime before it occurs. But what happens when these systems are trained using biased data? Kristian Lum and William Isaac consider the evidence – and the social consequences

"Shoshana Zuboff, named "the true prophet of the information age" by the Financial Times, has always been ahead of her time. Her seminal book In the Age of the Smart Machine foresaw the consequences of a then-unfolding era of computer technology. Now, three decades later she asks why the once-celebrated miracle of digital is turning into a nightmare. Zuboff tackles the social, political, business, personal, and technological meaning of "surveillance capitalism" as an unprecedented new market form. It is not simply about tracking us and selling ads, it is the business model for an ominous new marketplace that aims at nothing less than predicting and modifying our everyday behavior--where we go, what we do, what we say, how we feel, who we're with. The consequences of surveillance capitalism for us as individuals and as a society vividly come to life in The Age of Surveillance Capitalism's pathbreaking analysis of power. The threat has shifted from a totalitarian "big brother" state to a universal global architecture of automatic sensors and smart capabilities: A "big other" that imposes a fundamentally new form of power and unprecedented concentrations of knowledge in private companies--free from democratic oversight and control"--

Recent discussion in the public sphere about algorithmic classification has involved tension between competing notions of what it means for a probabilistic classification to be fair to different groups. We formalize three fairness conditions that lie at the heart of these debates, and we prove that except in highly constrained special cases, there is no method that can satisfy these three conditions simultaneously. Moreover, even satisfying all three conditions approximately requires that the data lie in an approximate version of one of the constrained special cases identified by our theorem. These results suggest some of the ways in which key notions of fairness are incompatible with each other, and hence provide a framework for thinking about the trade-offs between them.

Perspectives on Impact brings together leaders from across sectors to reflect on our approaches to social change. Sharing diverse examples from their work, these authors show how we must think more systemically and work more collaboratively to move the needle on the biggest social, humanitarian, and environmental challenges facing our world. Chapters by: Niko Canner, Shanti Nayak, and Cynthia Warner (Incandescent) Duncan Green (OxFam) Farah Ramzan Golant (Girl Effect, kyu) Sara Holoubek (Luminary Labs) Joi Ito (MIT Media Lab) Leila Janah (Samasource, LXMI, Samaschool) Amirah Jiwa George Kronnisanyon Werner (Republic of Liberia) Chris Larkin (IDEO.org) Eric Maltzer (Medora Ventures, Middlebury College) Jane Nelson (Harvard Kennedy School) Craig Nevill-Manning and Prem Ramaswami (Sidewalk Labs) Jacqueline Novogratz (Acumen) Deena Shakir (GV, formerly Google Ventures) Jose Miguel Sokoloff (MullenLowe Group) Lara Stein (TEDx, Women's March Global) Piyush Tantia (ideas42) Fay Twersky (William & Flora Hewlett Foundation) Sherrie Rollins Westin and Shari Rosenfeld (Sesame Workshop) Perspectives on Impact and its sister book, Perspectives on Purpose, bring together leading voices from across sectors to discuss how we must adapt our organizations for the twenty-first century world. Perspectives on Impact focuses on the recalibration of social impact approaches to tackle complex humanitarian, social, and environmental challenges; Perspectives on Purpose looks at the shifting role of the corporation in society through the lens of purpose. You can find Perspectives on Purpose: Leading Voices on Building Brands and Businesses for the Twenty-First Century here: https://www.amazon.com/Perspectives-Purpose-Building-Businesses-Twenty-First/dp/036711237X

Collectively, machine learning (ML) researchers are engaged in the creation and dissemination of knowledge about data-driven algorithms. In a given paper, researchers might aspire to any subset of the following goals, among others: to theoretically characterize what is learnable, to obtain understanding through empirically rigorous experiments, or to build a working system that has high predictive accuracy. While determining which knowledge warrants inquiry may be subjective, once the topic is fixed, papers are most valuable to the community when they act in service of the reader, creating foundational knowledge and communicating as clearly as possible. Recent progress in machine learning comes despite frequent departures from these ideals. In this paper, we focus on the following four patterns that appear to us to be trending in ML scholarship: (i) failure to distinguish between explanation and speculation; (ii) failure to identify the sources of empirical gains, e.g., emphasizing unnecessary modifications to neural architectures when gains actually stem from hyper-parameter tuning; (iii) mathiness: the use of mathematics that obfuscates or impresses rather than clarifies, e.g., by confusing technical and non-technical concepts; and (iv) misuse of language, e.g., by choosing terms of art with colloquial connotations or by overloading established technical terms. While the causes behind these patterns are uncertain, possibilities include the rapid expansion of the community, the consequent thinness of the reviewer pool, and the often-misaligned incentives between scholarship and short-term measures of success (e.g., bibliometrics, attention, and entrepreneurial opportunity). While each pattern offers a corresponding remedy (don't do it), we also discuss some speculative suggestions for how the community might combat these trends.

Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and…

Residing in New Whitby, Maine, a town founded by vampires trying to escape persecution, Mel finds her negative attitudes challenged when her best friend falls in love with one, another friend's father runs off with one, and she herself is attracted to someone who tries to pass himself off as one

Actuarial risk assessments might be unduly perceived as a neutral way to counteract implicit bias and increase the fairness of decisions made at almost every juncture of the criminal justice system, from pretrial release to sentencing, parole and probation. In recent times these assessments have come under increased scrutiny, as critics claim that the statistical techniques underlying them might reproduce existing patterns of discrimination and historical biases that are reflected in the data. Much of this debate is centered around competing notions of fairness and predictive accuracy, resting on the contested use of variables that act as "proxies" for characteristics legally protected against discrimination, such as race and gender. We argue that a core ethical debate surrounding the use of regression in risk assessments is not simply one of bias or accuracy. Rather, it's one of purpose. If machine learning is operationalized merely in the service of predicting individual future crime, then it becomes difficult to break cycles of criminalization that are driven by the iatrogenic effects of the criminal justice system itself. We posit that machine learning should not be used for prediction, but rather to surface covariates that are fed into a causal model for understanding the social, structural and psychological drivers of crime. We propose an alternative application of machine learning and causal inference away from predicting risk scores to risk mitigation.

Kin selection theory (KS) is widely invoked to account for the preferential treatment of kin—nepotism—in primate societies. Because this idea is so pervasive the role of KS is often unquestioned and optional mechanisms are often ignored. I first examine the potential role of some other nepotism-generating mechanisms by concentrating on the effect of the proximity correlate of matrilineal kinship. This correlate of kinship may bias the development of mutually selfish interactions among relatives—kin-biased mutualism—and that of reciprocally altruistic interactions—kin-biased reciprocal altruism—two mechanisms that have been given little weight compared to KS and whose impact on the evolution of nepotism is therefore unknown. However, these two options to KS cannot account for the existence of unilaterally altruistic interactions among kin, which provide, therefore, the best type of evidence to test KS. But such evidence is difficult to obtain because many behaviors considered altruistic may in fact be selfish, and because kin altruism is seldom unilateral; it is most often bilateral, as expected by reciprocal altruism theory. For these reasons, one should be extremely cautious before equating nepotism exclusively with KS. Next, I examine the predictions of KS regarding the deployment of altruism according to degree of kinship by considering, in addition to the variables of Hamilton's equation, the duration of behaviors, the size of kin classes and their differential availability. In general, altruism is expected to be allocated at a fairly constant rate among kin categories and to drop markedly past the degree of relatedness beyond which altruism is no more profitable. Very little data allow one to test conclusively this prediction, as well as some other significant predictions. Overall, there is ample evidence for the role of KS in shaping mother-offspring interactions in various areas. But the evidence for kin-selected altruism beyond the mother-offspring bond (r < 0.5), though qualitatively solid, is much less abundant. Kin altruism drops markedly beyond r = 0.25 (half-siblings and grandmother-grandoffspring dyads).

裏千家茶道で使う扇子の大きさや、扇子の扱い方（持ち方、置き方、差し方）などのお稽古です。「扇子ってどうやって使うの？」そんな時に参考にしてね。

Transcendental phenomenology brings added dimensions to the study of human experiences through qualitative research. Learn more.

This is the definitive work on the first and greatest of Japan's twentieth-century philosophers, Nishida Kitaro (1870-1945). Interspersed throughout the narrative of Nishida's life and thought is a generous selection of the philosopher's own essays, letters, and short presentations, newly translated into English.

NEXT POST: Part II of my thoughts on TikTok, on how the app design is informed by its algorithm and vice versa in a virtuous circle.

"In the spring of 1934, Virginia Woolf sketched an affectionate three-page "biographical fantasy" of her great friend, John Maynard Keynes, attempting to encompass no less than 25 themes, which she jotted down at its opening: "Politics. Art. Dancing. Letters. Economics. Youth. The Future. Glands. Genealogies. Atlantis. Mortality. Religion. Cambridge. Eton. The Drama. Society. Truth. Pigs. Sussex. The History of England. America. Optimism. Stammer. Old Books. Hume." In truth, his life contained even more. Years earlier, as a young Cambridge philosopher and economist, Keynes spent his days moving between government service and academia, and when he was called up to the Treasury on the eve of World War I, he relished an opportunity to save the empire. He worked dutifully, but as the aftermath of the war and the disastrous Versailles Treaty unfolded, with its harsh demands for German reparations, Keynes saw how the strain on its citizens might encourage would-be authoritarians. The experience began a career that spanned two world wars and a global depression and which often found him in a Cassandra-like position, arguing against widely accepted ideas that he saw as outdated or dangerous. His influential ideas made it to America and FDR's New Deal in the Great Depression, and through his books, especially The General Theory, he became a founding giant in the economics profession. Even as his star rose, however, the most important allegiance of Keynes's life was to writers and artists. He valued his membership in the iconic Bloomsbury Group above any position, and he forever envied the talents of his friends like Virginia Woolf and Lytton Strachey, often providing them with much needed financial support as the most gainfully employed member of the group. In return, they gave him a moral compass and inspired his vision of what society should be"--

Twenty-seven prominent researchers from MIT, Harvard, Princeton, NYU, UC Berkeley and Columbia have signed an open statement of concern regarding the use of actuarial risk assessment as a means of lowering pretrial jail populations.

The STS Program presents a lecture by Joichi Ito Director, MIT Media Laboratory, followed by a panel discussion featuring Joshua D. Greene Professor, Department of Psychology, Harvard University; Nicco Mele, Director, Shorenstein Center on Media, Politics, and Public Policy, Harvard Kennedy School; Martha Minow 300th Anniversary University Professor, Harvard University; Former Dean, Harvard Law School; and moderated by Sheila Jasanoff, Pforzheimer Professor of Science and Technology Studies, Harvard Kennedy School.

Actuarial risk assessments might be unduly perceived as a neutral way to counteract implicit bias and increase the fairness of decisions made at almost every juncture of the criminal justice system, from pretrial release to sentencing, parole and probation. In recent times these assessments have come under increased scrutiny, as critics claim that the statistical techniques underlying them might reproduce existing patterns of discrimination and historical biases that are reflected in the data. Much of this debate is centered around competing notions of fairness and predictive accuracy, resting on the contested use of variables that act as “proxies” for characteristics legally protected against discrimination, such as race and gender.