scholarly journals DATA AND ARTIFICIAL INTELLIGENCE FOR BETTER AND INTELLIGENT REGULATION

2021 ◽  
Vol 14 (1) ◽  
pp. 7-25
Author(s):  
Manuel Cabugueira
Keyword(s):  
Artificial Intelligence ◽  
Policy Making ◽  
New Technologies ◽  
Evidence Base ◽  
Data Driven ◽  
Evidence Based ◽  
Public Intervention ◽  
Economic Competitiveness ◽  
Better Regulation ◽  
Evidence Base Approach

In this article we bring forward a reflection on how data technology and artificial intelligence can improve the implementation of an evidence-based, data-driven, regulation. We start by arguing in favor of an evidence-base approach to regulation, meaning that policy making should be supported by information on the expected and observed impacts. We reach this position by acknowledging that, on one side, markets fail and public intervention will promote social welfare and economic competitiveness but, on the other, regulation also fails creating implementation and compliance costs. It follows that public intervention has to be supported by a demonstration that benefits will outweigh the costs. In this paper we discuss the challenges presented by this evidence-base regulation and how the new tools from data technologies and artificial intelligence may provide new resources to face those difficulties. We conclude that there is an obvious match between the solutions that these new technologies present and the requirements to “better regulate” and to “regulate better”. In the end, it seems only natural that evidence-base regulation should also be data-driven. Keywords: Regulation; Artificial Intelligence; Better Regulation; evidence-based regulation, data-driven regulation

scholarly journals Here Comes the Hyper-Connected Augmented Consumer

2017 ◽  
Vol 9 (2) ◽  
pp. 10-17 ◽  
Author(s):  
Andrew T. Stephen
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Search Costs ◽  
Data Driven ◽  
Smart Sensors ◽  
Market Intelligence ◽  
Consumer Data ◽  
New Type ◽  
To Come ◽  
Iot Devices

Abstract Consumers have become always on and constantly connected. Search costs have plummeted, individuals’ abilities to digitally express themselves and their opinions increased, and the opportunities for superior business and market intelligence for companies have skyrocketed. This has given rise to more, richer, and new sources of consumer data that marketers can leverage, and has fueled the data-driven insights revolution in marketing. But there is more to come very soon. In marketing, we are quickly moving from the age of the connected consumer to the age of the augmented consumer. New technologies like wearable devices, smart sensors, consumer IoT devices, smart homes, and, critically, artificial intelligence ecosystems will not only connect, but will substantially and meaningfully augment the consumer in terms of their thoughts and behaviors. The biggest challenge for marketers will lie in how they approach marketing to this new type of consumer, particularly personal artificial intelligence ecosystems. This means marketing to algorithms, instead of people, and that is very different to how most marketing work is currently done.

scholarly journals Can citizen science complement official data sources that serve as evidence-base for policies and practice to improve water quality?

2020 ◽  
pp. 1-16
Author(s):  
Ariane König ◽  
Karl Pickar ◽  
Jacek Stankiewicz ◽  
Kristina Hondrila
Keyword(s):  
Water Quality ◽  
Production Process ◽  
Citizen Science ◽  
Policy Making ◽  
Evidence Base ◽  
Project Work ◽  
Evidence Based ◽  
Evidence Based Policy ◽  
Data Production ◽  
Official Data

Addressing environmental issues in policy making requires recognising these issues as part of a complex socio-ecological system. The evidence base for such policies and associated monitoring and implementation measures, as well as related official indicators, statistics and environmental accounts are receiving increasing attention. This paper explores the potential of citizen science as a non-traditional source of data to complement the current data production process for evidence-based policy-making, using pollution of surface waters and its effect on associated ecosystems as an example. The paper develops a framework that helps to explore the official data production process in relation to different purposes of environmental policies. This highlights different challenges that the current official data production process sees itself confronted with in relation to the different purposes of the policies and associated monitoring regimes. These questions are explored with reference to the case of evidence-based policy making on water quality of surface freshwater in the EU, with a focus on Luxembourg. The analysis is based on extensive documentary analysis and literature review, as well as a series of interviews and participatory workshops with various stakeholders, and first results of a pilot project work with engaged citizen volunteers to solicit data on water quality with a focus on its nutrient content. On this basis, this paper argues that citizen science has the clear potential to meaningfully contribute both to the evidence base for policy and practice, as well as to an improved governance process.

scholarly journals Anthropology and the AI-Turn in Global Governance

AJIL Unbound ◽  
2021 ◽  
Vol 115 ◽  
pp. 294-298
Author(s):  
Maria Sapignoli
Keyword(s):  
Artificial Intelligence ◽  
International Law ◽  
European Commission ◽  
Global Governance ◽  
Policy Making ◽  
New Technologies ◽  
New Technology ◽  
Regional Institutions ◽  
Anthropological Theory ◽  
Artificial Intelligence Systems

Under the banner “AI (artificial intelligence) for good,” new technologies are becoming more and more central to the agendas of global and regional institutions, as technologies to be embraced and regulated at the same time. This is indicated by the 2018 UN Secretary General's Strategy on New Technology, and by the most recent European Commission proposal to regulate artificial intelligence systems. In this essay, I discuss how anthropology and its ethnographic method could contribute to our understanding of the AI-turn in global governance, by shedding greater light on the effects that the use of this technology has for society, the work of institutions, and the production and application of international law. I argue that engaging ethnographically with AI techniques and knowledge could also bring about a transformation in governance, policy-making, and anthropological theory.

scholarly journals Modern Business Intelligence: Big Data Analytics and Artificial Intelligence for Creating the Data-Driven Value

2021 ◽  
Author(s):  
Ahmed A.A. Gad-Elrab
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Business Intelligence ◽  
Data Analytics ◽  
New Technologies ◽  
Big Data Analytics ◽  
Data Driven ◽  
A Value ◽  
Challenges And Opportunities ◽  
Modern Business

Currently, business intelligence (BI) systems are used extensively in many business areas that are based on making decisions to create a value. BI is the process on available data to extract, analyze and predict business-critical insights. Traditional BI focuses on collecting, extracting, and organizing data for enabling efficient and professional query processing to get insights from historical data. Due to the existing of big data, Internet of Things (IoT), artificial intelligence (AI), and cloud computing (CC), BI became more critical and important process and received more great interest in both industry and academia fields. The main problem is how to use these new technologies for creating data-driven value for modern BI. In this chapter, to meet this problem, the importance of big data analytics, data mining, AI for building and enhancing modern BI will be introduced and discussed. In addition, challenges and opportunities for creating value of data by establishing modern BI processes.

scholarly journals Everything You Always Wanted to Know About AI - Nowcasting Digital Skills With Wikipedia

2019 ◽  
Author(s):  
Fabian Stephany
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Data Driven ◽  
Online Data ◽  
Digital Skills ◽  
Online Encyclopedia ◽  
Initial Research

With the use of online data from the tech job platform dice.com and the online encyclopedia Wikipedia, two networks of digital skills are created around the topic of Artificial Intelligence. Initial research indicates that new skill tags first join the Wikipedia network, before they appear in AI-related job announcements on dice.com. The findings of this work could be used in order to create a data-driven strategy for the acquisition and the development of adequate skills needed to implement and leverage new technologies at best.

scholarly journals CHALLENGES IN DATA-DRIVEN POLICYMAKING: USING SMART CITY DATA TO SUPPORT LOCAL RETAIL POLICIES

2020 ◽  
Vol VI-4/W2-2020 ◽  
pp. 55-61
Author(s):  
R. D’Hauwers ◽  
K. Borghys ◽  
J. T. A. Vannieuwenhuyze ◽  
N. Walravens ◽  
B. Lievens
Keyword(s):  
Policy Making ◽  
Smart Cities ◽  
Evaluation Research ◽  
Data Driven ◽  
Evidence Based ◽  
Retail Sector ◽  
Current State ◽  
Development Processes ◽  
Set Up ◽  
The Cost

Abstract. In Flanders (Belgium), there is a growing awareness among city administrations and governments to turn their cities into smart cities by transforming their policy decisions into evidence-based and data-driven policymaking. Nonetheless, many Flemish cities still face several challenges related to the integration of data-driven policy evaluation research at different stages of their policy making processes. For that reason, the ‘Smart Retail Dashboard’-project was set up, which aims to develop a dashboard for helping Flemish cities in transforming their retail policies into data-driven policies. This paper reports on the initial findings of this project. The most important finding is the varying degrees of maturity across cities regarding their smart retail policies. This is illustrated by the current state of data-driven policy making in the retail sector in Flanders. Subsequently we provide an overview of the current challenges reported by mature and less mature cities, which range from the cost and the usability of data to the analysis and interpretation of such data. We discuss how a Smart Retail Dashboard could provide answers to these challenges. This discussion helps city administrations to transform their policymaking processes into data-driven processes and dashboard developers to optimise their development processes.

Artificial Intelligence as a Technological Innovation to Accelerate Economic Development

2019 ◽  
Vol 12 (3) ◽  
pp. 125-133
Author(s):  
S. V. Shchurina ◽  
A. S. Danilov
Keyword(s):  
Artificial Intelligence ◽  
Economic Development ◽  
Technological Innovation ◽  
Manufacturing Industry ◽  
New Technologies ◽  
Retail Trade ◽  
High Tech ◽  
Industrial Complex ◽  
Technological Gap ◽  
The Government

The subject of the research is the introduction of artificial intelligence as a technological innovation into the Russian economic development. The relevance of the problem is due to the fact that the Russian market of artificial intelligence is still in the infancy and the necessity to bridge the current technological gap between Russia and the leading economies of the world is coming to the forefront. The financial sector, the manufacturing industry and the retail trade are the drivers of the artificial intelligence development. However, company managers in Russia are not prepared for the practical application of expensive artificial intelligence technologies. Under these circumstances, the challenge is to develop measures to support high-tech projects of small and medium-sized businesses, given that the technological innovation considered can accelerate the development of the Russian economy in the energy sector fully or partially controlled by the government as well as in the military-industrial complex and the judicial system.The purposes of the research were to examine the current state of technological innovations in the field of artificial intelligence in the leading countries and Russia and develop proposals for improving the AI application in the Russian practices.The paper concludes that the artificial intelligence is a breakthrough technology with a great application potential. Active promotion of the artificial intelligence in companies significantly increases their efficiency, competitiveness, develops industry markets, stimulates introduction of new technologies, improves product quality and scales up manufacturing. In general, the artificial intelligence gives a new impetus to the development of Russia and facilitates its entry into the five largest world’s economies.

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