0000000000040380

AUTHOR

Erika Halme

0000-0003-0750-1580

How Do Software Companies Deal with Artificial Intelligence Ethics? : A Gap Analysis

The public and academic discussion on Artificial Intelligence (AI) ethics is accelerating and the general public is becoming more aware AI ethics issues such as data privacy in these systems. To guide ethical development of AI systems, governmental and institutional actors, as well as companies, have drafted various guidelines for ethical AI. Though these guidelines are becoming increasingly common, they have been criticized for a lack of impact on industrial practice. There seems to be a gap between research and practice in the area, though its exact nature remains unknown. In this paper, we present a gap analysis of the current state of the art by comparing practices of 39 companies that …

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Ethical User stories : Industrial study

Publisher Copyright: © 2022 Copyright for this paper by its authors In Port terminals a progressive change is underway in digitalizing traditional systems to SMART systems with the aid of AI. This study follows one of such progressions, the SMARTER project. SMARTER is a sub research and development project of the Sea for Value program of DIMECC company, Finland to create replicable models for digitalization for future terminals which involves the use of AI enabled tools. AI and Autonomous Systems (AS) are the direction that software systems are taking today. But due to ethical challenges involved in the use of AI systems and increased emphasis on ethical practices in the use and design of A…

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How to Write Ethical User Stories? : Impacts of the ECCOLA Method

AbstractArtificial Intelligence (AI) systems are increasing in significance within software services. Unfortunately, these systems are not flawless. Their faults, failures and other systemic issues have emphasized the urgency for consideration of ethical standards and practices in AI engineering. Despite the growing number of studies in AI ethics, comparatively little attention has been placed on how ethical issues can be mitigated in software engineering (SE) practice. Currently understanding is lacking regarding the provision of useful tools that can help companies transform high-level ethical guidelines for AI ethics into the actual workflow of developers. In this paper, we explore the i…

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Building a Maturity Model for Developing Ethically Aligned AI Systems

Ethical concerns related to Artificial Intelligence (AI) equipped systems are prompting demands for ethical AI from all directions. As a response, in recent years public bodies, governments, and companies have rushed to provide guidelines and principles for how AI-based systems are designed and used ethically. We have learned, however, that high-level principles and ethical guidelines cannot be easily converted into actionable advice for industrial organizations that develop AI-based information systems. Maturity models are commonly used in software and systems development companies as a roadmap for improving the performance. We argue that they could also be applied in the context of develo…

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ECCOLA : a method for implementing ethically aligned AI systems

Artificial Intelligence (AI) systems are becoming increasingly widespread and exert a growing influence on society at large. The growing impact of these systems has also highlighted potential issues that may arise from their utilization, such as data privacy issues, resulting in calls for ethical AI systems. Yet, how to develop ethical AI systems remains an important question in the area. How should the principles and values be converted into requirements for these systems, and what should developers and the organizations developing these systems do? To further bridge this gap in the area, in this paper, we present a method for implementing AI ethics: ECCOLA. Following a cyclical action res…

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Utilizing User Stories to Bring AI Ethics into Practice in Software Engineering

AI ethics is a research area characterized by a prominent gap between research and practice. With most studies in the area being conceptual in nature or focused on technical ML (Machine Learning) solutions, the link between AI (Artificial Intelligence) ethics and SE (Software Engineering) practice remains thin. Establishing this link, we argue, is vital going forward. While conceptual discussion is required to define AI ethics, much progress has already been made in this regard. Similarly, though technical ML solutions are also required for practical implementation, ML systems are ultimately still software, and thus SE cannot be forgotten. In this paper, we propose one way of bringing AI et…

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A Deployment Model to Extend Ethically Aligned AI Implementation Method ECCOLA

There is a struggle in Artificial intelligence (AI) ethics to gain ground in actionable methods and models to be utilized by practitioners while developing and implementing ethically sound AI systems. AI ethics is a vague concept without a consensus of definition or theoretical grounding and bearing little connection to practice. Practice involving primarily technical tasks like software development is not aptly equipped to process and decide upon ethical considerations. Efforts to create tools and guidelines to help people working with AI development have been concentrating almost solely on the technical aspects of AI. A few exceptions do apply, such as the ECCOIA method for creating ethic…

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Governance of Ethical and Trustworthy Al Systems: Research Gaps in the ECCOLA Method

Advances in machine learning (ML) technologies have greatly improved Artificial Intelligence (AI) systems. As a result, AI systems have become ubiquitous, with their application prevalent in virtually all sectors. However, AI systems have prompted ethical concerns, especially as their usage crosses boundaries in sensitive areas such as healthcare, transportation, and security. As a result, users are calling for better AI governance practices in ethical AI systems. Therefore, AI development methods are encouraged to foster these practices. This research analyzes the ECCOLA method for developing ethical and trustworthy AI systems to determine if it enables AI governance in development process…

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