How do software companies deal with artificial intelligence ethics? A gap analysis

Peer reviewe

Time for AI (Ethics) maturity model is now

Publisher Copyright: Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).There appears to be a common agreement that ethical concerns are of high importance when it comes to systems equipped with some sort of Artificial Intelligence (AI). Demands for ethical AI are declared from all directions. As a response, in recent years, public bodies, governments, and universities have rushed in to provide a set of principles to be considered when AI based systems are designed and used. We have learned, however, that high-level principles do not turn easily into actionable advice for practitioners. Hence, also companies are publishing their own ethical guidelines to guide their AI development. This paper argues that AI software is still software and needs to be approached from the software development perspective. The software engineering paradigm has introduced maturity model thinking, which provides a roadmap for companies to improve their performance from the selected viewpoints known as the key capabilities. We want to voice out a call for action for the development of a maturity model for AI software. We wish to discuss whether the focus should be on AI ethics or, more broadly, the quality of an AI system, called a maturity model for the development of AI systems.Peer reviewe

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 developing ethically aligned AI systems. In this paper, we propose a maturity model for AI ethics and explain how it can be devised by using a Design Science Research approach.©2021 Authors. Published by Association for Information Systems.fi=vertaisarvioitu|en=peerReviewed

Ethical User stories : Industrial study

Publisher Copyright: © 2022 Copyright for this paper by its authorsIn 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 AI systems, our study provides an ethical angle, Ethical User Stories (EUS). We use an ethically aligned design tool the ECCOLA method to transfer ethical requirements into EUS for non-functional requirements for an aspect of the logistics system, passenger flow. Over the span of six months, 125 EUS using the ECCOLA method were collected through a series of workshops for the passenger flow use case and the findings are revealed in this paper. This project is in the field of maritime industry and concentrates on digitalization of port terminals and this particular paper focuses on the passenger flow. Results are positive towards the practice of Ethical User Stories.Peer reviewe

Beyond 100 Ethical Concerns in the Development of Robot-to-Robot Cooperation

Peer reviewe

Helping students with mathematical difficulties : A literature study about how teaching can be designed to be beneficial.

Matematiksvårigheter är ett komplext och omfattande begrepp som innefattar elever i generella och specifika matematiksvårigheter. Syftet med denna litteraturstudie var att undersöka hur undervisningen kan utformas för att gynna elever i matematiksvårigheter. Litteraturstudien har genomförts genom att samla in, granska och bearbeta forskning som besvarar vår frågeställning och därmed studiens syfte. Vid insamling av data användes databassökning genom sökmotorn UniSearch och manuell sökning. Resultatet visar att elever i matematiksvårigheter gynnas av explicit undervisning. Undervisningens utformning kan organiseras genom att eleverna arbetar i mindre grupp samt representeras med hjälp av digitala spel, individanpassade uppgifter eller genom att eleverna arbetar med räknestrategier.

Helping students with mathematical difficulties : A literature study about how teaching can be designed to be beneficial.

Matematiksvårigheter är ett komplext och omfattande begrepp som innefattar elever i generella och specifika matematiksvårigheter. Syftet med denna litteraturstudie var att undersöka hur undervisningen kan utformas för att gynna elever i matematiksvårigheter. Litteraturstudien har genomförts genom att samla in, granska och bearbeta forskning som besvarar vår frågeställning och därmed studiens syfte. Vid insamling av data användes databassökning genom sökmotorn UniSearch och manuell sökning. Resultatet visar att elever i matematiksvårigheter gynnas av explicit undervisning. Undervisningens utformning kan organiseras genom att eleverna arbetar i mindre grupp samt representeras med hjälp av digitala spel, individanpassade uppgifter eller genom att eleverna arbetar med räknestrategier.

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 ethics closer to conventional SE practice: utilizing user stories to implement AI ethics by means of Ethical User Stories (EUS). EUS can be used to formulate both functional and non-functional requirements, although an ethical framework is required produce them. By treating AI ethics as a part of the development process in this fashion, as opposed to a separate task, it can ideally become a part of SE for ML systems.peerReviewe

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 research approach, ECCOLA has been iteratively developed over the course of multiple years, in collaboration with both researchers and practitioners.peerReviewe

Making ethics practical : User stories as a way of implementing ethical consideration in Software Engineering

Context: Shortcomings of AI systems have recently brought ethics into the spotlight in Software Engineering (SE) in the form of AI ethics. However, actually implementing ethics into practice remains a challenge in both AI ethics and SE at large. Translating abstract ethical principles into requirements and features is difficult and lacks established processes, as well as practices and methods. Objective: In this study, we explored user stories as a way of implementing ethics in SE. Initially, we simply investigated whether user stories could be utilized for this purpose. After we began to consider this possible, we began to develop the concept of ethical user stories (EUSs) as a specific practice for this purpose. Method: We utilized a design science research (DSR) approach to first explore the use of user stories in implementing ethics, and then to develop the concept of EUS. This process featured three DSR phases through which the concept of EUS was iteratively developed with empirical data. Results: Over three DSR iterations, we studied 689 user stories produced in different contexts including both student and industry settings. Based on the data, we defined the concept of EUS and provided empirical validation for it. Conclusions: The concept of EUS provides a novel way of tackling ethics in SE. This paper presents the concept in-depth, along with practical suggestions for utilizing EUS.©2024 Elsevier. This manuscript version is made available under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed