ACM TechBriefs

The new edition concerns the proliferation of data collection, advanced algorithms, and powerful computers which have made it easy to piece together information about individuals’ private lives from public information—even as controls over information privacy become increasingly ineffective. In an era of ubiquitous data collection and massive computing capacity, society faces unprecedented challenges to protecting information privacy. Technical advances in the fields of computer science, statistics, and information science both starkly illuminate privacy risks and have the potential to provide a foundation for privacy protection that is more systematic and effective.

This edition is focused on the problem that deficiencies in critical testing data and automated vehicle technology are impeding informed regulation and possible deployment of demonstrably safe automated vehicles. While it is unclear that fully automated vehicles will be able to operate safely without a human driver’s attention, regulators should not assume that fully automated vehicles will necessarily reduce road injuries and fatalities. Improved safety outcomes depend on appropriately regulating the safety engineering, testing, and ongoing performance of automated vehicles.

This edition is focused on the effectiveness of mechanisms and metrics implemented to promote trust of AI must be empirically evaluated to determine if they actually do so. Distrust of AI implicates trustworthiness and calls for a deeper understanding of stakeholder perceptions, concerns, and fears associated with AI and its specific applications. Fostering public trust of AI will require that policymakers demonstrate how they are making industry accountable to the public and their legitimate concerns.

This edition is focused on the rapid commercialization of generative AI (GenAI) posing multiple large-scale risks to individuals, society, and the planet which requires a rapid, internationally coordinated response to mitigate. It also presents conclusions concerning AI policy incoporting end-to-end governance approaches that address risks “by design” and regulate at all stages of the design-to-deployment life cycle of AI products, governance mechanisms for GenAI technologies.

This edition is focused on a key challenge: that the full potential of data-driven systems cannot be realized without better understanding the roots of the distrust they can engender. Importantly, the TechBrief dispels the popular misconception that a lack of trust in data systems is a result of poor data literacy among the public. However, the TechBrief points out that greater literacy often increases distrust. It also cites studies revealing that trust in data systems varies according to the context and institution that is handling the data.

This edition states that the ubiquity of algorithmic systems creates serious risks that are not being adequately addressed. A recurring theme of the TechBrief is that while incredibly useful and generally benign, when deployed in complex systems algorithms can cause a variety of profound harms to individuals and to society, threatening opportunity, liberty, and even life itself. To that end, it recommends that enabling safer algorithmic systems must be a high research and policy priority of governments and all stakeholders.

This edition explores the benefits of risk-limiting audits (RLAs), which were designed to determine how many post-election random ballot samples must be examined manually to assure the accuracy and integrity of a vote count. The TechBrief includes an overview of RLAs, the different techniques in which they are used, what conditions are necessary for optimum utilization, and the importance of RLAs in maintaining the public trust, among other benefits.

This edition focuses on the concept of quantum computing and simulation, a quickly advancing field of computer science with the potential for impacting many different and vitally important facets of life in the real world. Here, the TPC explores the various yet profound societal and individual risks this technology may pose, its potential benefits, and how the government, private sector, and CS as a whole should proceed with a varying combination of caution and confidence in this emerging area.

This edition focuses on the concept of Smart Cities and how to deploy information and communication technology (ICT) to create such cities without compromising either personal or societal freedoms. Concerns raised by such emerging tech include: cybersecurity risks at every stage of every smart city technology’s life cycle; effective privacy protection mechanisms as an essential component; transparancy and fairness to all city users, not just residents; and understanding the climate impact of smart city infrastructures both during design and after deployment.

This TechBrief focuses on policy issues raised by facial recognition and its use by governments and the private sector. Noting that “facial recognition use is increasing despite the technology’s fundamental limitations, creating profound privacy and ethical challenges,” the TechBrief covers the myriad of problems with such tech including that facial recognition is not a single, dependable technology, the inherent dangers to personal privacy, the evidence that bias in facial recognition systems is pervasive and profound, and that responsible application of facial recognition technology requires careful, scientifcally informed, and ongoing governance.

The first TechBrief concerns the deepening crisis of climate change, focusing on the issue that computing can help mitigate it but must first cease contributing to it. Policy implications suggested by the TPC include that all-encompassing measurements of Information and Communication Technology sector carbon emissions are needed to assess whether reduction targets have been met, computing-enabled efficiencies must be coupled with slashed energy demands, and that coordinated, clear, and enforceable governmental policies and law are needed to reduce ICT carbon emissions.