Industry involvement in the machine learning (ML) community seems to be increasing. However, the quantitative scale and ethical implications of this influence are rather unknown. For this purpose, we have not only carried out an informed ethical analysis of the field, but have inspected all papers of the main ML conferences NeurIPS, CVPR, and ICML of the last 5 years - almost 11,000 papers in total. Our statistical approach focuses on conflicts of interest, innovation and gender equality. We have obtained four main findings: (1) Academic-corporate collaborations are growing in numbers. At the same time, we found that conflicts of interest are rarely disclosed. (2) Industry publishes papers about trending ML topics on average two years earlier than academia does. (3) Industry papers are not lagging behind academic papers in regard to social impact considerations. (4) Finally, we demonstrate that industrial papers fall short of their academic counterparts with respect to the ratio of gender diversity. We believe that this work is a starting point for an informed debate within and outside of the ML community.
Columbia University（哥伦比亚大学）；Parity；J. P. Morgan（摩根大通）
Artificial intelligence (AI) continues to find more numerous and more critical applications in the financial services industry, giving rise to fair and ethical AI as an industry-wide objective. While many ethical principles and guidelines have been published in recent years, they fall short of addressing the serious challenges that model developers face when building ethical AI solutions. We survey the practical and overarching issues surrounding model development, from design and implementation complexities, to the shortage of tools, and the lack of organizational constructs. We show how prac…
Generative AI and LLMs in Industry: A text-mining Analysis and Critical Evaluation of Guidelines and Policy Statements Across Fourteen Industrial Sectors
The University of Texas at Austin（德克萨斯大学奥斯汀分校）；Allen Institute for AI（艾伦人工智能研究所）；IBM Research（IBM研究院）
The field of computer science is perhaps uniquely connected with industry. For example, our main publication outlets (i.e. conferences) are regularly sponsored by large technology companies, and much of our research funding is either directly or indirectly provided by industry. In turn, this places potential limitations on academic freedom, which is a profound ethical concern, yet curiously is not directly addressed within existing ethical codes. A field that limits academic freedom presents the risk that the results of the work conducted within it cannot always be relied upon. In the context …
Machine behavior that is based on learning algorithms can be significantly influenced by the exposure to data of different qualities. Up to now, those qualities are solely measured in technical terms, but not in ethical ones, despite the significant role of training and annotation data in supervised machine learning. This is the first study to fill this gap by describing new dimensions of data quality for supervised machine learning applications. Based on the rationale that different social and psychological backgrounds of individuals correlate in practice with different modes of human-compute…
The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues for more caution with the use of counterfactuals when the facts to be considered are social categories such as race or gender. We review a broad body of papers from philosophy and social sciences on social ontology and the semantics of counterfactuals, and we conclude that the counterfactual approach in machine learning fairness and social explainability can require an incoherent theory of what social categories are…
Pontifical Catholic University of Rio Grande do Sul（南里奥格兰德天主教大学）
The 4th Industrial Revolution is the culmination of the digital age. Nowadays, technologies such as robotics, nanotechnology, genetics, and artificial intelligence promise to transform our world and the way we live. Artificial Intelligence Ethics and Safety is an emerging research field that has been gaining popularity in recent years. Several private, public and non-governmental organizations have published guidelines proposing ethical principles for regulating the use and development of autonomous intelligent systems. Meta-analyses of the AI Ethics research field point to convergence on cert…
National University of Singapore（新加坡国立大学）；Agency for Science, Technology and Research（新加坡科技研究局）
The recent rapid advancements in artificial intelligence research and deployment have sparked more discussion about the potential ramifications of socially- and emotionally-intelligent AI. The question is not if research can produce such affectively-aware AI, but when it will. What will it mean for society when machines -- and the corporations and governments they serve -- can "read" people's minds and emotions? What should developers and operators of such AI do, and what should they not do? The goal of this article is to pre-empt some of the potential implications of these developments, and p…
This paper examines how pharmaceutical Artificial Intelligence advancements may affect the development of new drugs in the coming years. The question was answered by reviewing a rich body of source material, including industry literature, research journals, AI studies, market reports, market projections, discussion papers, press releases, and organizations' websites. The paper argues that continued innovation in pharmaceutical AI will enable rapid development of safe and effective therapies for previously untreatable diseases. A series of major points support this conclusion: The pharmaceutica…
This paper presents the Erasmus Mundus Joint Master Degree in Pervasive Computing and Communications for Sustainable Development (PERCCOM). This program brings together 11 academic partners and 8 industry partners to combine advanced Information and Communication Technologies (ICT) with environmental awareness to enable world-class education and unique competences for ICT professionals who can build cleaner, greener, more resource and energy efficient cyber-physical systems. First, this paper describes the rationale and motivations for ICT education for sustainability challenges. It then detai…
The ethical implications and social impacts of artificial intelligence have become topics of compelling interest to industry, researchers in academia, and the public. However, current analyses of AI in a global context are biased toward perspectives held in the U.S., and limited by a lack of research, especially outside the U.S. and Western Europe. This article summarizes the key findings of a literature review of recent social science scholarship on the social impacts of AI and related technologies in five global regions. Our team of social science researchers reviewed more than 800 academic …
The Narrow Depth and Breadth of Corporate Responsible AI Research
Sam M. Walton College of Business, University of Arkansas（阿肯色大学沃尔顿商学院）；Lundquist College of Business, University of Oregon（俄勒冈大学伦德奎斯特商学院）；Mendoza College of Business, University of Notre Dame（圣母门多萨商学院）；School of Computing, Southern Illinois University（南伊利诺伊大学计算机学院）
Technion - Israel Institute of Technology（以色列理工学院）；ALTER (Association for Long Term Existence and Resilience)（ALTER（长期存在与韧性协会））；Transformative Futures Institute（变革性未来研究所）；National Intelligence University（国家情报大学）
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively abou…
