crowdsourcing

‘To own or not to own?’ A study on the determinants and consequences of alternative intellectual property rights arrangements in crowdsourcing for innovation contests

Curated on August 27, 2018 by Stefaan Verhulst

Paper by Nuran Acur, Mariangela Piazza and Giovanni Perrone: “Firms are increasingly engaging in crowdsourcing for innovation to access new knowledge beyond their boundaries; however, scholars are no closer to understanding what guides seeker firms in deciding the level at which to acquire rights from solvers and the effect that this decision has on the performance of crowdsourcing contests.

Integrating Property Rights Theory and the problem solving perspective whist leveraging exploratory interviews and observations, we build a theoretical framework to examine how specific attributes of the technical problem broadcast affect the seekers’ choice between alternative intellectual property rights (IPR) arrangements that call for acquiring or licensing‐in IPR from external solvers (i.e. with high and low degrees of ownership respectively). Each technical problem differs in the knowledge required to be solved as well as in the stage of development it occurs of the innovation process and seeker firms pay great attention to such characteristics when deciding about the IPR arrangement they choose for their contests.

In addition, we analyze how this choice between acquiring and licensing‐in IPR, in turn, influences the performance of the contest. We empirically test our hypotheses analyzing a unique dataset of 729 challenges broadcast on the InnoCentive platform from 2010 to 2016. Our results indicate that challenges related to technical problems in later stages of the innovation process are positively related to the seekers’ preference toward IPR arrangements with a high level of ownership, while technical problems involving a higher number of knowledge domains are not.

Moreover, we found that IPR arrangements with a high level of ownership negatively affect solvers’ participation and that IPR arrangement plays a mediating role between the attributes of the technical problem and the solvers’ self‐selection process. Our article contributes to the open innovation and crowdsourcing literature and provides practical implications for both managers and contest organizers….(More)”.

JPMorgan is quietly building an IBM Watson-like platform

Curated on August 26, 2018 by Stefaan Verhulst

Frank Chaparro at BusinessInsider: “JPMorgan’s corporate and investment bank is best known for advising businesses on billion-dollar acquisitions, helping private unicorns tap into the public markets, and managing the cash of Fortune 500 companies.

But now it is quietly working on a new platform that would go far beyond anything the firm has previously done, using crowdsourcing to accumulate massive amounts of data intended to one day help its clients make complex decisions about how to run their businesses, according to people familiar with the project.

For JPMorgan’s clients like asset-management firms and hedge funds, it could provide new data sets to help investors squeeze out more alpha from their models or better price assets. But JPMorgan is looking to go beyond the buy side to help its large corporate clients as well. The platform could, for example, help retailers figure out where to build their next store, inform manufacturers about how to revamp systems in their factories, and improve logistics management for delivery services companies, the people said.

The platform, called Roar by JPMorgan, would store sensitive private data, such as hospital records or satellite imagery, that’s not in the public domain. Typically, this type of information is exchanged between firms on a bilateral arrangement so it is not improperly used. But Roar would allow clients to tap into this data, which they could then use in a secure fashion to make forecasts and gain business insights….

Right now, the platform is being tested internally with public data and JPMorgan is collaborating with academics to answer questions such as predicting traffic patterns or future air pollution….(More)”.

Trust, Security, and Privacy in Crowdsourcing

Curated on August 20, 2018 by Stefaan Verhulst

Guest Editorial to Special Issue of IEEE Internet of Things Journal: “As we become increasingly reliant on intelligent, interconnected devices in every aspect of our lives, critical trust, security, and privacy concerns are raised as well.

First, the sensing data provided by individual participants is not always reliable. It may be noisy or even faked due to various reasons, such as poor sensor quality, lack of sensor calibration, background noise, context impact, mobility, incomplete view of observations, or malicious attacks. The crowdsourcing applications should be able to evaluate the trustworthiness of collected data in order to filter out the noisy and fake data that may disturb or intrude a crowdsourcing system. Second, providing data (e.g., photographs taken with personal mobile devices) or using IoT applications may compromise data providers’ personal data privacy (e.g., location, trajectory, and activity privacy) and identity privacy. Therefore, it becomes essential to assess the trust of the data while preserving the data providers’ privacy. Third, data analytics and mining in crowdsourcing may disclose the privacy of data providers or related entities to unauthorized parities, which lowers the willingness of participants to contribute to the crowdsourcing system, impacts system acceptance, and greatly impedes its further development. Fourth, the identities of data providers could be forged by malicious attackers to intrude the whole crowdsourcing system. In this context, trust, security, and privacy start to attract a special attention in order to achieve high quality of service in each step of crowdsourcing with regard to data collection, transmission, selection, processing, analysis and mining, as well as utilization.

Trust, security, and privacy in crowdsourcing receives increasing attention. Many methods have been proposed to protect privacy in the process of data collection and processing. For example, data perturbation can be adopted to hide the real data values during data collection. When preprocessing the collected data, data anonymization (e.g., k-anonymization) and fusion can be applied to break the links between the data and their sources/providers. In application layer, anonymity is used to mask the real identities of data sources/providers. To enable privacy-preserving data mining, secure multiparty computation (SMC) and homomorphic encryption provide options for protecting raw data when multiple parties jointly run a data mining algorithm. Through cryptographic techniques, no party knows anything else than its own input and expected results. For data truth discovery, applicable solutions include correlation-based data quality analysis and trust evaluation of data sources. But current solutions are still imperfect, incomprehensive, and inefficient….(More)”.

A platform that puts political lobbying back into the hands of everyday people

Curated on June 24, 2018October 9, 2018 by Stefaan Verhulst

Michael Krumholtz at StartUpBeat: “Amit Thakkar saw first hand how messy and inefficient politics can be from the inside. While working as a political consultant for a decade, Thakkar said he became frustrated with seeing the same old players decide policy with almost no influence from actual constituents or voters.

That’s a large part of why he decided to create LawMaker.io, which bills itself as a revolutionary platform that gives those in the U.S. the chance to create propositions for new laws through crowdsourcing. That allows for support to build for popular ideas that are eventually handed over to legislators to propose them as real laws. Touting itself as a “free lobby for the lobbyless,” Thakkar said its a platform that could very much change the face of U.S. democracy.

“It didn’t make sense to me that such a small group of wealthy and well-connected people had such an outsized influence on the laws that are written and the way our government works,” he told Techli. “I knew there needed to be a free way that all Americans could propose common-sense ideas for laws and influence elected officials in a way that benefitted all Americans instead of just a powerful few.”

Lawmaker.io works by finding ideas at the ground level that can shape politics and then making sure it gets a wider audience after a user proposes a policy idea. It’s then shared widely by the user and suggestions are made for possible amendments to the initial proposal. Support is then gathered until the idea has at least 100 registered supporters and it is eventually sent off to the appropriate legislators.

LawMaker.io recently held its 2nd Lawmaker Challenge to offer up a winning policy proposal to legislators. As the Supreme Court’s Citizen United has become so influential in allowing big money to essentially buy politics, the winning proposal looked to reverse the impacts of the decision and shift back influence to voters over the power of wealthy interests….(More)”.

Can crowdsourcing scale fact-checking up, up, up? Probably not, and here’s why

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Mevan Babakar at NiemanLab: “We foolishly thought that harnessing the crowd was going to require fewer human resources, when in fact it required, at least at the micro level, more.”….There’s no end to the need for fact-checking, but fact-checking teams are usually small and struggle to keep up with the demand. In recent months, organizations like WikiTribune have suggested crowdsourcing as an attractive, low-cost way that fact-checking could scale.

As the head of automated fact-checking at the U.K.’s independent fact-checking organization Full Fact, I’ve had a lot of time to think about these suggestions, and I don’t believe that crowdsourcing can solve the fact-checking bottleneck. It might even make it worse. But — as two notable attempts, TruthSquad and FactcheckEU, have shown — even if crowdsourcing can’t help scale the core business of fact checking, it could help streamline activities that take place around it.

Think of crowdsourced fact-checking as including three components: speed (how quickly the task can be done), complexity (how difficult the task is to perform; how much oversight it needs), and coverage (the number of topics or areas that can be covered). You can optimize for (at most) two of these at a time; the third has to be sacrificed.

High-profile examples of crowdsourcing like Wikipedia, Quora, and Stack Overflow harness and gather collective knowledge, and have proven that large crowds can be used in meaningful ways for complex tasks across many topics. But the tradeoff is speed.

Projects like Gender Balance (which asks users to identify the gender of politicians) and Democracy Club Candidates (which crowdsources information about election candidates) have shown that small crowds can have a big effect when it comes to simple tasks, done quickly. But the tradeoff is broad coverage.

At Full Fact, during the 2015 U.K. general election, we had 120 volunteers aid our media monitoring operation. They looked through the entire media output every day and extracted the claims being made. The tradeoff here was that the task wasn’t very complex (it didn’t need oversight, and we only had to do a few spot checks).

But we do have two examples of projects that have operated at both high levels of complexity, within short timeframes, and across broad areas: TruthSquad and FactCheckEU….(More)”.

Charting a course to government by the crowd, for the crowd

Curated on June 10, 2018August 3, 2018 by Stefaan Verhulst

Nils Röper at The Conversation: “It is a bitter irony that politicians lament the threat to democracy posed by the internet, instead of exploiting its potential to enhance the existing system. Hackers and bots may help to sway elections, but modern technology has allowed the power of the multitude to positively disrupt the world of business and beyond. Now, crowdsourcing should be allowed to shake up the lawmaking process to make democracies more participatory and efficient.

The crowd clearly can be harnessed, whether it is Apple outsourcing the creation of apps, Wikipedia amassing an encyclopedia of unprecedented magnitude, or National Geographic searching for the Tomb of Genghis Khan. If we can agree that the most important factor of a responsive democracy is participation, then there must be a way to capitalise on this collective intelligence.

In fact, political participation hasn’t been this easy since the first days of democracy in Athens 2,500 years ago. Modern social media can turn into a reality the utopian vision of direct civic engagement on a massive scale. Lawmaking can now be married to public consent through technology. The crowd can be unleashed.

Sharing a platform

Governments haven’t completely missed out. Iceland used crowdsourcing to include citizens in its constitutional reform beginning in 2010, while petition websites are increasingly common and have forced parliamentary debates in the UK. US federal agencies have initiated “national dialogues” on topics of public concern and, in many US municipalities, citizens can provide input on budget decisions online and follow instantaneously whether items make it into the budget.

These initiatives show promise in improving what goes into and what comes out of the process of government. However, they are on too small a scale to counter what many believe to be a period of fundamental democratic disenchantment. That is why government needs to throw its weight behind a full online system through which citizens can easily access all ongoing legislative initiatives and provide input during periods of public consultation. That is a challenge, but not mission impossible. Over 2016/2017 a little over 200 bills were introduced in the UK’s parliament.

It could put the power of participation in the hands of the people, and grant greater legitimacy to government. Through websites and apps, the public would be given an intuitive, one-stop shop for democracy, accessible from any device, and which allowed them to engage no matter where they were – on the beach or on the bus. Registered users would get notifications when new legislation was up for consultation. If the legislation were of interest, it could be bookmarked in order to stay updated.

Users would be able to comment on each paragraph of a draft. Moderators would curate the debate by removing irrelevant and inappropriate content and by continuously summarising the most important and common comments to head off an overflow of information. At the end of the consultation period, the moderators could summarise suggestions, concerns and praise in a memo available to policymakers and the public….(More)”.

Using Collaborative Crowdsourcing to Give Voice to Diverse Communities

Curated on May 29, 2018November 15, 2018 by admin

Dennis Di Lorenzo at Campus Technology: “Universities face many critical challenges — student retention, campus safety, curriculum development priorities, alumni engagement and fundraising, and inclusion of diverse populations. In my role as dean of the New York University School of Professional Studies (NYUSPS) for the past four years, and in my prior 20 years of employment in senior-level positions within the school and at NYU, I have become intimately familiar with the complexities and the nuances of such multifaceted challenges.

For the past two years, one of our top priorities at NYUSPS has been striving to address sensitive issues regarding diversity and inclusion….

To identify and address the issues we saw arising from the shifting dynamics we were encountering in our classrooms, my team initially set about gathering feedback from NYUSPS faculty members and students through roundtable discussions. Though many individuals participated in these, we sensed that some were anxious and unwilling to fully share their experiences. We were able to initiate some productive conversations; however, we found they weren’t getting to the heart of the matter. To provide a sense of anonymity that would allow members of the NYUSPS community to express their concerns more freely, we identified a collaboration tool called POPin and utilized it to conduct a series of crowdsourcing campaigns that commenced with faculty members and then proceeded on to students.

Fostering Vital Conversations

Using POPin’s online discussion tool, we were able to scale an intimate and sensitive conversation up to include more than 4,500 students and 2,100 faculty members from a wide variety of countries, cultural and religious backgrounds, gender and sexual identities, economic classes and life stages. Because the tool’s feedback mechanism is both anonymous and interactive, the scope and quality of the conversations increased dramatically….(More)”.

Crowdbreaks: Tracking Health Trends using Public Social Media Data and Crowdsourcing

Curated on May 19, 2018November 15, 2018 by admin

Paper by Martin Mueller and Marcel Salath: “In the past decade, tracking health trends using social media data has shown great promise, due to a powerful combination of massive adoption of social media around the world, and increasingly potent hardware and software that enables us to work with these new big data streams.

At the same time, many challenging problems have been identified. First, there is often a mismatch between how rapidly online data can change, and how rapidly algorithms are updated, which means that there is limited reusability for algorithms trained on past data as their performance decreases over time. Second, much of the work is focusing on specific issues during a specific past period in time, even though public health institutions would need flexible tools to assess multiple evolving situations in real time. Third, most tools providing such capabilities are proprietary systems with little algorithmic or data transparency, and thus little buy-in from the global public health and research community.

Here, we introduce Crowdbreaks, an open platform which allows tracking of health trends by making use of continuous crowdsourced labelling of public social media content. The system is built in a way which automatizes the typical workflow from data collection, filtering, labelling and training of machine learning classifiers and therefore can greatly accelerate the research process in the public health domain. This work introduces the technical aspects of the platform and explores its future use cases…(More)”.

Smarter Crowdsourcing for Anti-Corruption: A Handbook of Innovative Legal, Technical, and Policy Proposals and a Guide to their Implementation

Curated on May 16, 2018November 15, 2018 by admin

Paper by Noveck, Beth Simone; Koga, Kaitlin; Aceves Garcia, Rafael; Deleanu, Hannah; Cantú-Pedraza, Dinorah: “Corruption presents a fundamental threat to the stability and prosperity of Mexico and combating it demands approaches that are both principled and practical. In 2017, the Inter-American Development Bank (IDB) approved project ME-T1351 to support Mexico in its fight against corruption using Open Innovation. Thus, the IDB partnered with the Governance Lab at NYU to support Mexico’s Secretariat of Public Service (Secretaría de la Función Pública) to identify innovative ideas and then turns them into practical implementation plans for the measurement, detection, and prevention of corruption in Mexico using the GovLab’s open innovation methodology named Smarter Crowdsourcing.

The purpose of Smarter Crowdsourcing was to identify concrete solutions that include the use of data analysis and technology to tackle corruption in the public sector. This document contains 13 implementation plans laying out practical ways to address corruption. The plans emerged from “Smarter Crowdsourcing Anti-Corruption,” a method that is an agile process, which begins with robust problem definition followed by online sourcing of global expertise to surface innovative solutions. Smarter Crowdsourcing Anti-Corruption focused on six specific challenges: (i) measuring corruption and its costs, (ii) strengthening integrity in the judiciary, (iii) engaging the public in anti-corruption efforts, (iv) whistleblowing, (v) effective prosecution, and (vi) tracking and analyzing money flows…(More)”.