scholarly journals The digital transition of social security in Finland. Frontrunner experiencing headwinds?

2021 ◽  
Vol 150 (3) ◽  
Author(s):  
Niko Väänänen
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Social Security ◽  
State Of The Art ◽  
Ethical Challenges ◽  
Organizational Challenges ◽  
Current State ◽  
Digital Transition ◽  
Digital Processes

Digitalization transforms our societies in a profound way. Public administrations and social security institutions are at different stages in this process. Digitalization poses technological, legal, and organizational challenges. Finland has typically been a frontrunner in the adaptation of ICT technology. This case study critically assesses the current state-of-the-art in the field of digitalization in Finnish social security. The text singles out the projects that are on-going and those that are planned for the immediate future. The article shows that Finnish social security institutions have integrated digital processes into their operations, but legal and ethical challenges exist, especially in the use of artificial intelligence and automatic decision-making in social security.

Ressourceneffizienz durch Digitalisierung*/Resource efficiency through digitisation. Potentials for SMEs in the manufacturing industry

2018 ◽  
Vol 108 (05) ◽  
pp. 319-324
Author(s):  
I. Bogdanov ◽  
A. Nuffer ◽  
A. Sauer
Keyword(s):  
Manufacturing Industry ◽  
State Of The Art ◽  
Manufacturing Sector ◽  
Resource Efficiency ◽  
Digitale Transformation ◽  
Case Study Analysis ◽  
Current State ◽  
Stand Der Technik ◽  
A Current

Der vorliegende Beitrag behandelt den Themenkomplex Ressourcen-effizienz und digitale Transformation im verarbeitenden Gewerbe sowie die dabei entstehenden Wechselwirkungen. Neben dem aktuellen Stand der Technik werden die im Rahmen einer aktuellen Studie durchgeführte Fallbeispielanalyse und die entwickelte Methodik zur Ermittlung der Ressourceneffizienzpotenziale vorgestellt. Diese Potenziale und die eingesetzten digitalen Maßnahmen sind zentrale Bausteine des vorliegenden Beitrags.   This article deals with the topic complex of resource efficiency and digital transformation in the manufacturing sector as well as the resulting interactions. In addition to the current state of the art and perspectives, the case study analysis carried out as part of a current study, as well as the developed method for establishing the resource efficiency potentials will be presented. The resultant potential and the digital measures are central components of this article.

scholarly journals Decision-Making Framework For Small Business With Limited Available Capital

2021 ◽  
Author(s):  
Milad Around
Keyword(s):  
Decision Making ◽  
Small Business ◽  
Small Businesses ◽  
General Level ◽  
Working Capital ◽  
Financial Assessment ◽  
Current State ◽  
Business Entities ◽  
A Current

In the world of business special attention is paid to entrepreneurs for their potential and large corporations for their impact on the market. Due to this, small businesses often fall short of resources and tools to help them grow. The aim of this dissertation is to introduce a framework for decision making to small businesses as a tool to help embed more structure into their organization. The framework was then applied to two distinct case studies to display its functionality and usefulness. The framework consists of several steps: 1) corporate plan and financial assessment 2) a current state analysis 3) a quantitative and mathematical feasibility study of the decision The framework in each case study resulted in an objective and qualified decision. It also suggests that, due to the unique structure and characteristics of each small business, the framework proposed would only be relevant and applicable on a general level and more work is required to refine the details in order to be able apply it universally to business entities with limited working capital.

scholarly journals A RESTful middleware for AI controlled sensors, actuators and smart devices

2019 ◽  
Vol 11 (7) ◽  
pp. 2963-2986 ◽  
Author(s):  
Nikos Dipsis ◽  
Kostas Stathis
Keyword(s):  
Smart Home ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Smart Devices ◽  
Machine Learning Algorithm ◽  
Concrete Case ◽  
Domain Specific ◽  
Sensor Actuator ◽  
Current State

Abstract The numerous applications of internet of things (IoT) and sensor networks combined with specialized devices used in each has led to a proliferation of domain specific middleware, which in turn creates interoperability issues between the corresponding architectures and the technologies used. But what if we wanted to use a machine learning algorithm to an IoT application so that it adapts intelligently to changes of the environment, or enable a software agent to enrich with artificial intelligence (AI) a smart home consisting of multiple and possibly incompatible technologies? In this work we answer these questions by studying a framework that explores how to simplify the incorporation of AI capabilities to existing sensor-actuator networks or IoT infrastructures making the services offered in such settings smarter. Towards this goal we present eVATAR+, a middleware that implements the interactions within the context of such integrations systematically and transparently from the developers’ perspective. It also provides a simple and easy to use interface for developers to use. eVATAR+ uses JAVA server technologies enhanced by mediator functionality providing interoperability, maintainability and heterogeneity support. We exemplify eVATAR+ with a concrete case study and we evaluate the relative merits of our approach by comparing our work with the current state of the art.

Algorithmic decision-making? The user interface and its role for human involvement in decisions supported by artificial intelligence

Organization ◽  
2019 ◽  
Vol 26 (5) ◽  
pp. 655-672 ◽  
Author(s):  
Verena Bader ◽  
Stephan Kaiser
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
User Interface ◽  
User Involvement ◽  
Traditional View ◽  
Telecommunications Company

Artificial intelligence can provide organizations with prescriptive options for decision-making. Based on the notions of algorithmic decision-making and user involvement, we assess the role of artificial intelligence in workplace decisions. Using a case study on the implementation and use of cognitive software in a telecommunications company, we address how actors can become distanced from or remain involved in decision-making. Our results show that humans are increasingly detached from decision-making spatially as well as temporally and in terms of rational distancing and cognitive displacement. At the same time, they remain attached to decision-making because of accidental and infrastructural proximity, imposed engagement, and affective adhesion. When human and algorithmic intelligence become unbalanced in regard to humans’ attachment to decision-making, three performative effects result: deferred decisions, workarounds, and (data) manipulations. We conceptualize the user interface that presents decisions to humans as a mediator between human detachment and attachment and, thus, between algorithmic and humans’ decisions. These findings contrast the traditional view of automated media as diminishing user involvement and have useful implications for research on artificial intelligence and algorithmic decision-making in organizations.

Future Directions in Cognitive Engineering and Naturalistic Decision Making

1995 ◽  
Vol 39 (9) ◽  
pp. 450-453 ◽  
Author(s):  
Mica R. Endsley ◽  
Gary Klein ◽  
David D. Woods ◽  
Philip J. Smith ◽  
Stephen J. Selcon
Keyword(s):  
Decision Making ◽  
State Of The Art ◽  
Cognitive Engineering ◽  
Training Process ◽  
Naturalistic Decision Making ◽  
Future Directions ◽  
Current State ◽  
Near Future ◽  
And Training ◽  
Research Domain

Cognitive Engineering and Naturalistic Decision Making are presented as two related fields of endeavor that seek to understand how people process information and perform within complex systems and to develop ways of applying this knowledge within the design and training process This panel presents an overview of the current state of the art in this research domain and charts paths for needed developments in the field in the near future.

Making the Case for Practice-Based Research and the Imperative Role of Design Practitioners

2016 ◽  
Vol 10 (3) ◽  
pp. 66-82 ◽  
Author(s):  
Kara Freihoefer ◽  
Terri Zborowsky
Keyword(s):  
Decision Making ◽  
Design Practice ◽  
Design Work ◽  
Body Of Knowledge ◽  
Current State ◽  
Practice Based Research ◽  
Architecture And Design ◽  
Validation Tool

The purpose of this article is to justify the need for evidence-based design (EBD) in a research-based architecture and design practice. This article examines the current state of practice-based research (PBR), supports the need for EBD, illustrates PBR methods that can be applied to design work, and explores how findings can be used as a decision-making tool during design and as a validation tool during postoccupancy. As a result, design professions’ body of knowledge will advance and practitioners will be better informed to protect the health, safety, and welfare of the society. Furthermore, characteristics of Friedman’s progressive research program are used as a framework to examine the current state of PBR in design practice. A modified EBD approach is proposed and showcased with a case study of a renovated inpatient unit. The modified approach demonstrates how a highly integrated project team, especially the role of design practitioners, contributed to the success of utilizing baseline findings and evidence in decision-making throughout the design process. Lastly, recommendations and resources for learning research concepts are provided for practitioners. It is the role of practitioners to pave the way for the next generation of design professionals, as the request and expectation for research become more prevalent in design practice.

scholarly journals Methodology for integrating artificial intelligence in healthcare systems: learning from COVID-19 to prepare for Disease X

AI and Ethics ◽  
2021 ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Carsten Maple ◽  
Uchenna Ani
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Qualitative Case Study ◽  
Healthcare Systems ◽  
Lessons Learned ◽  
Case Study Method ◽  
Research Problems ◽  
Systems Learning ◽  
Digital Healthcare

AbstractArtificial intelligence and edge devices have been used at an increased rate in managing the COVID-19 pandemic. In this article we review the lessons learned from COVID-19 to postulate possible solutions for a Disease X event. The overall purpose of the study and the research problems investigated is the integration of artificial intelligence function in digital healthcare systems. The basic design of the study includes a systematic state-of-the-art review, followed by an evaluation of different approaches to managing global pandemics. The study design then engages with constructing a new methodology for integrating algorithms in healthcare systems, followed by analysis of the new methodology and a discussion. Action research is applied to review existing state of the art, and a qualitative case study method is used to analyse the knowledge acquired from the COVID-19 pandemic. Major trends found as a result of the study derive from the synthesis of COVID-19 knowledge, presenting new insights in the form of a conceptual methodology—that includes six phases for managing a future Disease X event, resulting with a summary map of various problems, solutions and expected results from integrating functional AI in healthcare systems.

scholarly journals ASSESSING ETHICAL AI-BASED DECISION-MAKING: TOWARDS AN APPLIED ANALYTICAL FRAMEWORK

2019 ◽  
Vol 2019 ◽  
Author(s):  
Paul Henman
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Analytical Framework ◽  
Government Accountability ◽  
Ethical Challenges ◽  
Government Decision ◽  
Policy Work ◽  
Key Questions

Globally there is strong enthusiasm for using Artificial Intelligence (AI) in government decision making, yet this technocratic approach is not without significant downsides including bias, exacerbating discrimination and inequalities, and reducing government accountability and transparency. A flurry of analytical and policy work has recently sought to identify principles, policies, regulations and institutions for enacting ethical AI. Yet, what is lacking is a practical framework and means by which AI can be assessed as un/ethical. This paper provides an overview of an applied analytical framework for assessing the ethics of AI. It notes that AI (or algorithmic) decision-making is an outcome of data, code, context and use. Using these four categories, the paper articulates key questions necessary to determine the potential ethical challenges of using an AI/algorithm in decision making, and provides the basis for their articulation within a practical toolkit that can be demonstrated against known AI decision-making tools.

scholarly journals Precision Agriculture Technology: A Literature Review

2020 ◽  
pp. 30-34
Author(s):  
C. A. Danbaki ◽  
N. C. Onyemachi ◽  
D. S. M. Gado ◽  
G. S. Mohammed ◽  
D. Agbenu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Image Processing ◽  
Precision Agriculture ◽  
State Of The Art ◽  
Irrigation Management ◽  
Conventional Farming ◽  
Livestock Farming ◽  
Current State ◽  
Art Methods ◽  
Increase In Productivity

This study is a survey on state-of-the-art methods based on artificial intelligence and image processing for precision agriculture on Crop Management, Pest and Disease Management, Soil and Irrigation Management, Livestock Farming and the challenges it presents. Precision agriculture (PA) described as applying current technologies into conventional farming methods. These methods have proved to be highly efficient, sustainable and profitable to the farmer hence boosting the economy. This study is a survey on the current state of the art methods applied to precision agriculture. The application of precision agriculture is expected to yield an increase in productivity which ultimately ends in profit to the farmer, to the society increase sustainability and also improve the economy.

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