Related papers: Consumer Rights and Algorithms
Credit card frauds are at an ever-increasing rate and have become a major problem in the financial sector. Because of these frauds, card users are hesitant in making purchases and both the merchants and financial institutions bear heavy…
The newly emerged machine learning (e.g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial technology, and surveillance systems. Meanwhile, privacy has…
Extensive recent media focus has been directed towards the dark side of intelligent systems, how algorithms can influence society negatively. Often, transparency is proposed as a solution or step in the right direction. Unfortunately,…
The paper offers a contribution to the interdisciplinary constructs of analyzing fairness issues in automatic algorithmic decisions. Section 1 shows that technical choices in supervised learning have social implications that need to be…
When machine learning systems fail because of adversarial manipulation, how should society expect the law to respond? Through scenarios grounded in adversarial ML literature, we explore how some aspects of computer crime, copyright, and…
Deceptive patterns are design practices embedded in digital platforms to manipulate users, representing a widespread and long-standing issue in the web and mobile software development industry. Legislative actions highlight the urgency of…
Although the history of informatics is recent, this field poses unusual problems with respect to its preservation. These problems are amplified by legal issues, digital law being in itself a subject matter whose history is also worth…
Manipulation defines many of our experiences as a consumer, including subtle nudges and overt advertising campaigns that seek to gain our attention and money. With the advent of digital services that can continuously optimize online…
Large language models (LLMs) are increasingly central to many applications, raising concerns about bias, fairness, and regulatory compliance. This paper reviews risks of biased outputs and their societal impact, focusing on frameworks like…
As algorithms increasingly take on critical roles in high-stakes areas such as credit scoring, housing, and employment, civil enforcement actions have emerged as a powerful tool for countering potential discrimination. These legal actions…
Information has exploded on the Internet and mobile with the advent of the big data era. In particular, recommendation systems are widely used to help consumers who struggle to select the best products among such a large amount of…
The cyberspace and development of intelligent systems using Artificial Intelligence (AI) creates new challenges to computer professionals, data scientists, regulators and policy makers. For example, self-driving cars raise new technical,…
Under the current regulatory framework for data protections, the protection of human rights writ large and the corresponding outcomes are regulated largely independently from the data and tools that both threaten those rights and are needed…
Algorithms learned from data are increasingly used for deciding many aspects in our life: from movies we see, to prices we pay, or medicine we get. Yet there is growing evidence that decision making by inappropriately trained algorithms may…
As financial institutions increasingly rely on machine learning models to automate lending decisions, concerns about algorithmic fairness have risen. This paper explores the tradeoff between enforcing fairness constraints (such as…
The increased adoption of Artificial Intelligence (AI) presents an opportunity to solve many socio-economic and environmental challenges; however, this cannot happen without securing AI-enabled technologies. In recent years, most AI models…
Appropriately regulating artificial intelligence is an increasingly urgent and widespread policy challenge. We identify two primary, competing problem. First is a technical deficit: Legislatures and regulatory face significant challenges in…
AI-based systems are widely employed nowadays to make decisions that have far-reaching impacts on individuals and society. Their decisions might affect everyone, everywhere and anytime, entailing concerns about potential human rights…
Personal data related to a user's activities, preferences and services, is considered to be a valuable commodity not only for a wide range of technology-oriented companies like Google, Amazon and Apple but also for more traditional…
Fair machine learning research has been primarily concerned with classification tasks that result in discrimination. However, as machine learning algorithms are applied in new contexts the harms and injustices that result are qualitatively…