Collection

An Overview of National AI Strategies

Curated on August 28, 2018 by Stefaan Verhulst

Medium Article by Tim Dutton: “The race to become the global leader in artificial intelligence (AI) has officially begun. In the past fifteen months, Canada, China, Denmark, the EU Commission, Finland, France, India, Italy, Japan, Mexico, the Nordic-Baltic region, Singapore, South Korea, Sweden, Taiwan, the UAE, and the UK have all released strategies to promote the use and development of AI. No two strategies are alike, with each focusing on different aspects of AI policy: scientific research, talent development, skills and education, public and private sector adoption, ethics and inclusion, standards and regulations, and data and digital infrastructure.

This article summarizes the key policies and goals of each strategy, as well as related policies and initiatives that have announced since the release of the initial strategies. It also includes countries that have announced their intention to develop a strategy or have related AI policies in place….(More)”.

‘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)”.

Citizen science, public policy

Curated on August 26, 2018 by Stefaan Verhulst

Paper by Christi J. Guerrini, Mary A. Majumder, Meaganne J. Lewellyn, and Amy L. McGuire in Science: “Citizen science initiatives that support collaborations between researchers and the public are flourishing. As a result of this enhanced role of the public, citizen science demonstrates more diversity and flexibility than traditional science and can encompass efforts that have no institutional affiliation, are funded entirely by participants, or continuously or suddenly change their scientific aims.

But these structural differences have regulatory implications that could undermine the integrity, safety, or participatory goals of particular citizen science projects. Thus far, citizen science appears to be addressing regulatory gaps and mismatches through voluntary actions of thoughtful and well-intentioned practitioners.

But as citizen science continues to surge in popularity and increasingly engage divergent interests, vulnerable populations, and sensitive data, it is important to consider the long-term effectiveness of these private actions and whether public policies should be adjusted to complement or improve on them. Here, we focus on three policy domains that are relevant to most citizen science projects: intellectual property (IP), scientific integrity, and participant protections….(More)”.

How Social Media Came To The Rescue After Kerala’s Floods

Curated on August 23, 2018 by Stefaan Verhulst

Kamala Thiagarajan at NPR: Devastating rainfall followed by treacherous landslides have killed 210 people since August 8 and displaced over a million in the southern Indian state of Kerala. India’s National Disaster Relief Force launched its biggest ever rescue operation in the state, evacuating over 10,000 people. The Indian army and the navy were deployed as well.

But they had some unexpected assistance.

Thousands of Indian citizens used mobile phone technology and social media platforms to mobilize relief efforts….

In many other cases, it was ordinary folk who harnessed social media and their own resources to play a role in relief and rescue efforts.

As the scope of the disaster became clear, the state government of Kerala reached out to software engineers from around the world. They joined hands with the state-government-run Information Technology Cell, coming together on Slack, a communications platform, to create the website www.keralarescue.in

The website allowed volunteers who were helping with disaster relief in Kerala’s many flood-affected districts to share the needs of stranded people so that authorities could act.

Johann Binny Kuruvilla, a travel blogger, was one of many volunteers. He put in 14-hour shifts at the District Emergency Operations Center in Ernakulam, Kochi.

The first thing he did, he says, was to harness the power of Whatsapp, a critical platform for dispensing information in India. He joined five key Whatsapp groups with hundreds of members who were coordinating rescue and relief efforts. He sent them his number and mentioned that he would be in a position to communicate with a network of police, army and navy personnel. Soon he was receiving an average of 300 distress calls a day from people marooned at home and faced with medical emergencies.

No one trained volunteers like Kuruvilla. “We improvised and devised our own systems to store data,” he says. He documented the information he received on Excel spreadsheets before passing them on to authorities.

He was also the contact point for INSPIRE, a fraternity of mechanical engineering students at a government-run engineering college at Barton Hill in Kerala. The students told him they had made nearly 300 power banks for charging phones, using four 1.5 volt batteries and cables, and, he says, “asked us if we could help them airdrop it to those stranded in flood-affected areas.” A power bank could boost a mobile phone’s charge by 20 percent in minutes, which could be critical for people without access to electricity. Authorities agreed to distribute the power banks, wrapping them in bubble wrap and airdropping them to areas where people were marooned.

Some people took to social media to create awareness of the aftereffects of the flooding.

Anand Appukuttan, 38, is a communications designer. Working as a consultant he currently lives in Chennai, 500 miles by road from Kerala, and designs infographics, mobile apps and software for tech companies. Appukuttan was born and brought up in Kottayam, a city in South West Kerala. When he heard of the devastation caused by the floods, he longed to help. A group of experts on disaster management reached out to him over Facebook on August 18, asking if he would share his time and expertise in creating flyers for awareness; he immediately agreed….(More)”.

Self-Invasion And The Invaded Self

Curated on August 21, 2018 by Stefaan Verhulst

Rochelle Gurstein in the Baffler: “WHAT DO WE LOSE WHEN WE LOSE OUR PRIVACY? This question has become increasingly difficult to answer, living as we do in a society that offers boundless opportunities for men and women to expose themselves (in all dimensions of that word) as never before, to commit what are essentially self-invasions of privacy. Although this is a new phenomenon, it has become as ubiquitous as it is quotidian, and for that reason, it is perhaps one of the most telling signs of our time. To get a sense of the sheer range of unconscious exhibitionism, we need only think of the popularity of reality TV shows, addiction-recovery memoirs, and cancer diaries. Then there are the banal but even more conspicuous varieties, like soaring, all-glass luxury apartment buildings and hotels in which inhabitants display themselves in all phases of their private lives to the casual glance of thousands of city walkers below. Or the incessant sound of people talking loudly—sometimes gossiping, sometimes crying—on their cell phones, broadcasting to total strangers the intimate details of their lives.

And, of course, there are now unprecedented opportunities for violating one’s own privacy, furnished by the technology of the internet. The results are everywhere, from selfies and Instagrammed trivia to the almost automatic, everyday activity of Facebook users registering their personal “likes” and preferences. (As we recently learned, this online pastime is nowhere near as private as we had been led to believe; more than fifty million users’ idly generated “data” was “harvested” by Cambridge Analytica to make “personality profiles” that were then used to target voters with advertisements from Donald Trump’s presidential campaign.)

Beyond these branded and aggressively marketed forums for self-invasions of privacy there are all the giddy, salacious forms that circulate in graphic images and words online—the sort that led not so long ago to the downfall of Anthony Weiner. The mania for attention of any kind is so pervasive—and the invasion of privacy so nonchalant—that many of us no longer notice, let alone mind, what in the past would have been experienced as insolent violations of privacy….(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)”.

What is mechanistic evidence, and why do we need it for evidence-based policy?

Curated on August 20, 2018October 23, 2018 by Stefaan Verhulst

Paper by Caterina Marchionni and Samuli Reijula: “It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so. Although agreeing with the spirit of this proposal, we argue that the underlying conception of mechanistic evidence as evidence that is different in kind from correlational, difference-making or statistical evidence, does not correctly capture the role that information about mechanisms should play in evidence-based policy. We offer an alternative account of mechanistic evidence as information concerning the causal pathway connecting the policy intervention to its outcome. Not only can this be analyzed as evidence of difference-making, it is also to be found at any level and is obtainable by a broad range of methods, both experimental and observational. Using behavioral policy as an illustration, we draw the implications of this revised understanding of mechanistic evidence for debates concerning policy extrapolation, evidence hierarchies, and evidence integration…(More)”.

Data Science Thinking: The Next Scientific, Technological and Economic Revolution

Curated on August 20, 2018 by Stefaan Verhulst

Book by Longbing Cao: “This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists?

Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.

The topics cover an extremely wide spectrum of essential and relevant aspects of data science, spanning its evolution, concepts, thinking, challenges, discipline, and foundation, all the way to industrialization, profession, education, and the vast array of opportunities that data science offers. The book’s three parts each detail layers of these different aspects….(More)”.