What is machine learning?


Chris Meserole at Brookings: “In the summer of 1955, while planning a now famous workshop at Dartmouth College, John McCarthy coined the term “artificial intelligence” to describe a new field of computer science. Rather than writing programs that tell a computer how to carry out a specific task, McCarthy pledged that he and his colleagues would instead pursue algorithms that could teach themselves how to do so. The goal was to create computers that could observe the world and then make decisions based on those observations—to demonstrate, that is, an innate intelligence.

The question was how to achieve that goal. Early efforts focused primarily on what’s known as symbolic AI, which tried to teach computers how to reason abstractly. But today the dominant approach by far is machine learning, which relies on statistics instead. Although the approach dates back to the 1950s—one of the attendees at Dartmouth, Arthur Samuels, was the first to describe his work as “machine learning”—it wasn’t until the past few decades that computers had enough storage and processing power for the approach to work well. The rise of cloud computing and customized chips has powered breakthrough after breakthrough, with research centers like OpenAI or DeepMind announcing stunning new advances seemingly every week.

The extraordinary success of machine learning has made it the default method of choice for AI researchers and experts. Indeed, machine learning is now so popular that it has effectively become synonymous with artificial intelligence itself. As a result, it’s not possible to tease out the implications of AI without understanding how machine learning works—as well as how it doesn’t….(More)”.

Why Is Behavioral Economics So Popular?


David Gal at the New York Times: “Behavioral economics seems to have captured the popular imagination. Authors like Michael Lewis write about it in best sellers like “The Undoing Project,” while pioneers of the field like Daniel Kahneman popularize it in books like “Thinking, Fast and Slow.” Its lexicon of “nudging,” “framing bias” and “the endowment effect” has become part of the vernacular of business, finance and policymaking. Even “Crazy Rich Asians,” the summer’s blockbuster romantic comedy, features an explicit nod to “loss aversion,” a key concept in the field.

What is behavioral economics, and why has it become so popular? The field has been described by Richard Thaler, one of its founders, as “economics done with strong injections of good psychology.” Proponents view it as a way to make economics more accurate by incorporating more realistic assumptions about how humans behave.

In practice, much of behavioral economics consists in using psychological insights to influence behavior. These interventions tend to be small, often involving subtle changes in how choices are presented: for example, whether you have to “opt in” to a 401(k) savings plan versus having to “opt out.” In this respect, behavioral economics can be thought of as endorsing the outsize benefits of psychological “tricks,” rather than as calling for more fundamental behavioral or policy change.

The popularity of such low-cost psychological interventions, or “nudges,” under the label of behavioral economics is in part a triumph of marketing. It reflects the widespread perception that behavioral economics combines the cleverness and fun of pop psychology with the rigor and relevance of economics.

Yet this triumph has come at a cost. In order to appeal to other economists, behavioral economists are too often concerned with describing how human behavior deviates from the assumptions of standard economic models, rather than with understanding why people behave the way they do.

Consider loss aversion. This is the notion that losses have a bigger psychological impact than gains do — that losing $5, for example, feels worse than gaining $5 feels good. Behavioral economists point to loss aversion as a psychological glitch that explains a lot of puzzling human conduct. But in an article published this year, the psychologist Derek D. Rucker and I contend that the behaviors most commonly attributed to loss aversion are a result of other causes….

There is nothing wrong with achieving small victories with minor interventions. The worry, however, is that the perceived simplicity and efficacy of such tactics will distract decision makers from more substantive efforts — for example, reducing electricity consumption by taxing it more heavily or investing in renewable energy resources.

It is great that behavioral economics is receiving its due; the field has contributed significantly to our understanding of ourselves. But in all the excitement, it’s important to keep an eye on its limits….(More)”.

The law and ethics of big data analytics: A new role for international human rights in the search for global standards


David Nersessian at Business Horizons: “The Economist recently declared that digital information has overtaken oil as the world’s most valuable commodity. Big data technology is inherently global and borderless, yet little international consensus exists over what standards should govern its use. One source of global standards benefitting from considerable international consensus might be used to fill the gap: international human rights law.

This article considers the extent to which international human rights law operates as a legal or ethical constraint on global commercial use of big data technologies. By providing clear baseline standards that apply worldwide, human rights can help shape cultural norms—implemented as ethical practices and global policies and procedures—about what businesses should do with their information technologies. In this way, human rights could play a broad and important role in shaping business thinking about the proper handling of this increasingly valuable commodity in the modern global society…(More)”.

Nervous States


Book by William Davies: “Why do we no longer trust experts, facts and statistics? Why has politics become so fractious and warlike? What caused the populist political upheavals of recent years?How can the history of ideas help us understand our present?

In this bold and far-reaching exploration of our new political landscape, William Davies reveals how feelings have come to reshape our world. Drawing deep on history, philosophy, psychology and economics, he shows how some of the fundamental assumptions that defined the modern world have dissolved. With advances in science and medicine, the division between mind and body is no longer so clear-cut. The spread of digital and military technology has left us not quite at war nor exactly at peace. In the murky new space between mind and body, between war and peace, lie nervous states: with all of us relying increasingly on feeling rather than fact.

In a book of profound insight and astonishing breadth, William Davies reveals the origins of this new political reality. Nervous States is a compelling and essential guide to the turbulent times we are living through….(More)”.

Translating science into business innovation: The case of open food and nutrition data hackathons


Paper by Christopher TucciGianluigi Viscusi and Heidi Gautschi: “In this article, we explore the use of hackathons and open data in corporations’ open innovation portfolios, addressing a new way for companies to tap into the creativity and innovation of early-stage startup culture, in this case applied to the food and nutrition sector. We study the first Open Food Data Hackdays, held on 10-11 February 2017 in Lausanne and Zurich. The aim of the overall project that the Hackdays event was part of was to use open food and nutrition data as a driver for business innovation. We see hackathons as a new tool in the innovation manager’s toolkit, a kind of live crowdsourcing exercise that goes beyond traditional ideation and develops a variety of prototypes and new ideas for business innovation. Companies then have the option of working with entrepreneurs and taking some of the ideas forward….(More)”.

(In)Equalities and Social (In)Visibilities in the Digital Age


Intro by Inês Amaral, Maria João Barata and Vasco Almeida to the Special issue of Interações: “The influence of new technologies in public and private spheres of society, rather than a reformulation, has given rise to a new social field and directly interferes with how we perceive the world, relate to it and to others. One should note that in Pierre Bourdieu›s (2001) theory, field arises as a configuration of socially distributed relations.
Progressively, a universe of socialisation has emerged and consolidated: cyber-space. Although virtual, it exists and produces effects. It can be defined as the space boosted by the different digital communication platforms and assumes itself as an
individual communication model, allowing the receiver to be simultaneously emitter. Space of flows (Castells, 1996), cyberspace translates the social dimension of the Internet, enabling the diffusion of communication/information on a global scale. This causes an intense process of inclusion and exclusion of people in the network.
The reference to info-inclusive and info-excluded societies of the digital scenario is imperative when it is reflected in the geography of the new socio-technological spaces. The dynamics of these territories are directly associated with the way social,
demographic, economic and technological variables condition each other, revealing the potential for dissemination of information and knowledge through technologies.
In this special issue of the journal Interações we propose a reflection on (In)Equalities and Social (In)Visibilities in the Digital Age. The articles in the volume present research results and/or theoretical reflection on social visibilities and invisibilities
created by dynamics of media and digital inclusion and exclusion, relations between the digital and inequalities in different geographical, social and professional contexts, digital literacy and vulnerable social groups, conditioning created by technology to the individual in social context, among others….(More)”

Privacy and Interoperability Challenges Could Limit the Benefits of Education Technology


Report by Katharina Ley Best and John F. Pane: “The expansion of education technology is transforming the learning environment in classrooms, schools, school systems, online, and at home. The rise of education technology brings with it an increased opportunity for the collection and application of data, which are valuable resources for educators, schools, policymakers, researchers, and software developers.

RAND researchers examine some of the possible implications of growing data collection and availability related to education technology. Specifically, this Perspective discusses potential data infrastructure challenges that could limit data usefulness, consider data privacy implications in an education technology context, and review privacy principles that could help educators and policymakers evaluate the changing education data privacy landscape in anticipation of potential future changes to regulations and best practices….(More)”.

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier.


Paper by Christine L. Borgman: “As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of “grey data” about individuals in their daily activities of research, teaching, learning, services, and administration.

The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This Article explores the competing values inherent in data stewardship and makes recommendations for practice by drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk….(More)”.

The latest tools for sexual assault victims: Smartphone apps and software


 
Peter Holley at the Washington Post:  “…For much of the past decade, dozens of apps and websites have been created to help survivors of sexual assault electronically record and report such crimes. They are designed to assist an enormous pool of potential victims. The Rape Abuse & Incest National Network reports that more than 11 percent of all college students — both graduate and undergraduate — experience rape or sexual assault through physical force, violence or incapacitation. Despite the prevalence of such incidents, less than 10 percent of victims on college campuses report their assaults, according to the National Sexual Violence Resource Center.

The apps range from electronic reporting tools such as JDoe to legal guides that provide victims with access to law enforcement and crisis counseling. Others help victims save and share relevant medical information in case of an assault. The app Uask includes a “panic button” that connects users with 911 or allows them to send emergency messages to people with their location.

 

Since its debut in 2015, Callisto’s software has been adopted by 12 college campuses — including Stanford, the University of Oregon and St. John’s University — and made available to more than 160,000 students, according to the company. Sexual assault survivors who visit Callisto are six times as likely to report, and 15 percent of those survivors have matched with another victim of the same assailant, the company claims.

Peter Cappelli, a professor of management at the Wharton School and director of Wharton’s Center for Human Resources, told NPR that he sees potential problems with survivors “crowdsourcing” their decision to report assaults.

“I don’t think we want to have a standard where the decisions are crowdsourced,” he said. “I think what you want is to tell people [that] the criteria [for whether or not to report] are policy related, not personally related, and you should bring forward anything that fits the criteria, not [based on] whether you feel enough other people have made the complaint or not. We want to sometimes encourage people to do things they might feel uncomfortable about.”…(More)”.

Managing the Consumer Data Deluge


Joe Marion at Healthcare Informatics: “By now, everyone is aware of Apple’s recent announcement of an ECG capability on its latest watch.  It joins an expanding list of portable or in-home devices for monitoring cardiac and other functions.  The Apple device takes advantage of an established ECG device from AliveCor, which had previously introduced the CardiaMobile ECG capture device for Android and iOS devices.  More sophisticated monitoring devices such as implantable devices can monitor heart function in heart failure cases.

Many facilities are implementing video-conferencing type capabilities for patient consultation for non-life-threatening issues.  These might include the capture of information such as a “selfie” of a rash that is uploaded to the physician for assessment.

Given that many of these devices are designed to collect diagnostic data outside of the primary care facility, there is a growing tsunami in terms of the amount of diagnostic data that will need to be managed.  Since most of this data is created outside of the primary care facility, there are several questions that need to be addressed.

Who owns the data? Let’s take the case of ECG data captured from an Apple or AliveCor device.  The data is being acquired by the user, and it is initially stored on the watch or phone device, and may utilize some initial diagnosis application.  The whole purpose of capturing this data is to monitor cardiac function, particularly fibrillation, and to share it with a medical professional.  In the case of these devices the data can be optionally uploaded to an AliveCor cloud application for storage.  Thus, the assumption would be that the patient is the “owner” of the data.  But what if it is necessary to transmit this data to a professional such as a cardiologist?  Is it then the responsibility of the receiving entity to store and manage the data?  Or, is it assumed that the patient is responsible for maintaining the data?

Once data is brought into a provider organization for diagnostic purposes, it seems reasonable that the facility would be responsible for maintaining that data, just as they do today for radiographic studies that are taken.  If, for example a cardiologist dictates a report on ECG results, the results most likely end up in the EHR, but what becomes of the diagnostic data?

Who is responsible for maintaining the data? As stated above, if the acquired data results in a report of some type, the report most likely becomes the legal document in the EHR, but for legal purposes, many facilities feel the need to store the original diagnostic data for some period of time….

Who is the originator of the data collection? The informed patient may wish to acquire diagnostic data, such as ECG or blood pressure information, but are they prepared to manage that data?  If they are concerned about episodes of atrial fibrillation, then there may be an incentive to acquire and manage such data.

Conversely, many in-home devices are initiated by care providers, such as remote monitoring of heart failure.  In these instances, the acquisition devices are most likely provided to the patient for the physician’s benefit.  Therefore, the onus is on the provider to manage the acquired data, and it would become the facility’s responsibility for managing data storage.

Another question is how valuable is such data to the management of the patient?  For devices such as the Apple watch ECG capability, is it important to the physician to have access to that data over the long term?…(More)”.