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

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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

The Role of Explainable AI in the Research Field of AI Ethics

Ethics of Artificial Intelligence (AI) is a growing research field that has emerged in response to the challenges related to AI. Transparency poses a key challenge for implementing AI ethics in practice. One solution to transparency issues is AI systems that can explain their decisions. Explainable AI (XAI) refers to AI systems that are interpretable or understandable to humans. The research fields of AI ethics and XAI lack a common framework and conceptualization. There is no clarity of the field’s depth and versatility. A systematic approach to understanding the corpus is needed. A systematic review offers an opportunity to detect research gaps and focus points. This paper presents the results of a systematic mapping study (SMS) of the research field of the Ethics of AI. The focus is on understanding the role of XAI and how the topic has been studied empirically. An SMS is a tool for performing a repeatable and continuable literature search. This paper contributes to the research field with a Systematic Map that visualizes what, how, when, and why XAI has been studied empirically in the field of AI ethics. The mapping reveals research gaps in the area. Empirical contributions are drawn from the analysis. The contributions are reflected on in regards to theoretical and practical implications. As the scope of the SMS is a broader research area of AI ethics the collected dataset opens possibilities to continue the mapping process in other directions.© 2023 Association for Computing Machinery.fi=vertaisarvioitu|en=peerReviewed

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

Sosiaalinen media yrityksen asiakkuudenhallinnassa

Tässä tutkielmassa kerättiin aineistoa kirjallisuuskatsauksena vastauksena kysymykseen: ”Miten yritykset voivat hyödyntää sosiaalista mediaa asiakkuudenhallinnassaan?”. Tutkielman on tarkoitus hyödyttää yrityksiä tarjoamalla tietoa sosiaalisen median käyttömahdollisuuksista. Aineiston keruun jälkeen tulokset on esitetty tutkielman pääluvussa ja koottu ristiintaulukkoon. Ristiintaulukossa on kaksi näkökulmaa: sosiaalisen median hunajakennoteoria ja Zablah, Bellenger ja Johnston:in asiakkuudenhallinnan viisiosainen teoria. Sosiaalisessa mediassa yritys pystyy tutustumaan henkilökohtaisesti asiakkaaseen ja tämän tarpeisiin, muokkaamaan identiteettiään ja brändiään, hallitsemaan itseään koskevaa keskustelua, levittämään tietoa nopeasti, erottamaan markkinointisegmenttejä ja seuraamaan asiakkaiden välistä kommunikaatiota. Suhteiden ja ryhmien hyödyntäminen sosiaalisessa mediassa tarvitsee lisää tutkimusta.The use of social media in customer relationship management. In this literature review, I did research to get an answer to the question: “how can a company take advantage of social media in its customer relationship management (CRM)?”. It is intended to offer companies information on how to implement social media in their CRM. The collected material is presented in the main chapter of the study, textually and within a table. The results in the table are presented from two perspectives: the Social Media Honeycomb framework, and Zablah, Bellenger and Johnston's five-pointed CRM theory. The results of the study show that a company can take advantage of social media in CRM in many ways, but implementing it for optimal results may re-quire skill and consideration: In social media, a company can develop personal relationships to its customers and their needs, modify its identity, control and take part in conversation regarding it, spread information rapidly, distinguish marketing segments and observe communication between customers. Area that requires further study is the use of groups and relationships in social media customer relationship management

Practical implications of ethics in AI development

This Master’s thesis presents two studies: a multiple case study on perceptions and actions of AI prototype developers regarding implementation of AI ethics; and a Grey Literature review of AI ethics guidelines published by corporations, institutions and governments. The empirical study assesses the skills, practices and attitudes towards ethical dimensions of developers who create artificial intelligence applications. The results indicate that the developers have varying levels of knowledge on ethical practices; this appears to be related to the level of responsibility and rank of the developers. because information does not seem to always pass down from supervisors to lower level employees. The developers appeared to delegate responsibility of AI impacts on themselves, their supervisors and their employing institution. A framework of keywords accountability, transparency and responsibility were utilized to discover different aspects of the development. The Grey Literature review indicates that there are certain recurring themes among the studied guidelines, such as transparency, fairness, privacy and accountability, which makes the results in part consistent with the empirical research framework

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

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

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

Artificial 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 idea of using user stories to transform abstract ethical requirements into tangible outcomes in Agile software development. We tested this idea by studying master’s level student projects (15 teams) developing web applications for a real industrial client over the course of five iterations. These projects resulted in 250+ user stories that were analyzed for the purposes of this paper. The teams were divided into two groups: half of the teams worked using the ECCOLA method for AI ethics in SE, while the other half, a control group, was used to compare the effectiveness of ECCOLA. Both teams were tasked with writing user stories to formulate customer needs into system requirements. Based on the data, we discuss the effectiveness of ECCOLA, and Primary Empirical Contributions (PECs) from formulating ethical user stories in Agile development.peerReviewe