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)”.
Daphne Leprince-Ringuet at ZDNet: “A crowdsourcing platform aims to provide better insight into health issues than is currently available….In the age of social media, blogs, and online forums, the most common practice when feeling slightly under the weather has undeniably become to resort to a quick Google search. Unfortunately, when they are not unnecessarily worrying, the answers found on the web are typically inconclusive. That observation is what prompted Israeli entrepreneur Yael Elish to launch StuffThatWorks, an AI-based online platform that collects crowdsourced data about a host of chronic conditions.
The idea being that, unlike Facebook groups or Reddit threads, the information shared by patients is centralized and assessed for quality to readily provide informed data to other users who are enquiring about their own symptoms. Healthline cuts through the confusion with straightforward, expert-reviewed, person-first experiences — all designed to help you make the best decisions. Elish is a former member of the founding team for crowdsourced navigation app Waze, but this time instead of tapping user-generated content to come up with traffic predictions and accident warnings, StuffThatWorks is intended to give users better insights into illness…(More)”.
Trace Labs is a nonprofit organization whose mission is to accelerate
the family reunification of missing persons while training members in
the trade craft of open source intelligence (OSINT)….We crowdsource open source intelligence through both the Trace Labs OSINT Search Party CTFs and Ongoing Operations with our global community. Our highly skilled intelligence analysts then triage the data collected to produce actionable intelligence reports on each missing persons subject. These intelligence reports allow the law enforcement agencies that we work with the ability to quickly see any new details required to reopen a cold case and/or take immediate action on a missing subject.(More)”
Paper by Eva M. Krockow et al: “Antibiotic overprescribing is a global challenge contributing to rising levels of antibiotic resistance and mortality. We test a novel approach to antibiotic stewardship. Capitalising on the concept of “wisdom of crowds”, which states that a group’s collective judgement often outperforms the average individual, we test whether pooling treatment durations recommended by different prescribers can improve antibiotic prescribing. Using international survey data from 787 expert antibiotic prescribers, we run computer simulations to test the performance of the wisdom of crowds by comparing three data aggregation rules across different clinical cases and group sizes. We also identify patterns of prescribing bias in recommendations about antibiotic treatment durations to quantify current levels of overprescribing. Our results suggest that pooling the treatment recommendations (using the median) could improve guideline compliance in groups of three or more prescribers. Implications for antibiotic stewardship and the general improvement of medical decision making are discussed. Clinical applicability is likely to be greatest in the context of hospital ward rounds and larger, multidisciplinary team meetings, where complex patient cases are discussed and existing guidelines provide limited guidance….(More)“
Paper by Katerina Zdravkova: “Crowdsourcing has become a fruitful solution for many activities, promoting the joined power of the masses. Although not formally recognised as an educational model, the first steps towards embracing crowdsourcing as a form of formal learning and teaching have recently emerged. Before taking a dramatic step forward, it should be estimated whether it is feasible, sustainable and socially responsible.
A nice initiative, which intends to set a groundwork for responsible research and innovation and actively implement crowdsourcing for language learning of all citizens regardless of their diversified social, educational, and linguistic backgrounds is enetCollect.
In order to achieve these goals, a sound framework that embraces the ethical and legal considerations should be established. The framework is intended for all the current and prospective creators of crowd-oriented educational systems. It incorporates the ethical issues affecting the three stakeholders: collaborative content creators, prospective users, as well as the institutions intending to implement the approach for educational purposes. The proposed framework offers a practical solution intending to overcome the revealed barriers, which might increase the risk of compromising its main educational goals. If carefully designed and implemented, crowdsourcing might become a very helpful, and at the same time, a very reliable educational model….(More)”.
Report by Craig Matasick: “…innovative new set of citizen engagement practices—collectively known as deliberative democracy—offers important lessons that, when applied to the media development efforts, can help improve media assistance efforts and strengthen independent media environments around the world. At a time when disinformation runs rampant, it is more important than ever to strengthen public demand for credible information, reduce political polarization, and prevent media capture. Deliberative democracy approaches can help tackle these issues by expanding the number and diversity of voices that participate in policymaking, thereby fostering greater collective action and enhancing public support for media reform efforts.
Through a series of five illustrative case studies, the report demonstrates how deliberative democracy practices can be employed in both media development and democracy assistance efforts, particularly in the Global South. Such initiatives produce recommendations that take into account a plurality of voices while building trust between citizens and decision-makers by demonstrating to participants that their issues will be heard and addressed. Ultimately, this process can enable media development funders and practitioners to identify priorities and design locally relevant projects that have a higher likelihood for long-term impact.
– Deliberative democracy approaches, which are characterized by representative participation and moderated deliberation, provide a framework to generate demand-driven media development interventions while at the same time building greater public support for media reform efforts.
– Deliberative democracy initiatives foster collaboration across different segments of society, building trust in democratic institutions, combatting polarization, and avoiding elite capture.
– When employed by news organizations, deliberative approaches provide a better understanding of the issues their audiences care most about and uncover new problems affecting citizens that might not otherwise have come to light….(More)”.
Poster by Geoffrey Henry Siwo: The promise of artificial intelligence (AI) in medicine is advancing rapidly driven by exponential growth in computing speed, data and new modeling techniques such as deep learning. Unfortunately, advancements in AI stand to disproportionately benefit diseases that predominantly affect the developed world because the key ingredients for AI – computational resources, big data and AI expertise – are less accessible in the developing world. Our research on automated mining of biomedical literature indicates that adoption of machine learning algorithms in global health, for example to understand malaria, lags several years behind diseases like cancer.
To shift these inequities, we have been exploring the use of crowdsourced data science challenges as a means to rapidly advance computational models in global health. Data science challenges involve seeking computational solutions for specific, well-defined questions from anyone in the world. Here we describe key lessons from our work in this area and the potential value of data science challenges in accelerating AI for global health.
In one of our first initiatives in this area – the Malaria DREAM Challenge – we invited data scientists from across the world to develop computational models that predict the in vitro and in vivo drug sensitivity of malaria parasites to artemisinin using gene expression datasets. More than 360 individuals drawn from academia, government and startups across 31 countries participated in the challenge. Approximately 100 computational solutions to the problem were generated within a period of 3 months. In addition to this sheer volume of participation, a diverse range of modeling approaches including artificial neural networks and automated machine learning were employed….(More)”.
Bloomberg Cities: “Outdoor dining has been a summer savior in these COVID times, keeping restaurants and the people they employ afloat while bringing sidewalks and streets once hushed by stay-at-home orders back to life.
But with Labor Day now behind us, many city leaders and residents alike are asking, “What’s next?” “What becomes of the vibrant ‘streateries’ once winter comes rolling in?”
Perhaps it’s no surprise that Chicago, notorious for its frigid winters and whipping lakefront winds, is at the forefront of the hunt for an answer. The city recently launched the City of Chicago Winter Dining Challenge to get everyone from designers to dishwashers thinking up new ideas for how to do outdoor eating in the cold in a way that is both appealing and safe for customers and restaurant workers.
More intriguing is just how much interest the competition has generated, including nearly 650 entries from all over the world. There are dozens of takes on warming large patios and small dining pods, including approaches likened to greenhouses, igloos, and yurts; ideas for repurposing parking garages and city buses; furniture-based concepts with heated tables, seats and umbrellas, and even a Swiss-style fondue chalet.
The goal, said Samir Mayekar, Chicago’s Deputy Mayor for Economic and Neighborhood Development, is to surface ideas city leaders would never have thought of. Three winners will get $5,000 each and see their ideas piloted in neighborhoods across the city in October….(More)”.
Paper by Nikolaus Franke, Kathrin Reinsberger and Philipp Topic: “Self-selection has been portrayed to be one of the core reasons for the stunning success of crowdsourcing. It is widely believed that among the mass of potential problem solvers particularly those individuals decide to participate who have the best problem-solving capabilities with regard to the problem at question. Extant research assumes that this self-selection effect is beneficial based on the premise that self-selecting individuals know more about their capabilities and knowledge than the publisher of the task – which frees the organization from costly and error-prone active search.
However, the effectiveness of this core principle has hardly been analyzed, probably because it is extremely difficult to investigate characteristics of those individuals who self-select out. In a unique research design in which we overcome these difficulties by combining behavioral data from a real crowdsourcing contest with data from a survey and archival data, we find that self-selection is actually working in the right direction. Those with particularly strong problem-solving capabilities tend to self-select into the contest and those with low capabilities tend to self-select out. However, this self-selection effect is much weaker than assumed and thus much potential is being lost. This suggests that much more attention needs to be paid to the early stages of crowdsourcing contests and particularly to those the hitherto almost completely overlooked individuals who could provide great solutions but self-select out.”…(More)”.
Paper by Christopher Loynes, Jamal Ouenniche & Johannes De Smedt: “This paper provides the humanitarian community with an automated tool that can detect a disaster using tweets posted on Twitter, alongside a portal to identify local and regional Non-Governmental Organisations (NGOs) that are best-positioned to provide support to people adversely affected by a disaster. The proposed disaster detection tool uses a linear Support Vector Classifier (SVC) to detect man-made and natural disasters, and a density-based spatial clustering of applications with noise (DBSCAN) algorithm to accurately estimate a disaster’s geographic location. This paper provides two original contributions. The first is combining the automated disaster detection tool with the prototype portal for NGO identification. This unique combination could help reduce the time taken to raise awareness of the disaster detected, improve the coordination of aid, increase the amount of aid delivered as a percentage of initial donations and improve aid effectiveness. The second contribution is a general framework that categorises the different approaches that can be adopted for disaster detection. Furthermore, this paper uses responses obtained from an on-the-ground survey with NGOs in the disaster-hit region of Uttar Pradesh, India, to provide actionable insights into how the portal can be developed further…(More)”.