The State of AI Ethics Report (Volume 4)

ArXiv, 2020

The 2nd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in the field of AI Ethics since July 2020. This report aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the ever-changing developments in the field. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, including: AI and society, bias and algorithmic justice, disinformation, humans and AI, labor impacts, privacy, risk, and future of AI ethics. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. These experts include: Danit Gal (Tech Advisor, United Nations), Amba Kak (Director of Global Policy and Programs, NYU's AI Now Institute), Rumman Cho...

ArXiv, 2021

The 3rd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020. It aims to help anyone, from machine learning experts to human rights activists and policymakers, quickly digest and understand the field's ever-changing developments. Through research and article summaries, as well as expert commentary, this report distills the research and reporting surrounding various domains related to the ethics of AI, including: algorithmic injustice, discrimination, ethical AI, labor impacts, misinformation, privacy, risk and security, social media, and more. In addition, The State of AI Ethics includes exclusive content written by world-class AI Ethics experts from universities, research institutes, consulting firms, and governments. Unique to this report is"The Abuse and Misogynoir Playbook,"written by Dr. Katlyn Tuner (Research Scientist, Space Enabled Research Group, MIT), Dr. Danielle Wood...

ArXiv, 2020

These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watchers aghast. Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as we all spend increasingly larger amounts of time online. It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and dev...

2023

Artificial Intelligence (AI) is a rapidly advancing technology that permeates human life at various levels. It evokes hopes for a better, easier, and more exciting life, while also instilling fears about the future without humans. AI has become part of our daily lives, supporting fields such as medicine, customer service, finance, and justice systems; providing entertainment, and driving innovation across diverse fields of knowledge. Some even argue that we have entered the “AI era.” However, AI is not solely a matter of technological progress. We already witness its positive and negative impact on individuals and societies. Hence, it is crucial to examine the primary challenges posed by AI, which is the subject of AI ethics. In this paper, I present the key challenges that emerged in the literature and require ethical reflection. These include the issues of data privacy and security, the problem of AI biases resulting from social, technical, or socio-technical factors, and the challenges associated with using AI for prediction of human behavior (particularly in the context of the justice system). I also discuss existing approaches to AI ethics within the framework of technological regulations and policymaking, presenting concrete ways in which ethics can be implemented in practice. Drawing on the functioning of other scientific and technological fields, such as gene editing, the development of automobile and aviation industries, I highlight the lessons we can learn from how they function to later apply it to how AI is introduced in societies. In the final part of the paper, I analyze two case studies to illustrate the ethical challenges related to recruitment algorithms and risk assessment tools in the criminal justice system. The objective of this work is to contribute to the sustainable development of AI by promoting human-centered, societal, and ethical approaches to its advancement. Such approach seeks to maximize the benefits derived from AI while simultaneously mitigating its diverse negative consequences.

International Journal of Science and Research Archive, 2024

In an era where artificial intelligence (AI) increasingly intersects with every facet of human life, the imperative for ethical AI has never been more pronounced. This paper delves into the complex interplay between technological advancements in AI and the overarching human values that guide societal norms. The background of the study establishes the urgency of addressing ethical challenges inherent in AI, such as privacy, bias, and accountability, within the broader context of regulatory and policy frameworks. Aiming to critically evaluate the integration and effectiveness of ethical principles in AI applications, the paper navigates through a qualitative analysis, employing theoretical frameworks to dissect the ethical dimensions of AI. The scope encompasses a diverse range of topics, including global trends in ethical AI development, the impact of AI on human rights and personal freedoms, and the analysis of bias and fairness in AI algorithms. Real-world case studies provide insights into the successes and failures of ethical AI implementation, while the role of public perception and trust in AI adoption is scrutinized. The main conclusions reveal a dynamic global landscape of ethical AI, emphasizing the need for robust ethical frameworks and proactive strategies to mitigate biases and ensure equitable outcomes. Recommendations advocate for clear ethical guidelines, integration of ethics in AI development, transparency, accountability, multi-stakeholder collaboration, public engagement, and continuous ethical evaluation. The study concludes that balancing technological innovation with ethical constraints is crucial for the responsible development of AI. It underscores the importance of ethical vigilance, ensuring AI aligns with societal values and individual rights.

Cornell University - arXiv, 2021

Go Wide: Article Summaries (summarized by Abhishek Gupta) Ethical AI isn't the same as trustworthy AI, and that matters (Original VentureBeat article by Kimberly Nevala) Google showed us the danger of letting corporations lead AI research (Original QZ article by Nicolás Rivero) If not AI ethicists like Timnit Gebru, who will hold Big Tech accountable? (Original Brookings article by Alex Engler) AI research survey finds machine learning needs a culture change (Original VentureBeat article by Khari Johnson)

Handbook on the Ethics of Artificial Intelligence (Eds. David Gunkel), 97-112 , 2024

This book chapter aims to offer readers insight into the key distinctions between these two fields, specifically in terms of their subject matter, viewpoints, and approaches. Following this introduction, the second section delves into AI ethics, while the third section explores machine ethics. The fourth section offers a synopsis of two important intersecting issues – the moral standing of AI systems and AI ethics in facial recognition technology (as exemplified by China’s Social Credit Point System). The final section provides some concluding remarks.

2022

The paper presents an ethical analysis and constructive critique of the current practice of AI ethics. It identifies conceptual substantive and procedural challenges and it outlines strategies to address them. The strategies include countering the hype and understanding AI as ubiquitous infrastructure including neglected issues of ethics and justice such as structural background injustices into the scope of AI ethics and making the procedures and fora of AI ethics more inclusive and better informed with regard to philosophical ethics. These measures integrate the perspective of AI justice into AI ethics, strengthening its capacity to provide comprehensive normative orientation and guidance for the development and use of AI that actually improves human lives and living together. People around the globe increasingly encounter, use and benefit from AI in their daily lives in one form or another. AI-based applications range from web-based maps and navigation services to digital behavioural technologies such as mobile health apps, from recommender algorithms in online stores to parking aids, and AI-based services in policing, the legal system, etc. Also, less exciting but tedious taskssuch as analysing immense amounts of data in different domains, or determining the next date for a maintenance check of a machine-can, fortunately, increasingly be done by AI-based systems, relieving humans from burdensome work. Once they are well set up, such AI-based systems work quickly and effectively through vast amounts of data that cannot be handled by humans. And they do so more reliably than humans because machines-unlike humans-are not distracted by fatigue, hunger or the like. AI figures among the most advanced tools humanity has developed to date, yet its potential for future development remains vast. That is why the High-Level Expert * Jan-Christoph Heilinger

2022 ACM Conference on Fairness, Accountability, and Transparency

How has recent AI Ethics literature addressed topics such as fairness and justice in the context of continued social and structural power asymmetries? We trace both the historical roots and current landmark work that have been shaping the field and categorize these works under three broad umbrellas: (i) those grounded in Western canonical philosophy, (ii) mathematical and statistical methods, and (iii) those emerging from critical data/algorithm/information studies. We also survey the field and explore emerging trends by examining the rapidly growing body of literature that falls under the broad umbrella of AI Ethics. To that end, we read and annotated peer-reviewed papers published over the past four years in two premier conferences: FAccT and AIES. We organize the literature based on an annotation scheme we developed according to three main dimensions: whether the paper deals with concrete applications, use-cases, and/or people's lived experience; to what extent it addresses harmed, threatened, or otherwise marginalized groups; and if so, whether it explicitly names such groups. We note that although the goals of the majority of FAccT and AIES papers were often commendable, their consideration of the negative impacts of AI on traditionally marginalized groups remained shallow. Taken together, our conceptual analysis and the data from annotated papers indicate that the field would benefit from an increased focus This work is licensed under a Creative Commons Attribution International 4.0 License.

Artificial intelligence (AI) is rapidly reshaping our world. As AI systems become increasingly autonomous and integrated into various sectors, fundamental ethical issues such as accountability, transparency, bias, and privacy are exacerbated or morph into new forms. This introduction provides an overview of the current ethical landscape of AI. It explores the pressing need to address biases in AI systems, protect individual privacy, ensure transparency and accountability, and manage the broader societal impacts of AI on labour markets, education, and social interactions. It also highlights the global nature of AI's challenges, such as its environmental impact and security risks, stressing the importance of international collaboration and culturally sensitive ethical guidelines. It then outlines three unprecedented challenges AI poses to copyright and intellectual property rights; individual autonomy through AI's "hypersuasion"; and our understanding of authenticity, originality, and creativity through the transformative impact of AI-generated content. The conclusion emphasises the importance of ongoing critical vigilance, imaginative conceptual design, and collaborative efforts between diverse stakeholders to deal with the ethical complexities of AI and shape a sustainable and socially preferable future. It underscores the crucial role of philosophy in identifying and analysing the most significant problems and designing convincing and feasible solutions, calling for a new, engaged, and constructive approach to philosophical inquiry in the digital age.