Invisible Women: Exposing Data Bias in a World Designed for Men

Curated on Posted on by Stefaan Verhulst

Book by Caroline Criado Perez: “Imagine a world where your phone is too big for your hand, where your doctor prescribes a drug that is wrong for your body, where in a car accident you are 47% more likely to be seriously injured, where every week the countless hours of work you do are not recognised or valued. If any of this sounds familiar, chances are that you’re a woman.

Invisible Women shows us how, in a world largely built for and by men, we are systematically ignoring half the population. It exposes the gender data gap – a gap in our knowledge that is at the root of perpetual, systemic discrimination against women, and that has created a pervasive but invisible bias with a profound effect on women’s lives.

Award-winning campaigner and writer Caroline Criado Perez brings together for the first time an impressive range of case studies, stories and new research from across the world that illustrate the hidden ways in which women are forgotten, and the impact this has on their health and well-being. From government policy and medical research, to technology, workplaces, urban planning and the media, Invisible Womenreveals the biased data that excludes women. In making the case for change, this powerful and provocative book will make you see the world anew….(More)”

The Big Nine: How The Tech Titans and Their Thinking Machines Could Warp Humanity

Curated on Posted on by Stefaan Verhulst

Book by Amy Webb:”…A call-to-arms about the broken nature of artificial intelligence, and the powerful corporations that are turning the human-machine relationship on its head. We like to think that we are in control of the future of “artificial” intelligence. The reality, though, is that we–the everyday people whose data powers AI–aren’t actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can’t see and have no input into–one largely free from regulation or oversight. The big nine corporations–Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple–are the new gods of AI and are short-changing our futures to reap immediate financial gain.

In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI–the people working on the system, their motivations, the technology itself–is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don’t share our motivations, desires, or hopes for the future of humanity.

Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations….(More)”

Whose Rules? The Quest for Digital Standards

Curated on Posted on by Stefaan Verhulst

Stephanie Segal at CSIS: “Prime Minister Shinzo Abe of Japan made news at the World Economic Forum in Davos last month when he announced Japan’s aspiration to make the G20 summit in Osaka a launch pad for “world-wide data governance.” This is not the first time in recent memory that Japan has taken a leadership role on an issue of keen economic importance. Most notably, the Trans-Pacific Partnership (TPP) lives on as the Comprehensive and Progressive Agreement on Trans-Pacific Partnership (CPTPP), thanks in large part to Japan’s efforts to keep the trading bloc together after President Trump announced U.S. withdrawal from the TPP. But it’s in the area of data and digital governance that Japan’s efforts will perhaps be most consequential for future economic growth.

Data has famously been called “the new oil” in the global economy. A 2016 report by the McKinsey Global Institute estimated that global data flows contributed $2.8 trillion in value to the global economy back in 2014, while cross-border data flows and digital trade continue to be key drivers of global trade and economic growth. Japan’s focus on data and digital governance is therefore consistent with its recent efforts to support global growth, deepen global trade linkages, and advance regional and global standards.

Data governance refers to the rules directing the collection, processing, storage, and use of data. The proliferation of smart devices and the emergence of a data-driven Internet of Things portends an exponential growth in digital data. At the same time, recent reporting on overly aggressive commercial practices of personal data collection, as well as the separate topic of illegal data breaches, have elevated public awareness and interest in the laws and policies that govern the treatment of data, and personal data in particular. Finally, a growing appreciation of data’s central role in driving innovation and future technological and economic leadership is generating concern in many capitals that different data and digital governance standards and regimes will convey a competitive (dis)advantage to certain countries.

Bringing these various threads together—the inevitable explosion of digital data; the need to protect an individual’s right to privacy; and the appreciation that data has economic value and conveys economic advantage—is precisely why Japan’s initiative is both timely and likely to face significant challenges….(More)”.

The Role of Big Data Analytics in Predicting Suicide

Curated on Posted on by Stefaan Verhulst

Chapter by Ronald C. Kessler et al: “…reviews the long history of using electronic medical records and other types of big data to predict suicide. Although a number of the most recent of these studies used machine learning (ML) methods, these studies were all suboptimal both in the features used as predictors and in the analytic approaches used to develop the prediction models. We review these limitations and describe opportunities for making improvements in future applications.

We also review the controversy among clinical experts about using structured suicide risk assessment tools (be they based on ML or older prediction methods) versus in-depth clinical evaluations of needs for treatment planning. Rather than seeing them as competitors, we propose integrating these different approaches to capitalize on their complementary strengths. We also emphasize the distinction between two types of ML analyses: those aimed at predicting which patients are at highest suicide risk, and those aimed at predicting the treatment options that will be best for individual patients. We explain why both are needed to optimize the value of big data ML methods in addressing the suicide problem….(More)”.

See also How Search Engine Data Enhance the Understanding of Determinants of Suicide in India and Inform Prevention: Observational Study.

The Lancet Countdown: Tracking progress on health and climate change using data from the International Energy Agency (IEA)

Curated on Posted on by Stefaan Verhulst

Victoria Moody at the UK Data Service: “The 2015 Lancet Commission on Health and Climate Change—which assessed responses to climate change with a view to ensuring the highest attainable standards of health for populations worldwide—concluded that “tackling climate change could be the greatest global health opportunity of the 21st century”. The Commission recommended that more accurate national quantification of the health co-benefits and economic impacts of mitigation decisions was essential in promoting a low-carbon transition.

Building on these foundations, the Lancet Countdown: tracking progress on health and climate change was formed as an independent research collaboration…

The partnership comprises 24 academic institutions from every continent, bringing together individuals with a broad range of expertise across disciplines (including climate scientists, ecologists, mathematicians, geographers, engineers, energy, food, and transport experts, economists, social and political scientists, public health professionals, and physicians).

Four of the indicators developed for Working Group 3 (Mitigation actions and health co-benefits) uses International Energy Agency (IEA) data made available by the the IEA via the UK Data Service for use by researchers, learners and teaching staff in UK higher and further education. Additionally, two of the indicators developed for Working Group 4 (Finance and economics) also use IEA data.

Read our impact case study to find our more about the impact and reach of the Lancet Countdown, watch the YouTube film below, read the Lancet Countdown 2018 Report …(More)”

https://web.archive.org/web/2000/https://www.youtube.com/watch?v=moYzcYNX1iM

Urban Computing

Curated on Posted on by Stefaan Verhulst

Book by Yu Zheng:”…Urban computing brings powerful computational techniques to bear on such urban challenges as pollution, energy consumption, and traffic congestion. Using today’s large-scale computing infrastructure and data gathered from sensing technologies, urban computing combines computer science with urban planning, transportation, environmental science, sociology, and other areas of urban studies, tackling specific problems with concrete methodologies in a data-centric computing framework. This authoritative treatment of urban computing offers an overview of the field, fundamental techniques, advanced models, and novel applications.

Each chapter acts as a tutorial that introduces readers to an important aspect of urban computing, with references to relevant research. The book outlines key concepts, sources of data, and typical applications; describes four paradigms of urban sensing in sensor-centric and human-centric categories; introduces data management for spatial and spatio-temporal data, from basic indexing and retrieval algorithms to cloud computing platforms; and covers beginning and advanced topics in mining knowledge from urban big data, beginning with fundamental data mining algorithms and progressing to advanced machine learning techniques. Urban Computing provides students, researchers, and application developers with an essential handbook to an evolving interdisciplinary field….(More)”

Data Was Supposed to Fix the U.S. Education System. Here’s Why It Hasn’t.

Curated on Posted on by Stefaan Verhulst

Simon Rodberg at Harvard Business School: “For too long, the American education system failed too many kids, including far too many poor kids and kids of color, without enough public notice or accountability. To combat this, leaders of all political persuasions championed the use of testing to measure progress and drive better results. Measurement has become so common that in school districts from coast to coast you can now find calendars marked “Data Days,” when teachers are expected to spend time not on teaching, but on analyzing data like end-of-year and mid-year exams, interim assessments, science and social studies and teacher-created and computer-adaptive tests, surveys, attendance and behavior notes. It’s been this way for more than 30 years, and it’s time to try a different approach.

The big numbers are necessary, but the more they proliferate, the less value they add. Data-based answers lead to further data-based questions, testing, and analysis; and the psychology of leaders and policymakers means that the hunt for data gets in the way of actual learning. The drive for data responded to a real problem in education, but bad thinking about testing and data use has made the data cure worse than the disease….

The leadership decision at stake is how much data to collect. I’ve heard variations on “In God we trust; all others bring data” at any number of conferences and beginning-of-school-year speeches. But the mantra “we believe in data” is actually only shorthand for “we believe our actions should be informed by the best available data.” In education, that mostly means testing. In other fields, the kind of process is different, but the issue is the same. The key question is not, “will the data be useful?” (of course it can be) or, “will the data be interesting?” (Yes, again.) The proper question for leaders to ask is: will the data help us make better-enough decisions to be worth the cost of getting and using it? So far, the answer is “no.”

Nationwide data suggests that the growth of data-driven schooling hasn’t worked even by its own lights. Harvard professor Daniel Koretz says “The best estimate is that test-based accountability may have produced modest gains in elementary-school mathematics but no appreciable gains in either reading or high-school mathematics — even though reading and mathematics have been its primary focus.”

We wanted data to help us get past the problem of too many students learning too little, but it turns out that data is an insufficient, even misleading answer. It’s possible that all we’ve learned from our hyper-focus on data is that better instruction won’t come from more detailed information, but from changing what people do. That’s what data-driven reform is meant for, of course: convincing teachers of the need to change and focusing where they need to change….(More)”.

The Internet of Bodies: A Convenient—and, Yes, Creepy—New Platform for Data Discovery

Curated on Posted on by Stefaan Verhulst

David Horrigan at ALM: “In the Era of the Internet of Things, we’ve become (at least somewhat) comfortable with our refrigerators knowing more about us than we know about ourselves and our Apple watches transmitting our every movement. The Internet of Things has even made it into the courtroom in cases such as the hot tub saga of Amazon Echo’s Alexa in State v. Bates and an unfortunate wife’s Fitbit in State v. Dabate.

But the Internet of Bodies?…

The Internet of Bodies refers to the legal and policy implications of using the human body as a technology platform,” said Northeastern University law professor Andrea Matwyshyn, who works also as co-director of Northeastern’s Center for Law, Innovation, and Creativity (CLIC).

“In brief, the Internet of Things (IoT) is moving onto and inside the human body, becoming the Internet of Bodies (IoB),” Matwyshyn added….


The Internet of Bodies is not merely a theoretical discussion of what might happen in the future. It’s happening already.

Former U.S. Vice President Dick Cheney revealed in 2013 that his physicians ordered the wireless capabilities of his heart implant disabled out of concern for potential assassin hackers, and in 2017, the U.S. Food and Drug Administration recalled almost half a million pacemakers over security issues requiring a firmware update.

It’s not just former vice presidents and heart patients becoming part of the Internet of Bodies. Northeastern’s Matwyshyn notes that so-called “smart pills” with sensors can report back health data from your stomach to smartphones, and a self-tuning brain implant is being tested to treat Alzheimer’s and Parkinson’s.

So, what’s not to like?

Better with Bacon?

“We are attaching everything to the Internet whether we need to or not,” Matwyshyn said, calling it the “Better with Bacon” problem, noting that—as bacon has become a popular condiment in restaurants—chefs are putting it on everything from drinks to cupcakes.

“It’s great if you love bacon, but not if you’re a vegetarian or if you just don’t like bacon. It’s not a bonus,” Matwyshyn added.

Matwyshyn’s bacon analogy raises interesting questions: Do we really need to connect everything to the Internet? Do the data privacy and data protection risks outweigh the benefits?

The Northeastern Law professor divides these IoB devices into three generations: 1) “body external” devices, such as Fitbits and Apple watches, 2) “body internal” devices, including Internet-connected pacemakers, cochlear implants, and digital pills, and 3) “body embedded” devices, hardwired technology where the human brain and external devices meld, where a human body has a real time connection to a remote machine with live updates.

Chip Party for Chipped Employees

A Wisconsin company, Three Square Market, made headlines in 2017—including an appearance on The Today Show—when the company microchipped its employees, not unlike what veterinarians do with the family pet. Not surprisingly, the company touted the benefits of implanting microchips under the skin of employees, including being able to wave one’s hand at a door instead of having to carry a badge or use a password….(More)”.

High-performance medicine: the convergence of human and artificial intelligence

Curated on Posted on by Stefaan Verhulst

Eric Topol in Nature: “The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to have an impact at three levels: for clinicians, predominantly via rapid, accurate image interpretation; for health systems, by improving workflow and the potential for reducing medical errors; and for patients, by enabling them to process their own data to promote health. The current limitations, including bias, privacy and security, and lack of transparency, along with the future directions of these applications will be discussed in this article. Over time, marked improvements in accuracy, productivity, and workflow will likely be actualized, but whether that will be used to improve the patient–doctor relationship or facilitate its erosion remains to be seen….(More)”.

The Datafication of Employment

Curated on Posted on by Stefaan Verhulst

Report by Sam Adler-Bell and Michelle Miller at the Century Foundation: “We live in a surveillance society. Our every preference, inquiry, whim, desire, relationship, and fear can be seen, recorded, and monetized by thousands of prying corporate eyes. Researchers and policymakers are only just beginning to map the contours of this new economy—and reckon with its implications for equity, democracy, freedom, power, and autonomy.

For consumers, the digital age presents a devil’s bargain: in exchange for basically unfettered access to our personal data, massive corporations like Amazon, Google, and Facebook give us unprecedented connectivity, convenience, personalization, and innovation. Scholars have exposed the dangers and illusions of this bargain: the corrosion of personal liberty, the accumulation of monopoly power, the threat of digital redlining,1 predatory ad-targeting,2 and the reification of class and racial stratification.3 But less well understood is the way data—its collection, aggregation, and use—is changing the balance of power in the workplace.

This report offers some preliminary research and observations on what we call the “datafication of employment.” Our thesis is that data-mining techniques innovated in the consumer realm have moved into the workplace. Firms who’ve made a fortune selling and speculating on data acquired from consumers in the digital economy are now increasingly doing the same with data generated by workers. Not only does this corporate surveillance enable a pernicious form of rent-seeking—in which companies generate huge profits by packaging and selling worker data in marketplace hidden from workers’ eyes—but also, it opens the door to an extreme informational asymmetry in the workplace that threatens to give employers nearly total control over every aspect of employment.

The report begins with an explanation of how a regime of ubiquitous consumer surveillance came about, and how it morphed into worker surveillance and the datafication of employment. The report then offers principles for action for policymakers and advocates seeking to respond to the harmful effects of this new surveillance economy. The final sections concludes with a look forward at where the surveillance economy is going, and how researchers, labor organizers, and privacy advocates should prepare for this changing landscape….(More)”