The uselessness of AI ethics

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.

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

AI and Ethics

Bias, unfairness and lack of transparency and accountability in Artificial Intelligence (AI) systems, and the potential for the misuse of predictive models for decision-making have raised concerns about the ethical impact and unintended consequences of new technologies for society across every sector where data-driven innovation is taking place. This paper reviews the landscape of suggested ethical frameworks with a focus on those which go beyond high-level statements of principles and offer practical tools for application of these principles in the production and deployment of systems. This work provides an assessment of these practical frameworks with the lens of known best practices for impact assessment and audit of technology. We review other historical uses of risk assessments and audits and create a typology that allows us to compare current AI ethics tools to Best Practices found in previous methodologies from technology, environment, privacy, finance and engineering. We ana...

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.

ArXiv, 2021

The 4th 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 January 2021. 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, with a particular focus on four key themes: Ethical AI, Fairness&Justice, Humans&Tech, and Privacy. 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. Opening the report is a long-form piece by Edward Higgs (Professor of History, University of Essex) titled"AI and the Face: A Historian's View."In it, Higgs examines the unscientif...

The debate on the ethical challenges of artificial intelligence (AI) is nothing new. Researchers and commentators have highlighted the deficiencies of AI technology regarding visible minorities, women, youth, seniors and indigenous people. Currently, there are several ethical guidelines and recommendations for AI. These guidelines provide ethical principles and humancentred values to guide the creation of responsible AI. Since these guidelines are non-binding, it has no significant effect. It is time to harness initiatives to regulate AI globally and incorporate human rights and ethical standards in AI creation. The government need to intervene, and discriminated groups should lend their voice to shape AI regulation to suit their circumstances. This study highlights the discriminatory and technological risks suffered by minority/marginalised groups owing to AI's ethical dilemma. As a result, it recommends the guarded deployment of AI vigilantism to regulate the use of AI technologies and prevent harm arising from AI systems' operations. The appointed AI vigilantes will comprise mainly persons/groups with an increased risk of their rights being disproportionately impacted by AI. It is a well-intentioned group that will work with the government to avoid abuse of powers.

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.

Big Data & Society, 2020

Ethics has powerful teeth, but these are barely being used in the ethics of AI today – it is no wonder the ethics of AI is then blamed for having no teeth. This article argues that ‘ethics’ in the current AI ethics field is largely ineffective, trapped in an ‘ethical principles’ approach and as such particularly prone to manipulation, especially by industry actors. Using ethics as a substitute for law risks its abuse and misuse. This significantly limits what ethics can achieve and is a great loss to the AI field and its impacts on individuals and society. This article discusses these risks and then highlights the teeth of ethics and the essential value they can – and should – bring to AI ethics now.

SSRN Electronic Journal

AI Ethics is now a global topic of discussion in academic and policy circles. At least 84 public-private initiatives have produced statements describing high-level principles, values, and other tenets to guide the ethical development, deployment, and governance of AI. According to recent meta-analyses, AI Ethics has seemingly converged on a set of principles that closely resemble the four classic principles of medical ethics. Despite the initial credibility granted to a principled approach to AI Ethics by the connection to principles in medical ethics, there are reasons to be concerned about its future impact on AI development and governance. Significant differences exist between medicine and AI development that suggest a principled approach in the latter may not enjoy success comparable to the former. Compared to medicine, AI development lacks (1) common aims and fiduciary duties, (2) professional history and norms, (3) proven methods to translate principles into practice, and (4) robust legal and professional accountability mechanisms. These differences suggest we should not yet celebrate consensus around high-level principles that hide deep political and normative disagreement.