scholarly journals Analysis of Environmental Governance Expense Prediction Reform With the Background of Artificial Intelligence

2022 ◽  
Vol 34 (5) ◽  
pp. 1-19
Author(s):  
Xiaohui Wu
Keyword(s):  
Artificial Intelligence ◽  
Environmental Management ◽  
Environmental Governance ◽  
Shared Governance ◽  
Cost Prediction ◽  
Rule Based ◽  
The Public ◽  
General Government ◽  
Equilibrium Approach ◽  
The Cost

In this paper, Artificial Intelligence assisted rule-based confidence metric (AI-CRBM) framework has been introduced for analyzing environmental governance expense prediction reform. A metric method is to assess a level of collective environmental governance representing general, government, and corporate aspects. The equilibrium approach is used to calculate improvements in the source of environmental management based on cost, and it is tailored to test the public sector-corporation for environmental shared governance. The overall concept of cost prediction or estimation of environmental governance is achieved by the rule-based confidence method. The framework compares the expected cost to the environment of governance to determine the efficiency of the cost prediction process.

scholarly journals Using Artificial Intelligence to classify Jobseekers: The Accuracy-Equity Trade-off

2020 ◽  
pp. 1-19
Author(s):  
SAM DESIERE ◽  
LUDO STRUYVEN
Keyword(s):  
Artificial Intelligence ◽  
Maximum Level ◽  
Employment Services ◽  
Trade Off ◽  
The Public ◽  
Foreign Origin ◽  
Trade Offs ◽  
Graphical Tool ◽  
The Cost

Abstract Artificial intelligence (AI) is increasingly popular in the public sector to improve the cost-efficiency of service delivery. One example is AI-based profiling models in public employment services (PES), which predict a jobseeker’s probability of finding work and are used to segment jobseekers in groups. Profiling models hold the potential to improve identification of jobseekers at-risk of becoming long-term unemployed, but also induce discrimination. Using a recently developed AI-based profiling model of the Flemish PES, we assess to what extent AI-based profiling ‘discriminates’ against jobseekers of foreign origin compared to traditional rule-based profiling approaches. At a maximum level of accuracy, jobseekers of foreign origin who ultimately find a job are 2.6 times more likely to be misclassified as ‘high-risk’ jobseekers. We argue that it is critical that policymakers and caseworkers understand the inherent trade-offs of profiling models, and consider the limitations when integrating these models in daily operations. We develop a graphical tool to visualize the accuracy-equity trade-off in order to facilitate policy discussions.

scholarly journals Environmental Governance Cost Prediction of Transportation Industry by Considering the Technological Constraints

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1352
Author(s):  
Suhui Wang ◽  
Fei-Fei Ye
Keyword(s):  
Prediction Model ◽  
Technological Innovation ◽  
Environmental Governance ◽  
Transportation Industry ◽  
Input Output ◽  
Investment Planning ◽  
Cost Prediction ◽  
The Cost ◽  
Technological Constraints ◽  
Governance Costs

In order to solve the problem of environmental governance investment planning in the transportation industry, a cost prediction model is proposed under technological constraints, where the input output indictors emphasizes the flexibility of prediction and its characters are asymmetric, while the constructs of prediction model focuses on the standardization and its characters are symmetrical. The basic principle of the cost prediction model is based on an extended belief rule-based (EBRB) system to model the input-output relationship in investment planning, and a parameter learning model to improve the accuracy of the EBRB system. Additionally, the technological innovation factors are also embedded in the cost prediction model to investigate the influence of technology-related outcomes on investment planning. Finally, based on the data of environmental governance in China’s transportation industry from 2003 to 2016, the cost of transportation industry environmental management in China’s thirty provinces from 2017 to 2033 is predicted under the constraints of technological innovation. Results show that: (1) the accuracy of the proposed cost prediction model is higher than some existing cost prediction methods; (2) the predicted environmental governance costs have a significant regional difference; (3) the upgrading of technological innovation is conducive to saving the future environmental governance costs of the transportation industry in some provinces. In addition to the above results, the present study provides model supports and policy references for government decision makers in transportation industry-related environmental cost planning.

A comparison of the cost of research in South Africa's public research and higher education institutions

2008 ◽  
Vol 104 (11/12) ◽  
Author(s):  
D.R. Walwyn
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Public Research ◽  
Pricing Policy ◽  
The Public ◽  
Annual Salary ◽  
Research Sector ◽  
Salary Survey ◽  
The Cost ◽  
Comparative Information

Despite the importance of labour and overhead costs to both funders and performers of research in South Africa, there is little published information on the remuneration structures for researchers, technician and research support staff. Moreover, there are widely different pricing practices and perceptions within the public research and higher education institutions, which in some cases do not reflect the underlying costs to the institution or the inherent value of the research. In this article, data from the 2004/5 Research and Development Survey have been used to generate comparative information on the cost of research in various performance sectors. It is shown that this cost is lowest in the higher education institutions, and highest in the business sector, although the differences in direct labour and overheads are not as large as may have been expected. The calculated cost of research is then compared with the gazetted rates for engineers, scientists and auditors performing work on behalf of the public sector, which in all cases are higher than the research sector. This analysis emphasizes the need within the public research and higher education institutions for the development of a common pricing policy and for an annual salary survey, in order to dispel some of the myths around the relative costs of research, the relative levels of overhead ratios and the apparent disparity in remuneration levels.

The Internet Trap

2018 ◽  
Author(s):  
Matthew Hindman
Keyword(s):  
The Internet ◽  
Net Neutrality ◽  
The Public ◽  
Attention Economy ◽  
Digital News ◽  
The Cost ◽  
Over Time

The Internet was supposed to fragment audiences and make media monopolies impossible. Instead, behemoths like Google and Facebook now dominate the time we spend online—and grab all the profits from the attention economy. This book explains how this happened. It sheds light on the stunning rise of the digital giants and the online struggles of nearly everyone else—and reveals what small players can do to survive in a game that is rigged against them. The book shows how seemingly tiny advantages in attracting users can snowball over time. The Internet has not reduced the cost of reaching audiences—it has merely shifted who pays and how. Challenging some of the most enduring myths of digital life, the book explains why the Internet is not the postindustrial technology that has been sold to the public, how it has become mathematically impossible for grad students in a garage to beat Google, and why net neutrality alone is no guarantee of an open Internet. It also explains why the challenges for local digital news outlets and other small players are worse than they appear and demonstrates what it really takes to grow a digital audience and stay alive in today's online economy. The book shows why, even on the Internet, there is still no such thing as a free audience.

Strategy for Protecting the North Sea: A Chemical Industry Perspective

1991 ◽  
Vol 24 (10) ◽  
pp. 269-276
Author(s):  
J. R. Lawrence ◽  
N. C. D. Craig
Keyword(s):  
North Sea ◽  
Chemical Industry ◽  
Important Research ◽  
The Public ◽  
The North ◽  
Anthropogenic Inputs ◽  
Seven Principles ◽  
The North Sea ◽  
The Cost

The public has ever-rising expectations for the environmental quality of the North Sea and hence of everreducing anthropogenic inputs; by implication society must be willing to accept the cost of reduced contamination. The chemical industry accepts that it has an important part to play in meeting these expectations, but it is essential that proper scientific consideration is given to the potential transfer of contamination from one medium to another before changes are made. A strategy for North Sea protection is put forward as a set of seven principles that must govern the management decisions that are made. Some areas of uncertainty are identified as important research targets. It is concluded that although there have been many improvements over the last two decades, there is more to be done. A systematic and less emotive approach is required to continue the improvement process.

Towards a Customized¬ Awareness Campaign to Educate the Public about COVID-19: Development and Validation of a Messaging Campaign to Promote Precautionary Behavior Using Geospatial Intelligence in Saudi Arabia (Preprint)

2020 ◽  
Author(s):  
Mayda Alrige ◽  
Hind Bitar Bitar ◽  
Maram Meccawi ◽  
Balakrishnan Mullachery
Keyword(s):  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Content Validity ◽  
Awareness Campaign ◽  
Artificial Intelligence Technique ◽  
The Public ◽  
High Infection ◽  
Local Map ◽  
The City ◽  
Intelligence Technique

BACKGROUND Designing a health promotion campaign is never an easy task, especially during a pandemic of a highly infectious disease, such as Covid-19. In Saudi Arabia, many attempts have been made toward raising the public awareness about Covid-19 infection-level and its precautionary health measures that have to be taken. Although this is useful, most of the health information delivered through the national dashboard and the awareness campaign are very generic and not necessarily make the impact we like to see on individuals’ behavior. OBJECTIVE The objective of this study is to build and validate a customized awareness campaign to promote precautionary health behavior during the COVID-19 pandemic. The customization is realized by utilizing a geospatial artificial intelligence technique called Space-Time Cube (STC) technique. METHODS This research has been conducted in two sequential phases. In the first phase, an initial library of thirty-two messages was developed and validated to promote precautionary messages during the COVID-19 pandemic. This phase was guided by the Fogg Behavior Model (FBM) for behavior change. In phase 2, we applied STC as a Geospatial Artificial Intelligence technique to create a local map for one city representing three different profiles for the city districts. The model was built using COVID-19 clinical data. RESULTS Thirty-two messages were developed based on resources from the World Health Organization and the Ministry of Health in Saudi Arabia. The enumerated content validity of the messages was established through the utilization of Content Validity Index (CVI). Thirty-two messages were found to have acceptable content validity (I-CVI=.87). The geospatial intelligence technique that we used showed three profiles for the districts of Jeddah city: one for high infection, another for moderate infection, and the third for low infection. Combining the results from the first and second phases, a customized awareness campaign was created. This awareness campaign would be used to educate the public regarding the precautionary health behaviors that should be taken, and hence help in reducing the number of positive cases in the city of Jeddah. CONCLUSIONS This research delineates the two main phases to developing a health awareness messaging campaign. The messaging campaign, grounded in FBM, was customized by utilizing Geospatial Artificial Intelligence to create a local map with three district profiles: high-infection, moderate-infection, and low-infection. Locals of each district will be targeted by the campaign based on the level of infection in their district as well as other shared characteristics. Customizing health messages is very prominent in health communication research. This research provides a legitimate approach to customize health messages during the pandemic of COVID-19.

Living machines in our cultural imagination

2018 ◽  
Author(s):  
Michael Szollosy
Keyword(s):  
Artificial Intelligence ◽  
Science Fiction ◽  
Public Perceptions ◽  
Human Condition ◽  
Cultural Imagination ◽  
The Public ◽  
The Enlightenment ◽  
The Future ◽  
Public Imagination ◽  
The Human Condition

Public perceptions of robots and artificial intelligence (AI)—both positive and negative—are hopelessly misinformed, based far too much on science fiction rather than science fact. However, these fictions can be instructive, and reveal to us important anxieties that exist in the public imagination, both towards robots and AI and about the human condition more generally. These anxieties are based on little-understood processes (such as anthropomorphization and projection), but cannot be dismissed merely as inaccuracies in need of correction. Our demonization of robots and AI illustrate two-hundred-year-old fears about the consequences of the Enlightenment and industrialization. Idealistic hopes projected onto robots and AI, in contrast, reveal other anxieties, about our mortality—and the transhumanist desire to transcend the limitations of our physical bodies—and about the future of our species. This chapter reviews these issues and considers some of their broader implications for our future lives with living machines.

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