Beyond Tools and Procedures

2022 ◽  
pp. 16-23
Author(s):  
Ivana Bartoletti ◽  
Lucia Lucchini
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Court Cases ◽  
Daily Lives ◽  
Viable Approach ◽  
Almost All ◽  
Automated Decision Making ◽  
Business Framework

As artificial intelligence (AI) is increasingly being deployed in almost all aspects of our daily lives, the discourse around the pervasiveness of algorithmic tools and automated decision-making appears to be almost a trivial one. This chapter investigates limits and opportunities within existing debates and examines the rapidly evolving legal landscape and recent court cases. The authors suggest that a viable approach to fairness, which ultimately remains a choice that organizations have to make, could be rooted in a new measurable and accountable responsible business framework.

Blockchain-Enabled Internet of Things for Unsupervised Structural Health Monitoring in Potential Building Structures

2021 ◽  
pp. 158-170
Author(s):  
Wael Mohammad Alenazy
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Structural Health Monitoring ◽  
Internet Of Things ◽  
Health Monitoring ◽  
Remote Monitoring ◽  
Building Structures ◽  
Stress Strain ◽  
Structural Health ◽  
Automated Decision Making

The integration of internet of things, artificial intelligence, and blockchain enabled the monitoring of structural health with unattended and automated means. Remote monitoring mandates intelligent automated decision-making capability, which is still absent in present solutions. The proposed solution in this chapter contemplates the architecture of smart sensors, customized for individual structures, to regulate the monitoring of structural health through stress, strain, and bolted joints looseness. Long range sensors are deployed for transmitting the messages a longer distance than existing techniques. From the simulated results, different sensors record the monitoring information and transmit to the blockchain platform in terms of pressure points, temperature, pre-tension force, and the architecture deems the criticality of transactions. Blockchain platform will also be responsible for storage and accessibility of information from a decentralized medium, automation, and security.

scholarly journals In AI we trust? Perceptions about automated decision-making by artificial intelligence

AI & Society ◽  
2020 ◽  
Vol 35 (3) ◽  
pp. 611-623 ◽  
Author(s):  
Theo Araujo ◽  
Natali Helberger ◽  
Sanne Kruikemeier ◽  
Claes H. de Vreese
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Automated Decision Making

scholarly journals Exploring Peoples' Perception of Autonomy and Reactance in Everyday AI Interactions

2021 ◽  
Vol 12 ◽  
Author(s):  
Supraja Sankaran ◽  
Chao Zhang ◽  
Henk Aarts ◽  
Panos Markopoulos
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Social Media ◽  
Future Development ◽  
Human Interaction ◽  
Potential Threat ◽  
Daily Lives ◽  
The Social ◽  
Human Autonomy ◽  
Design Fiction

Applications using Artificial Intelligence (AI) have become commonplace and embedded in our daily lives. Much of our communication has transitioned from human–human interaction to human–technology or technology-mediated interaction. As technology is handed over control and streamlines choices and decision-making in different contexts, people are increasingly concerned about a potential threat to their autonomy. In this paper, we explore autonomy perception when interacting with AI-based applications in everyday contexts using a design fiction-based survey with 328 participants. We probed if providing users with explanations on “why” an application made certain choices or decisions influenced their perception of autonomy or reactance regarding the interaction with the applications. We also looked at changes in perception when users are aware of AI's presence in an application. In the social media context, we found that people perceived a greater reactance and lower sense of autonomy perhaps owing to the personal and identity-sensitive nature of the application context. Providing explanations on “why” in the navigation context, contributed to enhancing their autonomy perception, and reducing reactance since it influenced the users' subsequent actions based on the recommendation. We discuss our findings and the implications it has for the future development of everyday AI applications that respect human autonomy.

scholarly journals Thematic Dynamics of Internet of Things (IoT): Impact on Digital Personalized Healthcare (PHC)

2021 ◽  
Author(s):  
Bongs Lainjo
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Mining ◽  
Successful Implementation ◽  
Daily Lives ◽  
Personalized Healthcare ◽  
Iot Platform ◽  
Iot Platforms ◽  
Almost All

Abstract Background: Information technology has continued to shape contemporary thematic trends. Advances in communication have impacted almost all themes ranging from education, engineering, healthcare, and many other aspects of our daily lives. Method: This paper attempts to review the different dynamics of the thematic IoT platforms. A select number of themes are extensively analyzed with emphasis on data mining (DM), personalized healthcare (PHC), and thematic trends of a select number of subjectively identified IoT-related publications over three years. In this paper, the number of IoT-related-publications is used as a proxy representing the number of apps. DM remains the trailblazer, serving as a theme with crosscutting qualities that drive artificial intelligence (AI), machine learning (ML), and data transformation. A case study in PHC illustrates the importance, complexity, productivity optimization, and nuances contributing to a successful IoT platform. Among the initial 99 IoT themes, 18 are extensively analyzed using the number of IoT publications to demonstrate a combination of different thematic dynamics, including subtleties that influence escalating IoT publication themes. Results: Based on findings amongst the 99 themes, the annual median IoT-related publications for all the themes over the four years were increasingly 5510, 8930, 11700, and 14800 for 2016, 2017, 2018, and 2019 respectively; indicating an upbeat prognosis of IoT dynamics. Conclusion: The vulnerabilities that come with the successful implementation of IoT systems are highlighted including the successes currently achieved by institutions promoting the benefits of IoT-related systems like the case study. Security continues to be an issue of significant importance.

Artificial intelligence for production engineering: a historical approach

Robotica ◽  
1987 ◽  
Vol 5 (2) ◽  
pp. 99-110 ◽  
Author(s):  
Igor Aleksander
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Visual Information ◽  
Design Stage ◽  
Production Engineering ◽  
Television Camera ◽  
Knowledge Based ◽  
Work Cycle ◽  
Programming Techniques ◽  
Automated Decision Making

SUMMARYThis paper describes the principles of the advanced programming techniques often dubbed Artificial Intelligence involved in decision making as may be of some value in matters related to production engineering. Automated decision making in the context of production can adopt many aspects. At the most obvious level, a robot may have to plan a sequence of actions on the basis of signals obtained from changing conditions in its environment. These signals may, indeed, be quite complex, for example the input of visual information from a television camera.At another level, automated planning may be required to schedule the entire work cycle of a plant that includes many robots as well as other types of automated machinery. The often-quoted dark factory is an example of this, where not only some of the operations (such as welding) are done by robots, but also the transport of part-completed assemblies is automatically scheduled as a set of actions for autonomic transporters and cranes. It is common practice for this activity to be preprogrammed to the greatest detail. Automated decision making is aimed at adding flexibility to the process so that it can absolve the system designer from having to forsee every eventuality at the design stage.Frequent reference is made in this context to artificial intelligence (AI), knowledge-based and expert systems. Although these topics are more readily associated with computer science, it is the automated factory, in general, and the robot, in particular, that will benefit from success in these fields. In this part of the paper we try to sharpen up this perspective, while in part II we aim to discuss the history of artificial intelligence in this context. In part III we discuss the industrial prospects for the field.

Juvenile Justice and Plea Bargaining

2019 ◽  
pp. 107-131 ◽  
Author(s):  
Allison D. Redlich ◽  
Tina Zottoli ◽  
Tarika Daftary-Kapur
Keyword(s):  
Decision Making ◽  
Plea Bargaining ◽  
Criminal Court ◽  
Future Research ◽  
Court Cases ◽  
Guilty Plea ◽  
Criminal Justice Systems ◽  
Similarities And Differences ◽  
Adult Criminal Court ◽  
Almost All

As with adult criminal court cases, almost all juvenile and criminal court cases involving youth are resolved by guilty plea. This chapter reviews the extant research on youth defendants and guilty pleas. The focus is on three areas: (1) the circumstances surrounding guilty plea decisions (e.g., access to attorneys, time to make decisions); (2) youths’ knowledge about guilty plea decisions and whether they are made voluntarily; and (3) the rationales underlying guilty plea decisions. Additionally, across these three areas the chapter addresses plea decision-making by guilty and innocent juvenile defendants, highlighting the similarities and differences. The chapter concludes with a call for future research and implications for juveniles involved in the juvenile or adult criminal justice systems.

scholarly journals Integration of Artificial Intelligence into Dempster Shafer Theory: A Review on Decision Making in Condition Monitoring

2015 ◽  
Vol 773-774 ◽  
pp. 154-157 ◽  
Author(s):  
Muhammad Firdaus Rosli ◽  
Lim Meng Hee ◽  
M. Salman Leong
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Condition Monitoring ◽  
Support Vector ◽  
Dempster Shafer Theory ◽  
Basic Probability ◽  
Human Interpretation ◽  
The Individual ◽  
Shafer Theory ◽  
Automated Decision Making

Machines are the heart of most industries. By ensuring the health of machines, one could easily increase the company revenue and eliminates any safety threat related to machinery catastrophic failures. In condition monitoring (CM), questions often arise during decision making time whether the machine is still safe to run or not? Traditional CM approach depends heavily on human interpretation of results whereby decision is made solely based on the individual experience and knowledge about the machines. The advent of artificial intelligence (AI) and automated ways for decision making in CM provides a more objective and unbiased approach for CM industry and has become a topic of interest in the recent years. This paper reviews the techniques used for automated decision making in CM with emphasis given on Dempster-Shafer (D-S) evident theory and other basic probability assignment (BPA) techniques such as support vector machine (SVM) and etc.

scholarly journals Sustainability challenges of Artificial Intelligence and Policy Implications

2021 ◽  
Vol 36 (O1) ◽  
pp. 36-40
Author(s):  
Friederike Rohde ◽  
Maike Gossen ◽  
Josephin Wagner ◽  
Tilman Santarius
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Sustainable Development ◽  
Sustainable Development Goals ◽  
Policy Implications ◽  
Development Goals ◽  
Sustainability Challenges ◽  
Automated Decision Making

Automated decision-making based on Artificial Intelligence is associated with growing expectations and is to contribute to sustainable development goals. Which opportunities and risks for the environment, economy and society are associated with Artificial Intelligence-based applications and how can they be governed?

scholarly journals From Poisons to Antidotes: Algorithms as Democracy Boosters

2022 ◽  
pp. 1-25
Author(s):  
Paolo Cavaliere ◽  
Graziella Romeo
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Political Institutions ◽  
Theoretical Framework ◽  
Traditional Authority ◽  
Political Processes ◽  
Viable Solution ◽  
Decision Making Processes ◽  
Automated Decision Making ◽  
Public Decision

Abstract Under what conditions can artificial intelligence contribute to political processes without undermining their legitimacy? Thanks to the ever-growing availability of data and the increasing power of decision-making algorithms, the future of political institutions is unlikely to be anything similar to what we have known throughout the last century, possibly with parliaments deprived of their traditional authority and public decision-making processes largely unaccountable. This paper discusses and challenges these concerns by suggesting a theoretical framework under which algorithmic decision-making is compatible with democracy and, most relevantly, can offer a viable solution to counter the rise of populist rhetoric in the governance arena. Such a framework is based on three pillars: (1) understanding the civic issues that are subjected to automated decision-making; (2) controlling the issues that are assigned to AI; and (3) evaluating and challenging the outputs of algorithmic decision-making.

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