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on Big Data |
| By: | Gabrielle Berman; Kerry Albright |
| Abstract: | In an era of increasing dependence on data science and big data, the voices of one set of major stakeholders – the world’s children and those who advocate on their behalf – have been largely absent. A recent paper estimates one in three global internet users is a child, yet there has been little rigorous debate or understanding of how to adapt traditional, offline ethical standards for research involving data collection from children, to a big data, online environment (Livingstone et al., 2015). This paper argues that due to the potential for severe, long-lasting and differential impacts on children, child rights need to be firmly integrated onto the agendas of global debates about ethics and data science. The authors outline their rationale for a greater focus on child rights and ethics in data science and suggest steps to move forward, focusing on the various actors within the data chain including data generators, collectors, analysts and end-users. It concludes by calling for a much stronger appreciation of the links between child rights, ethics and data science disciplines and for enhanced discourse between stakeholders in the data chain, and those responsible for upholding the rights of children, globally. |
| Keywords: | children; data collection; data processing programmes; data protection; ethics; internet; research; |
| Date: | 2017 |
| URL: | http://d.repec.org/n?u=RePEc:ucf:inwopa:inwopa907&r=big |
| By: | Sander van der Hoog |
| Abstract: | A very timely issue for economic agent-based models (ABMs) is their empirical estimation. This paper describes a line of research that could resolve the issue by using machine learning techniques, using multi-layer artificial neural networks (ANNs), or so called Deep Nets. The seminal contribution by Hinton et al. (2006) introduced a fast and efficient training algorithm called Deep Learning, and there have been major breakthroughs in machine learning ever since. Economics has not yet benefited from these developments, and therefore we believe that now is the right time to apply Deep Learning and multi-layered neural networks to agent-based models in economics. |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1706.06302&r=big |
| By: | Frédéric Marty (Observatoire français des conjonctures économiques) |
| Abstract: | Les algorithmes de prix mis en œuvre par des firmes concurrentes peuvent constituer le support de collusions. Les ressources offertes par le Big Data, les possibilités d’ajustement des prix en temps réel et l’analyse prédictive peuvent permettre d’atteindre rapidement et de maintenir durablement des équilibres de collusion tacite. Le recours à l’intelligence artificielle pose un enjeu spécifique en ce sens que l’algorithme peut découvrir de lui-même l’intérêt d’un accord tacite de non-agression et que l’analyse de son processus décisionnel est particulièrement difficile. Ce faisant la sanction de l’entente sur la base du droit des pratiques anticoncurrentielles ne va pas de soi. L’article explore donc les voies de régulation possibles, que celles-ci passent par des audits ou par l’activation de règles de responsabilité. |
| Keywords: | Algorithmes des prix; Intelligence artificielle; Collusion tacite; Règles de responsabilité; Régles de concurrence |
| JEL: | K21 K23 L41 |
| Date: | 2017–05 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/4qghag40qc8g0r254fpopgv74r&r=big |
| By: | Marius Brulhart (Faculté des Hautes Etudes Commerciales (HEC Lausanne) (HEC Lausanne)); Céline Carrère (Geneva School of Economic and Management Univeristé de Genève); Frederic Robert-Nicoud (Center for Economic Policy Research) |
| Abstract: | Comment l'ouverture au commerce international affecte-t-elle les régions qui y sont le plus exposées de par leur proximité aux frontières? Ce document résume les résultats de recherches empiriques récentes sur la question. Nos résultats démontrent que l'emploi et les salaires des bourgades et villages proches des frontières internationales croissent plus rapidement lors d'épisodes de libéralisation du commerce international que leurs équivalents plus éloignés de la frontière. Les bourgs les plus grands bénéficient d'avantage sous forme de croissance des salaires. Ces résultats sont obtenus sur la base d'une analyse quasi-expérimentale de l'Autriche avant et après la chute du Rideau de fer. Une analyse à l'échelle du monde d'images satellites nocturnes confirme que la libéralisation du commerce international dynamise d'avantage l'activité économique des régions frontières que celle des régions intérieures. Puisque les régions frontières sont en généralement moins développées économiquement, nous en concluons que la libéralisation des échanges commerciaux contribue à la réduction des disparités régionales. |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:spo:wpmain:info:hdl:2441/qbqni4d3o824qe33b2ckl202c&r=big |
| By: | YAMASHITA Kazuhito |
| Abstract: | Certain advanced technology such as biotechnology have not made any great or significant contributions to the advancement of agriculture. Researchers have only explored the feasibility of technology and have yet to consider the aspects of economics or management. This applies to a portion of the agricultural industry such as fruits and vegetables but does not pertain to grain production which is a vital and indispensable food source for humans. Furthermore, technology has made partial improvements to agricultural production but has not provided fundamental solutions for Japanese agriculture in general. There are concerns that the same kinds of mistakes made in the past technological developments may be repeated in the current application of information technology (IT) and artificial intelligence (AI) technology to agriculture. IT and AI technology, which gathers, analyzes, or assimilates information, could potentially improve the agricultural system as a whole while biotechnology has only addressed the production side. In particular, if we could create open access big data along with an appropriate agricultural policy reform, Japanese agriculture would be drastically enhanced by IT and AI technology. The open access big data will enable IT and AI technology to make great contributions to the national food security. In order to create open access big data, we have to overcome numerous problems including how to collect interoperable data among different stakeholders and how to support farmers and industry participants who are not necessarily well versed in those technologies. In these aspects, this paper tries to make specific policy proposals to overcome such difficulties. |
| Date: | 2017–06 |
| URL: | http://d.repec.org/n?u=RePEc:eti:rpdpjp:17017&r=big |