scholarly journals From Automation to Autonomy: Legal and Ethical Responsibility Gaps in Artificial Intelligence Innovation

2021 ◽  
pp. 55
Author(s):  
David Nersessian ◽  
Ruben Mancha
Keyword(s):  
Artificial Intelligence ◽  
Value Chain ◽  
Strict Liability ◽  
Original Research ◽  
Process Data ◽  
Ethical Perspective ◽  
Ethical Practices ◽  
Adverse Impacts ◽  
The Moment ◽  
Liability Claims

The increasing prominence of artificial intelligence (AI) systems in daily life and the evolving capacity of these systems to process data and act without human input raise important legal and ethical concerns. This article identifies three primary AI actors in the value chain (innovators, providers, and users) and three primary types of AI (automation, augmentation, and autonomy). It then considers responsibility in AI innovation from two perspectives: (i) strict liability claims arising out of the development, commercialization, and use of products with built-in AI capabilities (designated herein as “AI artifacts”); and (ii) an original research study on the ethical practices of developers and managers creating AI systems and AI artifacts. The ethical perspective is important because, at the moment, the law is poised to fall behind technological reality—if it hasn’t already. Consideration of the liability issues in tandem with ethical perspectives yields a more nuanced assessment of the likely consequences and adverse impacts of AI innovation. Companies should consider both legal and ethical strategies thinking about their own liability and ways to limit it, as well as policymakers considering AI regulation ex ante.

scholarly journals AI MSK clinical applications: spine imaging

2021 ◽  
Author(s):  
Florian A. Huber ◽  
Roman Guggenberger
Keyword(s):  
Artificial Intelligence ◽  
Clinical Application ◽  
Value Chain ◽  
Clinical Applications ◽  
Status Quo ◽  
Use Cases ◽  
Musculoskeletal Imaging ◽  
Future Perspective ◽  
Spine Imaging ◽  
The Status

AbstractRecent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions.

scholarly journals DUTIES AND LIABILITIES IN PRIVATE LAW

Legal Theory ◽  
2006 ◽  
Vol 12 (2) ◽  
pp. 137-156
Author(s):  
Peter Jaffey
Keyword(s):  
Strict Liability ◽  
Corrective Justice ◽  
Private Law ◽  
Liability Claims

Private law is generally formulated in terms of right–duty relations, and accordingly, private-law claims are understood to arise from breaches of duty, or wrongs. Some claims are not easy to explain on this basis because the claim arises from an act that the defendant was justified in doing. The violation/infringement distinction seems to offer an explanation of such claims, but it is argued that the explanation is illusory. Claims of this sort are best understood as based not on a primary right–duty relation at all but on a “primary liability” or “right–liability” relation. A primary-liability claim is not a claim arising from the breach of a strict-liability duty. The recognition of primary-liability claims does not involve skepticism about duties or rules or legal relations and it is consistent with the analysis of private law in terms of corrective justice.

Modular Service-Oriented Cyber-Physical Systems for the European Tool Making Industry

2015 ◽  
Vol 752-753 ◽  
pp. 1349-1355 ◽  
Author(s):  
Günther Schuh ◽  
Stefan Rudolf ◽  
Martin Pitsch ◽  
Martin Sommer ◽  
Wilhelm Karmann
Keyword(s):  
Value Chain ◽  
Physical System ◽  
Industrial Product ◽  
Cyber Physical System ◽  
High Wage ◽  
Process Data ◽  
Operating Life ◽  
Serial Production ◽  
Product Service ◽  
Service Oriented

Manufacturing companies in high-wage countries are facing rising challenges in a global market. Increasing customer demands for a higher degree of individualization result in smaller lot sizes and higher variety of products. In addition, competitors from low-wage countries in Asia and Eastern Europe have significantly improved their technical capabilities, resulting in a more competitive environment. The tool making industry provides its customers with the means to achieve excellence in production due to its unique position in the value chain between product development and the serial production of parts. A tool making company’s ability to improve the efficiency of serial production and develop innovative product design is strongly dependent on its capability of integrating itself into the preceding and following customer processes. Over the last years, customer demands for global sourcing of tools have changed from low prices to the demands of extended tool operating life and high operational availability. European tool making companies have learned to take this development as a chance to differentiate themselves from global competitors and subsequently increase their range of services up- and downstream the value chain. As a result, new industrial product-service-systems (IPS²) for the European tool making industry need to be developed that address the demand of a higher degree of integration into the preceding and following customer processes. Within the German Government founded research project “Smart Tools”, an industrial product-service-system (IPS²) for the tool making industry has been developed based on a modular service-oriented cyber-physical system. Core element of the cyber-physical system is the smart tool – an injection molding tool equipped with state-of-the-art sensor technology to capture data on the condition of the tool during its operational use. Its intelligence derives from the condition based interpretation and data management of the collected process data which is also the basis for the design of customer specific services. Besides the successful integration of force and position sensors into the tool, experimental research has delivered important results on the application of solid borne sound sensors for online early detection of tool wear. An innovative concept for the distribution and interpretation of the process data incorporates the specific requirements of the customers. To cope with the demands of individual and small series production in the tool making industry, a modular sensor kit has been developed together with a diagnostic unit for data interpretation and storage of data in an electronic tool book. The developed modular service-oriented cyber-physical system delivers the means to extended tool operating life and improves the overall efficiency of serial production. Based on the results new business models can be developed for tool making companies to differentiate themselves from global competitors and overcome the challenges of production in high-wage countries.

Beshada v. Johns-Manville Products Corp.: The Function of State of the Art Evidence in Strict Products Liability

1984 ◽  
Vol 10 (1) ◽  
pp. 93-114 ◽  
Author(s):  
Jack Berman
Keyword(s):  
New Jersey ◽  
Supreme Court ◽  
State Of The Art ◽  
Strict Liability ◽  
The State ◽  
Health Hazards ◽  
Products Liability ◽  
The Supreme Court ◽  
Liability Claims

AbstractIn Beshada v. Johns-Manville Products Corp., the Supreme Court of New Jersey held that a state of the art defense is unavailable in cases brought under a theory of strict liability for failure to warn. The court indicated that asbestos producers may be held liable for their products' harms even if the health hazards of asbestos were unknown and not discoverable when the products were marketed. In a subsequent case, the New Jersey court held that state of the art evidence is relevant to whether a product is defective. This Case Comment examines these different uses of knowledge evidence in the disposition of products liability cases. It contends that manufacturers should not be held liable for unknowable risks. The Comment concludes that the state of the art defense establishes a logical limit on strict liability and promotes efficient resolution of products liability claims.

Qualität durch robuste Prozessketten steigern – Potentiale für die Umformtechnik mit Industrie 4.0/Quality improvement through robust process chains – Potentials for metal forming by Industrie 4.0 approaches

2015 ◽  
Vol 105 (10) ◽  
pp. 674-679
Author(s):  
P. Groche ◽  
J. Schreiner ◽  
J. Hohmann ◽  
S. Höhr ◽  
A. Lechler
Keyword(s):  
Value Chain ◽  
Metal Forming ◽  
Deep Understanding ◽  
Industrie 4.0 ◽  
Process Data ◽  
Process Chains ◽  
Recording Analysis ◽  
Robust Process ◽  
And Storage ◽  
Insight Into

Industrie 4.0 gestattet transparente sowie sachgerecht angepasste Wertschöpfungsketten. Dazu ist es nötig, ein tiefgreifendes Prozessverständnis zu besitzen sowie die Aufnahme, Auswertung und Speicherung der relevanten Daten zu bewerkstelligen. Der Beitrag gibt einen Einblick in Industrie 4.0-Ansätze in der Umformtechnik und zeigt ausgewählte Ergebnisse aus dem Verbundprojekt „RobIN 4.0“.   Industrie 4.0 opens the possibility to realize a monitoring and qualified adaption along the entire value chain. Prerequisites for this include a deep understanding of the process as well as achieving the recording, analysis and storage of relevant process data. This paper gives an insight into Industrie 4.0 approaches for the forming industry and presents selected results of the RobIN 4.0-project.

scholarly journals Early Adopters to Early Majority - What's Driving the Artificial Intelligence and Machine Learning Powered Transformation in Financial Services?

2021 ◽  
Vol 12 (4) ◽  
pp. 43
Author(s):  
Srikrishna Chintalapati
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Portfolio Management ◽  
Value Chain ◽  
Financial Services ◽  
Retail Banking ◽  
Early Adopters ◽  
Customer Life Cycle ◽  
Digital Disruption ◽  
The Impact

From retail banking to corporate banking, from property and casualty to personal lines, and from portfolio management to trade processing, the next wave of digital disruption in financial services has been unleashed by the concepts and applications of Artificial Intelligence (AI) and Machine Learning (ML). Together, AI and ML are undoubtedly creating one of the largest technological transformations the world has ever witnessed. Within the advanced streams of research in AI and ML, human intelligence blended with the cognitive reasoning of machines is finally out of the labs and into real-time applications. The Financial Services sector is one of the early adopters of this revolution and arguably much ahead of its leverage compared to other sectors. Built on the conceptual foundations of Innovation diffusion, and a contemporary perspective of enterprise customer life-cycle journey across the AI-value chain defined by McKinsey Global Institute (2017), the current study attempts to highlight the features and use-cases of early-adopters of this transformation. With the theoretical underpinning of technology adoption lifecycle, this paper is an earnest attempt to comment on how AI and ML have been significantly transforming the Financial Services market space from the lens of a domain practitioner. The findings of this study would be of particular relevance to the subject matter experts, Industry analysts, academicians, and researchers focussed on studying the impact of AI and ML in the financial services industry.

scholarly journals Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice

2021 ◽  
Vol 3 (10) ◽  
Author(s):  
Bianca Weber-Lewerenz
Keyword(s):  
Artificial Intelligence ◽  
Business Models ◽  
Research Question ◽  
Transformation Process ◽  
Digital Transformation ◽  
Fundamental Rights ◽  
Ethical Framework ◽  
Ethical Guidelines ◽  
Ethical Perspective ◽  
Construction Engineering

AbstractDigitization is developing fast and has become a powerful tool for digital planning, construction and operations, for instance digital twins. Now is the right time for constructive approaches and to apply ethics-by-design in order to develop and implement a safe and efficient artificial intelligence (AI) application. So far, no study has addressed the key research question: Where can corporate digital responsibility (CDR) be allocated, and how shall an adequate ethical framework be designed to support digital innovations in order to make full use of the potentials of digitization and AI? Therefore, the research on how best practices meet their corporate responsibility in the digital transformation process and the requirements of the EU for trustworthy AI and its human-friendly use is essential. Its transformation bears a high potential for companies, is critical for success and thus, requires responsible handling. This study generates data by conducting case studies and interviewing experts as part of the qualitative method to win profound insights into applied practice. It provides an assessment of demands stated in the Sustainable Development Goals by the United Nations (SDGs), White Papers on AI by international institutions, European Commission and German Government requesting the consideration and protection of values and fundamental rights, the careful demarcation between machine (artificial) and human intelligence and the careful use of such technologies. The study discusses digitization and the impacts of AI in construction engineering from an ethical perspective. This research critically evaluates opportunities and risks concerning CDR in construction industry. To the author’s knowledge, no study has set out to investigate how CDR in construction could be conceptualized, especially in relation to digitization and AI, to mitigate digital transformation both in large, medium- and small-sized companies. This study applies a holistic, interdisciplinary, inclusive approach to provide guidelines for orientation and examine benefits as well as risks of AI. Furthermore, the goal is to define ethical principles which are key for success, resource-cost-time efficiency and sustainability using digital technologies and AI in construction engineering to enhance digital transformation. This study concludes that innovative corporate organizations starting new business models are more likely to succeed than those dominated by a more conservative, traditional attitude.

scholarly journals China’s AI experience: industrial digitalization

2020 ◽  
Vol 28 (3) ◽  
pp. 536-546
Author(s):  
Marina S. Reshetnikova
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Global Economy ◽  
The United States ◽  
High Tech ◽  
Global Innovation ◽  
Innovative Products ◽  
Fundamental Research ◽  
The Moment

The rapid acceleration of scientific and technological progress, which started at the beginning of the 21st century, has become a decisive factor in influencing the global economy. Who will lead the global innovation race? This problem is especially relevant in the field of artificial intelligence (AI). At the moment, the United States and China are the main participants in the battle for dominance in this area. The author assesses Chinas innovative potential in the field of AI and identifies its achievements in this area. Based on the statistics provided, Chinas AI leadership has reached a critical point. China is confidently leading the new fundamental research of artificial intelligence, forming its theoretical base and applied research and development, which will contribute to the creation of new high-tech innovative products and services. However, in terms of the number and quality of AI specialists (AI Talents) and the number of companies engaged in AI, China is still lagging behind its main rival, namely the United States. The author proved that, despite the obvious successes of China, the United States still has an equal lead in the global innovation race.

scholarly journals Detection of Breast Cancer using AI Techniques – A Survey

2019 ◽  
Vol 7 (7) ◽  
pp. 08-12
Author(s):  
Riju Bhattacharya ◽  
Diksha Gupta ◽  
Divyatara Rathod
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Diagnostics ◽  
Detection Methods ◽  
Health Issues ◽  
Process Data ◽  
Mortality And Morbidity ◽  
Medical Progress ◽  
Glass Slides ◽  
Abnormal Cells

Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue.Without treatment, it can cause serious health issues andresult in a loss of life. Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide. Early detection of cancer may reduce mortality and morbidity. This paper presents a review of the detection methods for cancer through Artificial Intelligence (AI) in different ways. Previously Microscopic reviews of tissues on glass slides are used for cancer diagnostics to improve diagnostic accuracy. We can use different techniques such as digital imaging and artificial intelligence algorithm. Cancer care is also advancing thanks to AI’s ability to collect and process data. Due to the nature of processing this information, the task is often a time-consuming and tedious job for doctors. This process may be made much easier, quicker and efficient through the advancement as well as by using modified technologies.

scholarly journals Research on the impact of artificial intelligence on the business model of an organization

E-Management ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 26-36
Author(s):  
A. A. Dashkov ◽  
Yu. O. Nesterova
Keyword(s):  
Artificial Intelligence ◽  
Information And Communication Technologies ◽  
Business Model ◽  
Digital Transformation ◽  
Successful Implementation ◽  
New Ways Of Working ◽  
Use Of Technology ◽  
Physical Assets ◽  
The Moment ◽  
The Impact

The digital transformation of our world and the inevitable interaction between people, digital technologies and physical assets create a rapidly changing and complex environment that requires organizations to be more flexible, better fit and ready to accept new ways of working. Businesses are coming to realize the need for change to operate successfully in the digital age. In the period of global digitalization, information and communication technologies are one of the most important aspects of existence for a business, which makes it more efficient, efficient and allows you to respond quickly to a rapidly changing external environment, as well as customer needs. At the moment, there is a high interest in the possibilities of artificial intelligence for use in business tasks in the world, as there are already examples of successful implementation, when Artificial Intelligence and machine learning radically change the way they work and increase the profit of organizations in different countries.The purpose of this study is to consider how artificial intelligence affects the value proposition and how the elements of the business model change when using this technology. The paper gives the existing examples of the use of technology, the consequences of its application and the emerging prospects for the use of Artificial Intelligence as one of the advanced technologies of digital transformation.

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