Responsible AI Development for Sustainable Enterprises A Review of Integrating Ethical AI with IoT and Enterprise Systems (original) (raw)

Toward Responsible AI Use: Considerations for Sustainability Impact Assessment

arXiv (Cornell University), 2023

As AI/ML models, including Large Language Models, continue to scale with massive datasets, so does their consumption of undeniably limited natural resources, and impact on society. In this collaboration between AI, Sustainability, HCI and legal researchers, we aim to enable a transition to sustainable AI development by enabling stakeholders across the AI value chain to assess and quantitfy the environmental and societal impact of AI. We present the ESG Digital and Green Index (DGI), which offers a dashboard for assessing a company's performance in achieving sustainability targets. This includes monitoring the efficiency and sustainable use of limited natural resources related to AI technologies (water, electricity, etc). It also addresses the societal and governance challenges related to AI. The DGI creates incentives for companies to align their pathway with the Sustainable Development Goals (SDGs). The value, challenges and limitations of our methodology and findings are discussed in the paper.

Sustainable AI: An inventory of the state of knowledge of ethical, social, and legal challenges related to artificial intelligence

2019

This report is an inventory of the state of knowledge of ethical, social, and legal challenges related to artificial intelligence conducted within the Swedish Vinnova-funded project “Hallbar AI – AI Ethics and Sustainability”, led by Anna Fellander. Based on a review and mapping of reports and studies, a quantitative and bibliometric analysis, and in-depth analyses of the healt- care sector, the telecom sector, and digital platforms, the report proposes three recommendations. Sustainable AI requires: 1. a broad focus on AI governance and regulation issues, 2. promoting multi-disciplinary collaboration, and 3. building trust in AI applications and applied machine-learning, which is a matter of key importance and requires further study of the relationship between transparency and accountability. (Less)

Artificial intelligence governance: Ethical considerations and implications for social responsibility

Expert Systems, 2023

A number of articles are increasingly raising awareness on the different uses of artificial intelligence (AI) technologies for customers and businesses. Many authors discuss about their benefits and possible challenges. However, for the time being, there is still limited research focused on AI principles and regulatory guidelines for the developers of expert systems like machine learning (ML) and/or deep learning (DL) technologies. This research addresses this knowledge gap in the academic literature. The objectives of this contribution are threefold: (i) It describes AI governance frameworks that were put forward by technology conglomerates, policy makers and by intergovernmental organizations, (ii) It sheds light on the extant literature on “AI governance” as well as on the intersection of “AI” and “corporate social responsibility” (CSR), (iii) It identifies key dimensions of AI governance, and elaborates about the promotion of accountability and transparency; explainability, interpretability and reproducibility; fairness and inclusiveness; privacy and safety of end users, as well as on the prevention of risks and of cyber security issues from AI systems. This research implies that all those who are involved in the research, development and maintenance of AI systems, have social and ethical responsibilities to bear toward their consumers as well as to other stakeholders in society.

Artificial Intelligence and Corporate Social Responsibility Synergies, Challenges, and Future Directions

International Journal of Advanced Multidisciplinary Research and Studies, 2024

Corporate social responsibility, or CSR, has been the subject of an increasing amount of interest with the infusion of artificial intelligence or AI. AI may open up much-needed improvements in CSR practice, including better decision making, transparency, and sustainable benefits, but it also poses challenges related to the ethical concerns of data privacy, bias, and accountability. This paper focuses on how an AI-based approach enhances CSR activities and identifies risks embedded in AI adoption in approaches to CSR. The study combines qualitative interviews with industry experts and quantitative analysis of CSR reports from AI-adopting firms and thus sheds lights on the upside and downside of AI-enhanced CSR. Finally, this article ends with recommendations in developing a framework that would align AI capabilities with CSR objectives and indicates how that may potentially challenge future research directions in order to mitigate the ethical challenges involved.

Unveiling The Potential Of Ai: Impacts On Industries And Ethical Considerations

Educational Administration: Theory and Practice, 2024

Background: Artificial Intelligence (AI) is widely regarded as a transformative tool capable of enhancing business processes, altering societal dynamics, and addressing sustainability challenges. This article explores the diverse positive effects of AI integration across various sectors and the associated challenges. Objectives: To analyze the positive impacts of AI in social, economic, and technical contexts, and to identify the problems it poses. The study aims to provide insights into how AI can optimize decision-making, improve processes, and drive innovation while addressing ethical and regulatory concerns. Methods: A comprehensive review of current literature and data analysis was conducted to examine the application of AI in various sectors, including healthcare, education, transportation, and public service delivery. The study also considers the potential negative consequences of AI, such as job displacement, ethical issues, and environmental impacts. Results: • AI has significantly improved decision-making and optimization in various sectors, leading to smarter supply chains, more effective promotional campaigns, better healthcare diagnostics, and safer transportation systems. • Despite these benefits, AI poses several challenges, including job loss due to automation, ethical concerns related to data privacy and algorithm bias, and environmental issues such as high energy consumption and electronic waste. Discussion: The integration of AI into business and societal processes requires a balanced approach that involves cross-functional stakeholder engagement and ongoing ethical evaluation. Policymakers, industry leaders, and civil society must collaborate to harness AI's potential while mitigating its negative impacts. Conclusions: The advancement of AI offers significant opportunities for societal and economic improvement. However, responsible AI innovation and inclusive decision-making processes are crucial to ensure that the benefits are widely shared and the risks are minimized. Future efforts should focus on promoting sustainable AI practices and addressing ethical and regulatory challenges to achieve a progressive and responsible future for all.

Strategic Integration of Artificial Intelligence for Sustainable Businesses: Implications for Data Management and Human User Engagement in the Digital Era

Sustainability

This research paper delves into the pivotal role of strategic integration of artificial intelligence (AI) concepts across sustainability efforts in for-profit businesses. As organizations are increasingly starting to rely on AI-driven solutions, this study examines the profound implications of AI integration for two critical facets: impact on data management in companies and diversification of human engagement during interactions in the digital ecosystem. The main goal of this research is to analyze the AI adoption index within a sample of 240 medium and large-sized companies (therefore excluding new companies, small startups, and low-scale AI applications). Firstly, the paper scrutinizes how AI technologies enhance data management by enabling efficient data collection, analysis, and utilization. It emphasizes the importance of AI-driven data analytics in improving decision-making processes, resource optimization, and overall operational efficiency for sustainable practices. Secondl...

Garbage in, toxic data out: a proposal for ethical artificial intelligence sustainability impact statements

AI and Ethics

Data and autonomous systems are taking over our lives, from healthcare to smart homes very few aspects of our day to day are not permeated by them. The technological advances enabled by these technologies are limitless. However, with advantages so too come challenges. As these technologies encompass more and more aspects of our lives, we are forgetting the ethical, legal, safety and moral concerns that arise as an outcome of integrating our lives with technology. In this work, we study the lifecycle of artificial intelligence from data gathering to deployment, providing a structured analytical assessment of the potential ethical, safety and legal concerns. The paper then presents the foundations for the first ethical artificial intelligence sustainability statement to guide future development of AI in a safe and sustainable manner.

Promote Sustainable AI to Limit the Ethical and Technological Futuristic Issues

2021

ABSTRACT: AI as a technology is effective in bringing about much transformations but it cannot be denied that along with the advantages that it is laced up with, there are certain challenges as well. These challenges mostly relate to ethical issues and the concern here is how sustainable is AI or how is the concept of sustainability related to AI. The main objective of the paper is to discuss on the ethical issues of AI in brief and then to figure out as to how the world can move towards sustainable AI technology. The study is needed in this time when across the world there are growing concerns as to how human activities can be sustainable. Sustainability has to be the core issue and with a technology as AI that is being taken as one of the major technologies, there is a need to evaluate it in terms of sustainability. Here the method used is simple and is fully based on reviewing of recent articles, journals and other secondary sources taken from the website Google Scholar. The majo...

Toward an Understanding of Responsible Artificial Intelligence Practices

Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020

Artificial Intelligence (AI) is influencing all aspects of human and business activities nowadays. Although potential benefits emerged from AI technologies have been widely discussed in many current literature, there is an urgently need to understand how AI can be designed to operate responsibly and act in a manner meeting stakeholders' expectations and applicable regulations. We seek to fill the gap by exploring the practices of responsible AI and identifying the potential benefits when implementing responsible AI practices. In this study, 10 responsible AI cases were selected from different industries to better understand the use of responsible AI in practices. Four responsible AI practices are identified, including governance, ethically design solutions, risk control and training and education and five strategies for firms who are considering to adopt responsible AI practices are recommended.