Geospatial Data Market Study

Curated on Posted on by Stefaan Verhulst

Study by Frontier Economics: “Frontier Economics was commissioned by the Geospatial Commission to carry out a detailed economic study of the size, features and characteristics of the UK geospatial data market. The Geospatial Commission was established within the Cabinet Office in 2018, as an independent, expert committee responsible for setting the UK’s Geospatial Strategy and coordinating public sector geospatial activity. The Geospatial Commission’s aim is to unlock the significant economic, social and environmental opportunities offered by location data. The UK’s Geospatial Strategy (2020) sets out how the UK can unlock the full power of location data and take advantage of the significant economic, social and environmental opportunities offered by location data….

Like many other forms of data, the value of geospatial data is not limited to the data creator or data user. Value from using geospatial data can be subdivided into several different categories, based on who the value accrues to:

Direct use value: where value accrues to users of geospatial data. This could include government using geospatial data to better manage public assets like roadways.

Indirect use value: where value is also derived by indirect beneficiaries who interact with direct users. This could include users of the public assets who benefit from better public service provision.

Spillover use value: value that accrues to others who are not a direct data user or indirect beneficiary. This could, for example, include lower levels of emissions due to improvement management of the road network by government. The benefits of lower emissions are felt by all of society even those who do not use the road network.

As the value from geospatial data does not always accrue to the direct user of the data, there is a risk of underinvestment in geospatial technology and services. Our £6 billion estimate of turnover for a subset of geospatial firms in 2018 does not take account of these wider economic benefits that “spill over” across the UK economy, and generate additional value. As such, the value that geospatial data delivers is likely to be significantly higher than we have estimated and is therefore an area for potential future investment….(More)”.

Introducing Reach: find and track research being put into action

Curated on Posted on by Stefaan Verhulst

Blog by Dawn Duhaney: “At Wellcome Data Labs we’re releasing our first product, Reach. Our goal is to support funding organisations and researchers by making it easier to find and track scientific research being put into action by governments and global health organisations.

https://reach.wellcomedatalabs.org/
https://reach.wellcomedatalabs.org/

We focused on solving this problem in collaboration with our internal Insights and Analysis team for Wellcome and with partner organisations before deciding to release Reach more widely.

We found that evaluation teams wanted tools to help them measure the influence academic research was having on policy making institutions. We noticed that it is often challenging to track how scientific evidence makes its way into policy making. Institutions like the UK Government and the World Health Organisation have hundreds of thousands of policy documents available — it’s a heavily manual task to search through them to find evidence of our funded research.

At Wellcome we have some established methods for collecting evidence of policy influence from our funded research such as end of scheme reporting and via word of mouth. Through these methods we found great examples of how funded research was being put into policy and practice by government and global health organisations.

One example is from Kenya. The KEMRI Research Programme — a collaboration between the Kenyan Medical Research Institute, Wellcome and Oxford University launched a research programme to improve maternal health in 2005. Their research was cited in the World Health Organisation and with advocacy efforts from the KEMRI team influenced the development of new Kenyan national guidelines of paediatric care.

In Wellcome Data Labs we wanted to build a tool that would aid the discovery of evidence based policy making and be a step in the process of assessing research influence for evaluators, researchers and funding institutions….(More)”.

Malicious Uses and Abuses of Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

Report by Europol, the United Nations Interregional Crime and Justice Research Institute (UNICRI) and Trend Micro: “… looking into current and predicted criminal uses of artificial intelligence (AI)… The report provides law enforcers, policy makers and other organizations with information on existing and potential attacks leveraging AI and recommendations on how to mitigate these risks.

“AI promises the world greater efficiency, automation and autonomy. At a time where the public is getting increasingly concerned about the possible misuse of AI, we have to be transparent about the threats, but also look into the potential benefits from AI technology.” said Edvardas Šileris, Head of Europol’s Cybercrime Centre. “This report will help us not only to anticipate possible malicious uses and abuses of AI, but also to prevent and mitigate those threats proactively. This is how we can unlock the potential AI holds and benefit from the positive use of AI systems.”

The report concludes that cybercriminals will leverage AI both as an attack vector and an attack surface. Deepfakes are currently the best-known use of AI as an attack vector. However, the report warns that new screening technology will be needed in the future to mitigate the risk of disinformation campaigns and extortion, as well as threats that target AI data sets.

For example, AI could be used to support:

  • Convincing social engineering attacks at scale
  • Document-scraping malware to make attacks more efficient
  • Evasion of image recognition and voice biometrics
  • Ransomware attacks, through intelligent targeting and evasion
  • Data pollution, by identifying blind spots in detection rules..

The three organizations make several recommendations to conclude the report:

Interoperability as a tool for competition regulation

Curated on Posted on by Stefaan Verhulst

Paper by Ian Brown: “Interoperability is a technical mechanism for computing systems to work together – even if they are from competing firms. An interoperability requirement for large online platforms has been suggested by the European Commission as one ex ante (up-front rule) mechanism in its proposed Digital Markets Act (DMA), as a way to encourage competition. The policy goal is to increase choice and quality for users, and the ability of competitors to succeed with better services. The application would be to the largest online platforms, such as Facebook, Google, Amazon, smartphone operating systems (e.g. Android/iOS), and their ancillary services, such as payment and app stores.

This report analyses up-front interoperability requirements as a pro-competition policy tool for regulating large online platforms, exploring the economic and social rationales and possible regulatory mechanisms. It is based on a synthesis of recent comprehensive policy re-views of digital competition in major industrialised economies, and related academic literature, focusing on areas of emerging consensus while noting important disagreements. It draws particularly on the Vestager, Furman and Stigler reviews, and the UK Competition and Markets Authority’s study on online platforms and digital advertising. It also draws on interviews with software developers, platform operators, government officials, and civil society experts working in this field….(More)”.

Facial-recognition research needs an ethical reckoning

Curated on Posted on by Stefaan Verhulst

Editorial in Nature: “…As Nature reports in a series of Features on facial recognition this week, many in the field are rightly worried about how the technology is being used. They know that their work enables people to be easily identified, and therefore targeted, on an unprecedented scale. Some scientists are analysing the inaccuracies and biases inherent in facial-recognition technology, warning of discrimination, and joining the campaigners calling for stronger regulation, greater transparency, consultation with the communities that are being monitored by cameras — and for use of the technology to be suspended while lawmakers reconsider where and how it should be used. The technology might well have benefits, but these need to be assessed against the risks, which is why it needs to be properly and carefully regulated.Is facial recognition too biased to be let loose?

Responsible studies

Some scientists are urging a rethink of ethics in the field of facial-recognition research, too. They are arguing, for example, that scientists should not be doing certain types of research. Many are angry about academic studies that sought to study the faces of people from vulnerable groups, such as the Uyghur population in China, whom the government has subjected to surveillance and detained on a mass scale.

Others have condemned papers that sought to classify faces by scientifically and ethically dubious measures such as criminality….One problem is that AI guidance tends to consist of principles that aren’t easily translated into practice. Last year, the philosopher Brent Mittelstadt at the University of Oxford, UK, noted that at least 84 AI ethics initiatives had produced high-level principles on both the ethical development and deployment of AI (B. Mittelstadt Nature Mach. Intell. 1, 501–507; 2019). These tended to converge around classical medical-ethics concepts, such as respect for human autonomy, the prevention of harm, fairness and explicability (or transparency). But Mittelstadt pointed out that different cultures disagree fundamentally on what principles such as ‘fairness’ or ‘respect for autonomy’ actually mean in practice. Medicine has internationally agreed norms for preventing harm to patients, and robust accountability mechanisms. AI lacks these, Mittelstadt noted. Specific case studies and worked examples would be much more helpful to prevent ethics guidance becoming little more than window-dressing….(More)”.

Remaking the Commons: How Digital Tools Facilitate and Subvert the Common Good

Curated on Posted on by Stefaan Verhulst

Paper by Jessica Feldman:”This scoping paper considers how digital tools, such as ICTs and AI, have failed to contribute to the “common good” in any sustained or scalable way. This is attributed to a problem that is at once political-economic and technical.

Many digital tools’ business models are predicated on advertising: framing the user as an individual consumer-to-be-targeted, not as an organization, movement, or any sort of commons. At the level of infrastructure and hardware, the increased privatization and centralization of transmission and production leads to a dangerous bottlenecking of communication power, and to labor and production practices that are undemocratic and damaging to common resources.

These practices escalate collective action problems, pose a threat to democratic decision making, aggravate issues of economic and labor inequality, and harm the environment and health. At the same time, the growth of both AI and online community formation raise questions around the very definition of human subjectivity and modes of relationality. Based on an operational definition of the common good grounded in ethics of care, sustainability, and redistributive justice, suggestions are made for solutions and further research in the areas of participatory design, digital democracy, digital labor, and environmental sustainability….(More)”

Google launches new tool to help cities stay cool

Curated on Posted on by Stefaan Verhulst

Article by Justine Calma: “Google unveiled a tool today that could help cities keep their residents cool by mapping out where trees are needed most. Cities tend to be warmer than surrounding areas because buildings and asphalt trap heat. An easy way to cool metropolitan areas down is to plant more trees in neighborhoods where they’re sparse.

Google’s new Tree Canopy Lab uses aerial imagery and Google’s AI to figure out where every tree is in a city. Tree Canopy Lab puts that information on an interactive map along with additional data on which neighborhoods are more densely populated and are more vulnerable to high temperatures. The hope is that planting new trees in these areas could help cities adapt to a warming world and save lives during heat waves.

Google piloted Tree Canopy Lab in Los Angeles. Data on hundreds more cities is on the way, the company says. City planners interested in using the tool in the future can reach out to Google through a form it posted along with today’s announcement.

“We’ll be able to really home in on where the best strategic investment will be in terms of addressing that urban heat,” says Rachel Malarich, Los Angeles’ first city forest officer.

Google claims that its new tool can save cities like Los Angeles time when it comes to taking inventory of their trees. That’s often done by sending people to survey each block. Los Angeles has also used LIDAR technology to map their urban forest in the past, which uses a laser sensor to detect the trees — but that process was expensive and slow, according to Malarich. Google’s new service, on the other hand, is free to use and will be updated regularly using images the company already takes by plane for Google Maps….(More)”.

How the U.S. Military Buys Location Data from Ordinary Apps

Curated on Posted on by Stefaan Verhulst

Joseph Cox at Vice: “The U.S. military is buying the granular movement data of people around the world, harvested from innocuous-seeming apps, Motherboard has learned. The most popular app among a group Motherboard analyzed connected to this sort of data sale is a Muslim prayer and Quran app that has more than 98 million downloads worldwide. Others include a Muslim dating app, a popular Craigslist app, an app for following storms, and a “level” app that can be used to help, for example, install shelves in a bedroom.

Through public records, interviews with developers, and technical analysis, Motherboard uncovered two separate, parallel data streams that the U.S. military uses, or has used, to obtain location data. One relies on a company called Babel Street, which creates a product called Locate X. U.S. Special Operations Command (USSOCOM), a branch of the military tasked with counterterrorism, counterinsurgency, and special reconnaissance, bought access to Locate X to assist on overseas special forces operations. The other stream is through a company called X-Mode, which obtains location data directly from apps, then sells that data to contractors, and by extension, the military.

The news highlights the opaque location data industry and the fact that the U.S. military, which has infamously used other location data to target drone strikes, is purchasing access to sensitive data. Many of the users of apps involved in the data supply chain are Muslim, which is notable considering that the United States has waged a decades-long war on predominantly Muslim terror groups in the Middle East, and has killed hundreds of thousands of civilians during its military operations in Pakistan, Afghanistan, and Iraq. Motherboard does not know of any specific operations in which this type of app-based location data has been used by the U.S. military.

The apps sending data to X-Mode include Muslim Pro, an app that reminds users when to pray and what direction Mecca is in relation to the user’s current location. The app has been downloaded over 50 million times on Android, according to the Google Play Store, and over 98 million in total across other platforms including iOS, according to Muslim Pro’s website….(More)”.

Data could hold the key to stopping Alzheimer’s

Curated on Posted on by Stefaan Verhulst

Blog post by Bill Gates: “My family loves to do jigsaw puzzles. It’s one of our favorite activities to do together, especially when we’re on vacation. There is something so satisfying about everyone working as a team to put down piece after piece until finally the whole thing is done.

In a lot of ways, the fight against Alzheimer’s disease reminds me of doing a puzzle. Your goal is to see the whole picture, so that you can understand the disease well enough to better diagnose and treat it. But in order to see the complete picture, you need to figure out how all of the pieces fit together.

Right now, all over the world, researchers are collecting data about Alzheimer’s disease. Some of these scientists are working on drug trials aimed at finding a way to stop the disease’s progression. Others are studying how our brain works, or how it changes as we age. In each case, they’re learning new things about the disease.

But until recently, Alzheimer’s researchers often had to jump through a lot of hoops to share their data—to see if and how the puzzle pieces fit together. There are a few reasons for this. For one thing, there is a lot of confusion about what information you can and can’t share because of patient privacy. Often there weren’t easily available tools and technologies to facilitate broad data-sharing and access. In addition, pharmaceutical companies invest a lot of money into clinical trials, and often they aren’t eager for their competitors to benefit from that investment, especially when the programs are still ongoing.

Unfortunately, this siloed approach to research data hasn’t yielded great results. We have only made incremental progress in therapeutics since the late 1990s. There’s a lot that we still don’t know about Alzheimer’s, including what part of the brain breaks down first and how or when you should intervene. But I’m hopeful that will change soon thanks in part to the Alzheimer’s Disease Data Initiative, or ADDI….(More)“.

CrowdHeritage: Improving the quality of Cultural Heritage through crowdsourcing methods

Curated on Posted on by Stefaan Verhulst

Paper by Maria Ralli et al: “The lack of granular and rich descriptive metadata highly affects the discoverability and usability of the digital content stored in museums, libraries and archives, aggregated and served through Europeana, thus often frustrating the user experience offered by these institutions’ portals. In this context, metadata enrichment services through automated analysis and feature extraction along with crowdsourcing annotation services can offer a great opportunity for improving the metadata quality of digital cultural content in a scalable way, while at the same time engaging different user communities and raising awareness about cultural heritage assets. Such an effort is Crowdheritage, an open crowdsourcing platform that aims to employ machine and human intelligence in order to improve the digital cultural content metadata quality….(More)”.