Public perceptions on data sharing: key insights from the UK and the USA


Paper by Saira Ghafur, Jackie Van Dael, Melanie Leis and Ara Darzi, and Aziz Sheikh: “Data science and artificial intelligence (AI) have the potential to transform the delivery of health care. Health care as a sector, with all of the longitudinal data it holds on patients across their lifetimes, is positioned to take advantage of what data science and AI have to offer. The current COVID-19 pandemic has shown the benefits of sharing data globally to permit a data-driven response through rapid data collection, analysis, modelling, and timely reporting.

Despite its obvious advantages, data sharing is a controversial subject, with researchers and members of the public justifiably concerned about how and why health data are shared. The most common concern is privacy; even when data are (pseudo-)anonymised, there remains a risk that a malicious hacker could, using only a few datapoints, re-identify individuals. For many, it is often unclear whether the risks of data sharing outweigh the benefits.

A series of surveys over recent years indicate that the public holds a range of views about data sharing. Over the past few years, there have been several important data breaches and cyberattacks. This has resulted in patients and the public questioning the safety of their data, including the prospect or risk of their health data being shared with unauthorised third parties.

We surveyed people across the UK and the USA to examine public attitude towards data sharing, data access, and the use of AI in health care. These two countries were chosen as comparators as both are high-income countries that have had substantial national investments in health information technology (IT) with established track records of using data to support health-care planning, delivery, and research. The UK and USA, however, have sharply contrasting models of health-care delivery, making it interesting to observe if these differences affect public attitudes.

Willingness to share anonymised personal health information varied across receiving bodies (figure). The more commercial the purpose of the receiving institution (eg, for an insurance or tech company), the less often respondents were willing to share their anonymised personal health information in both the UK and the USA. Older respondents (≥35 years) in both countries were generally less likely to trust any organisation with their anonymised personal health information than younger respondents (<35 years)…

Despite the benefits of big data and technology in health care, our findings suggest that the rapid development of novel technologies has been received with concern. Growing commodification of patient data has increased awareness of the risks involved in data sharing. There is a need for public standards that secure regulation and transparency of data use and sharing and support patient understanding of how data are used and for what purposes….(More)”.

The Open Innovation in Science research field: a collaborative conceptualisation approach


Paper by Susanne Beck et al: “Openness and collaboration in scientific research are attracting increasing attention from scholars and practitioners alike. However, a common understanding of these phenomena is hindered by disciplinary boundaries and disconnected research streams. We link dispersed knowledge on Open Innovation, Open Science, and related concepts such as Responsible Research and Innovation by proposing a unifying Open Innovation in Science (OIS) Research Framework. This framework captures the antecedents, contingencies, and consequences of open and collaborative practices along the entire process of generating and disseminating scientific insights and translating them into innovation. Moreover, it elucidates individual-, team-, organisation-, field-, and society‐level factors shaping OIS practices. To conceptualise the framework, we employed a collaborative approach involving 47 scholars from multiple disciplines, highlighting both tensions and commonalities between existing approaches. The OIS Research Framework thus serves as a basis for future research, informs policy discussions, and provides guidance to scientists and practitioners….(More)”.

Calling Bullshit: The Art of Scepticism in a Data-Driven World


Book by Carl Bergstrom and Jevin West: “Politicians are unconstrained by facts. Science is conducted by press release. Higher education rewards bullshit over analytic thought. Startup culture elevates bullshit to high art. Advertisers wink conspiratorially and invite us to join them in seeing through all the bullshit — and take advantage of our lowered guard to bombard us with bullshit of the second order. The majority of administrative activity, whether in private business or the public sphere, seems to be little more than a sophisticated exercise in the combinatorial reassembly of bullshit.

We’re sick of it. It’s time to do something, and as educators, one constructive thing we know how to do is to teach people. So, the aim of this course is to help students navigate the bullshit-rich modern environment by identifying bullshit, seeing through it, and combating it with effective analysis and argument.

What do we mean, exactly, by bullshit and calling bullshit? As a first approximation:

Bullshit involves language, statistical figures, data graphics, and other forms of presentation intended to persuade by impressing and overwhelming a reader or listener, with a blatant disregard for truth and logical coherence.

Calling bullshit is a performative utterance, a speech act in which one publicly repudiates something objectionable. The scope of targets is broader than bullshit alone. You can call bullshit on bullshit, but you can also call bullshit on lies, treachery, trickery, or injustice.

In this course we will teach you how to spot the former and effectively perform the latter.

While bullshit may reach its apogee in the political domain, this is not a course on political bullshit. Instead, we will focus on bullshit that comes clad in the trappings of scholarly discourse. Traditionally, such highbrow nonsense has come couched in big words and fancy rhetoric, but more and more we see it presented instead in the guise of big data and fancy algorithms — and these quantitative, statistical, and computational forms of bullshit are those that we will be addressing in the present course.

Of course an advertisement is trying to sell you something, but do you know whether the TED talk you watched last night is also bullshit — and if so, can you explain why? Can you see the problem with the latest New York Times or Washington Post article fawning over some startup’s big data analytics? Can you tell when a clinical trial reported in the New England Journal or JAMA is trustworthy, and when it is just a veiled press release for some big pharma company?…(More)”.

Project Patient Voice


Press Release: “The U.S. Food and Drug Administration today launched Project Patient Voice, an initiative of the FDA’s Oncology Center of Excellence (OCE). Through a new website, Project Patient Voice creates a consistent source of publicly available information describing patient-reported symptoms from cancer trials for marketed treatments. While this patient-reported data has historically been analyzed by the FDA during the drug approval process, it is rarely included in product labeling and, therefore, is largely inaccessible to the public.

“Project Patient Voice has been initiated by the Oncology Center of Excellence to give patients and health care professionals unique information on symptomatic side effects to better inform their treatment choices,” said FDA Principal Deputy Commissioner Amy Abernethy, M.D., Ph.D. “The Project Patient Voice pilot is a significant step in advancing a patient-centered approach to oncology drug development. Where patient-reported symptom information is collected rigorously, this information should be readily available to patients.” 

Patient-reported outcome (PRO) data is collected using questionnaires that patients complete during clinical trials. These questionnaires are designed to capture important information about disease- or treatment-related symptoms. This includes how severe or how often a symptom or side effect occurs.

Patient-reported data can provide additional, complementary information for health care professionals to discuss with patients, specifically when discussing the potential side effects of a particular cancer treatment. In contrast to the clinician-reported safety data in product labeling, the data in Project Patient Voice is obtained directly from patients and can show symptoms before treatment starts and at multiple time points while receiving cancer treatment. 

The Project Patient Voice website will include a list of cancer clinical trials that have available patient-reported symptom data. Each trial will include a table of the patient-reported symptoms collected. Each patient-reported symptom can be selected to display a series of bar and pie charts describing the patient-reported symptom at baseline (before treatment starts) and over the first 6 months of treatment. This information provides insights into side effects not currently available in standard FDA safety tables, including existing symptoms before the start of treatment, symptoms over time, and the subset of patients who did not have a particular symptom prior to starting treatment….(More)”.

Measuring Movement and Social Contact with Smartphone Data: A Real-Time Application to Covid-19


Paper by Victor Couture et al: “Tracking human activity in real time and at fine spatial scale is particularly valuable during episodes such as the COVID-19 pandemic. In this paper, we discuss the suitability of smartphone data for quantifying movement and social contact. We show that these data cover broad sections of the US population and exhibit movement patterns similar to conventional survey data. We develop and make publicly available a location exposure index that summarizes county-to-county movements and a device exposure index that quantifies social contact within venues. We use these indices to document how pandemic-induced reductions in activity vary across people and places….(More)”.

The Misinformation Edition


On-Line Exhibition by the Glass Room: “…In this exhibition – aimed at young people as well as adults – we explore how social media and the web have changed the way we read information and react to it. Learn why finding “fake news” is not as easy as it sounds, and how the term “fake news” is as much a problem as the news it describes. Dive into the world of deep fakes, which are now so realistic that they are virtually impossible to detect. And find out why social media platforms are designed to keep us hooked, and how they can be used to change our minds. You can also read our free Data Detox Kit, which reveals how to tell facts from fiction and why it benefits everyone around us when we take a little more care about what we share…(More)”.

EXPLORE OUR ONLINE EXHIBITION

Rethinking Readiness: A Brief Guide to Twenty-First-Century Megadisasters


Book by Jeff Schlegelmilch: “As human society continues to develop, we have increased the risk of large-scale disasters. From health care to infrastructure to national security, systems designed to keep us safe have also heightened the potential for catastrophe. The constant pressure of climate change, geopolitical conflict, and our tendency to ignore what is hard to grasp exacerbates potential dangers. How can we prepare for and prevent the twenty-first-century disasters on the horizon?

Rethinking Readiness offers an expert introduction to human-made threats and vulnerabilities, with a focus on opportunities to reimagine how we approach disaster preparedness. Jeff Schlegelmilch identifies and explores the most critical threats facing the world today, detailing the dangers of pandemics, climate change, infrastructure collapse, cyberattacks, and nuclear conflict. Drawing on the latest research from leading experts, he provides an accessible overview of the causes and potential effects of these looming megadisasters. The book highlights the potential for building resilient, adaptable, and sustainable systems so that we can be better prepared to respond to and recover from future crises. Thoroughly grounded in scientific and policy expertise, Rethinking Readiness is an essential guide to this century’s biggest challenges in disaster management…(More)”.

Rethinking citizen engagement for an inclusive energy transition


Urban Futures Studio: “In July 2020, we published our new essay ‘What, How and Who? Designing inclusive interactions in the energy transition’ (Bronsvoort, Hoffman and Hajer, 2020). In this essay, we argue that how the interactions between citizens and governments are shaped and enacted, has a large influence on who gets involved and to what extend people feel heard. To apply this approach to cases, we distinguish between three dimensions of interaction:

  • What (the defined object or issue at hand)
  • How (the setting and staging of the interaction)
  • Who (the target groups and protagonists of the process)

Focusing on the issue of form, we argue that processes for interaction between citizens and governments should be designed in a way that is more future oriented, organized over the long term, in closer proximity to citizens and with attention to the powerful role of ‘in-betweeners’ and ‘in-between’ places such as community houses, where people can meet to deliberate on the wide range of possible futures for their neighbourhood. 

Towards a multiplicity of future visions for sustainable cities
The energy transition has major consequences for the way we live, work, move and consume. For such complex transitions, governments need to engage and collaborate with citizens and other stakeholders. Their engagement enriches existing visions on future neighbourhoods, inform local policies and stimulate change. But how do you shape and organize such a participatory process? While governments use a wide range of public participation methods, many researchers have emphasized the limitations of many of these conventional methods with regard to the inclusion of diverse groups of citizens and in bridging discrepancies between government approaches and people’s lived experiences.

Rethinking citizen engagement for an inclusive energy transition
To help rethink citizen engagement, the Urban Futures Studio investigates existing and new approaches to citizen engagement and how they are practised by governments and societal actors. Following our essay research, our next project on citizen engagement includes a study on its relation to experimentation as a novel mode of governance. The goal of this research is to show insights into how citizen engagement manifests itself in the context of experimental governance on the neighbourhood level. By investigating the interactions between citizens, governments and other stakeholders in different types of participatory projects, we aim to gain a better understanding of how citizens are engaged and included in energy transition experiments and how we can improve its level of inclusion.

We use a relational approach of citizen engagement, by which we view participatory processes as collective practices that both shape and are shaped by their ‘matter of concern’, their public and their setting and staging. This view places emphasis on the form and conditions under which the interaction takes place. For example, the initiative of Places of Hope showed that engagement can be organised in diverse ways and can create new collectives….(More)”.

The Atlas of Surveillance


Electronic Frontier Foundation: “Law enforcement surveillance isn’t always secret. These technologies can be discovered in news articles and government meeting agendas, in company press releases and social media posts. It just hasn’t been aggregated before.

That’s the starting point for the Atlas of Surveillance, a collaborative effort between the Electronic Frontier Foundation and the University of Nevada, Reno Reynolds School of Journalism. Through a combination of crowdsourcing and data journalism, we are creating the largest-ever repository of information on which law enforcement agencies are using what surveillance technologies. The aim is to generate a resource for journalists, academics, and, most importantly, members of the public to check what’s been purchased locally and how technologies are spreading across the country.

We specifically focused on the most pervasive technologies, including drones, body-worn cameras, face recognition, cell-site simulators, automated license plate readers, predictive policing, camera registries, and gunshot detection. Although we have amassed more than 5,000 datapoints in 3,000 jurisdictions, our research only reveals the tip of the iceberg and underlines the need for journalists and members of the public to continue demanding transparency from criminal justice agencies….(More)”.

Four Principles for Integrating AI & Good Governance


Oxford Commission on AI and Good Governance: “Many governments, public agencies and institutions already employ AI in providing public services, the distribution of resources and the delivery of governance goods. In the public sector, AI-enabled governance may afford new efficiencies that have the potential to transform a wide array of public service tasks.
But short-sighted design and use of AI can create new problems, entrench existing inequalities, and calcify and ultimately undermine government organizations.

Frameworks for the procurement and implementation of AI in public service have widely remained undeveloped. Frequently, existing regulations and national laws are no longer fit for purpose to ensure
good behaviour (of either AI or private suppliers) and are ill-equipped to provide guidance on the democratic use of AI.
As technology evolves rapidly, we need rules to guide the use of AI in ways that safeguard democratic values. Under what conditions can AI be put into service for good governance?

We offer a framework for integrating AI with good governance. We believe that with dedicated attention and evidence-based policy research, it should be possible to overcome the combined technical and organizational challenges of successfully integrating AI with good governance. Doing so requires working towards:


Inclusive Design: issues around discrimination and bias of AI in relation to inadequate data sets, exclusion of minorities and under-represented
groups, and the lack of diversity in design.
Informed Procurement: issues around the acquisition and development in relation to due diligence, design and usability specifications and the assessment of risks and benefits.
Purposeful Implementation: issues around the use of AI in relation to interoperability, training needs for public servants, and integration with decision-making processes.
Persistent Accountability: issues around the accountability and transparency of AI in relation to ‘black box’ algorithms, the interpretability and explainability of systems, monitoring and auditing…(More)”