We are in the midst of a technological revolution that will fundamentally alter the way we live, ... more We are in the midst of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. Artificial Intelligence (AI) promises to transform many aspects of our society and economy.
There is broad scientific consensus that the capabilities of AI systems have progressed rapidly on many tasks in the last five years. Large Language Models (LLMs) are a particularly salient example. In 2019, GPT-2, then the most advanced LLM, could not reliably produce a coherent paragraph of text and could not always count to ten. At the time of writing, the most powerful LLMs like Claude 3, GPT-4, and Gemini Ultra can engage consistently in multi-turn conversations, write short computer programs, translate between multiple languages, score highly on university entrance exams, and summarise long documents.
This step-change in capabilities, and the potential for continued progress, could help advance the public interest in many ways. Among the most promising prospects are AI’s potential for education, medical applications, research advances in a wide range of fields, and increased innovation leading to increased prosperity. This rapid progress has also increased awareness of the current harms and potential future risks associated with the most capable types of AI.
Physical retailers, who once led the way in tracking with loyalty cards and ‘reverse appends’, no... more Physical retailers, who once led the way in tracking with loyalty cards and ‘reverse appends’, now lag begin online competitors. Yet we might be seeing these tables turn, as many increasingly deploy technologies ranging from simple sensors to advanced emotion detection systems, even enabling them to tailor prices and shopping experiences on a per-customer basis. Here, we examine these in-store tracking technologies in the retail context, and evaluate them from both technical and regulatory standpoints. We first introduce the relevant technologies in context, before considering privacy impacts, the current remedies individuals might seek through technology and the law, and those remedies’ limitations. To illustrate challenging tensions in this space we consider the feasibility of technical and legal approaches to both a) the recent ‘Go’ store concept from Amazon which requires fine-grained, multi-modal track- ing to function as a shop; and b) current challenges in opting in or out of...
Nowadays users often possess a variety of electronic devices for communication and entertainment.... more Nowadays users often possess a variety of electronic devices for communication and entertainment. In particular, smartphones are playing an increasingly central role in users’ lives: Users carry them everywhere they go and often use them to control other devices. This trend provides incentives for the industry to tackle new challenges, such as cross-device authentication, and to develop new monetization schemes. A new technology based on ultrasounds has recently emerged to meet these demands. Ultrasound technology has a number of desirable features: it is easy to deploy, flexible, and inaudible by humans. This technology is already utilized in a number of different real-world applications, such as device pairing, proximity detection, and cross-device tracking.This paper examines the different facets of ultrasound-based technology. Initially, we discuss how it is already used in the real world, and subsequently examine this emerging technology from the privacy and security perspectiv...
We are in the midst of a technological revolution that will fundamentally alter the way we live, ... more We are in the midst of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. Artificial Intelligence (AI) promises to transform many aspects of our society and economy.
There is broad scientific consensus that the capabilities of AI systems have progressed rapidly on many tasks in the last five years. Large Language Models (LLMs) are a particularly salient example. In 2019, GPT-2, then the most advanced LLM, could not reliably produce a coherent paragraph of text and could not always count to ten. At the time of writing, the most powerful LLMs like Claude 3, GPT-4, and Gemini Ultra can engage consistently in multi-turn conversations, write short computer programs, translate between multiple languages, score highly on university entrance exams, and summarise long documents.
This step-change in capabilities, and the potential for continued progress, could help advance the public interest in many ways. Among the most promising prospects are AI’s potential for education, medical applications, research advances in a wide range of fields, and increased innovation leading to increased prosperity. This rapid progress has also increased awareness of the current harms and potential future risks associated with the most capable types of AI.
Physical retailers, who once led the way in tracking with loyalty cards and ‘reverse appends’, no... more Physical retailers, who once led the way in tracking with loyalty cards and ‘reverse appends’, now lag begin online competitors. Yet we might be seeing these tables turn, as many increasingly deploy technologies ranging from simple sensors to advanced emotion detection systems, even enabling them to tailor prices and shopping experiences on a per-customer basis. Here, we examine these in-store tracking technologies in the retail context, and evaluate them from both technical and regulatory standpoints. We first introduce the relevant technologies in context, before considering privacy impacts, the current remedies individuals might seek through technology and the law, and those remedies’ limitations. To illustrate challenging tensions in this space we consider the feasibility of technical and legal approaches to both a) the recent ‘Go’ store concept from Amazon which requires fine-grained, multi-modal track- ing to function as a shop; and b) current challenges in opting in or out of...
Nowadays users often possess a variety of electronic devices for communication and entertainment.... more Nowadays users often possess a variety of electronic devices for communication and entertainment. In particular, smartphones are playing an increasingly central role in users’ lives: Users carry them everywhere they go and often use them to control other devices. This trend provides incentives for the industry to tackle new challenges, such as cross-device authentication, and to develop new monetization schemes. A new technology based on ultrasounds has recently emerged to meet these demands. Ultrasound technology has a number of desirable features: it is easy to deploy, flexible, and inaudible by humans. This technology is already utilized in a number of different real-world applications, such as device pairing, proximity detection, and cross-device tracking.This paper examines the different facets of ultrasound-based technology. Initially, we discuss how it is already used in the real world, and subsequently examine this emerging technology from the privacy and security perspectiv...
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There is broad scientific consensus that the capabilities of AI systems have progressed rapidly on many tasks in the last five years. Large Language Models (LLMs) are a particularly salient example. In 2019, GPT-2, then the most advanced LLM, could not reliably produce a coherent paragraph of text and could not always count to ten. At the time of writing, the most powerful LLMs like Claude 3, GPT-4, and Gemini Ultra can engage consistently in multi-turn conversations, write short computer programs, translate between multiple languages, score highly on university entrance exams, and summarise long documents.
This step-change in capabilities, and the potential for continued progress, could help advance the public interest in many ways. Among the most promising prospects are AI’s potential for education, medical applications, research advances in a wide range of fields, and increased innovation leading to increased prosperity. This rapid progress has also increased awareness of the current harms and potential future risks associated with the most capable types of AI.
There is broad scientific consensus that the capabilities of AI systems have progressed rapidly on many tasks in the last five years. Large Language Models (LLMs) are a particularly salient example. In 2019, GPT-2, then the most advanced LLM, could not reliably produce a coherent paragraph of text and could not always count to ten. At the time of writing, the most powerful LLMs like Claude 3, GPT-4, and Gemini Ultra can engage consistently in multi-turn conversations, write short computer programs, translate between multiple languages, score highly on university entrance exams, and summarise long documents.
This step-change in capabilities, and the potential for continued progress, could help advance the public interest in many ways. Among the most promising prospects are AI’s potential for education, medical applications, research advances in a wide range of fields, and increased innovation leading to increased prosperity. This rapid progress has also increased awareness of the current harms and potential future risks associated with the most capable types of AI.