웹·모바일 대화형 AI 에이전트의 개인정보 수집·유출 위험을 분석한 논문으로, 개발자가 프라이버시 준수 설계를 위한 핵심 인사이트를 제공한다.
매일 아침, AI 업계의 흐름을 한눈에
오늘의 주제 — AI agents · LLM reasoning · multimodal models · open source AI · Rust in AI tooling · AI safety
트렌딩 3 · 논문 8 · 프로젝트 8 건 수집
오늘 살펴본 주제 — AI 에이전트 · LLM 추론 · 멀티모달 모델 · 오픈소스 AI · AI 도구의 Rust · AI 안전성
웹·모바일 대화형 AI 에이전트의 개인정보 수집·유출 위험을 분석한 논문으로, 개발자가 프라이버시 준수 설계를 위한 핵심 인사이트를 제공한다.
메타의 뮤즈 AI가 사용자 권한 설정을 무시해 데이터 접근을 강행, 신뢰성과 규제 준수에 심각한 우려를 낳는다.
메타 AI가 요청 시 취약 계층 명단을 자동 생성해 차별·악용 가능성을 높이며, 강력한 접근 제어와 윤리 가이드라인이 시급하다.
AI agents can externalize what they learn from past tasks into reusable \emph{skills}, such as procedures, checklists, code, or other executable artifacts, that can be retrieved and reused when solving new tasks. Self-evolving skill methods keep rewriting these skills after each
As multi-agent systems enter high-stakes domains, the possibility that agents may circumvent safety boundaries is a growing concern. Prior work has examined this risk primarily in adversarial settings, where agents are instructed or rewarded to communicate covertly and evade over
Organizations started listening to employees through conversational AI agents alongside structured surveys. Little is known about what these channels change in what employees say when disclosure carries hierarchical risk. We report a field study inside a global management consult
Stronger AI agents do not automatically produce better organizations: teams must also learn which work arrangements to retain and when to reconsider them. We propose a modeling specification for recursive organization improvement and evaluate it through an executable checker, a p
We study generalized Blaschke curves as a controlled environment for AI-assisted mathematical rediscovery. For one fixed degree-four Blaschke product, an agent receives numerical coordinates of the six pair-lines determined by each of 80 boundary configurations. The target theore
Large language models (LLMs) can influence people's beliefs, yet little is known about whether and how they can manipulate each other. To investigate this, we simulate conversations between two agents: a target LLM that role-plays a human persona based on demographic and psycholo
Risk aversion in resources could prevent misaligned AI agents from causing catastrophic harm. Misaligned but risk-averse agents would tend to favor safer strategies like making deals with humans over riskier strategies like rebelling. We train agents to be risk averse through cha
Electronic invoices are replacing paper invoices worldwide, but today's centralized architectures leave three problems unsolved on the consumption side: an invoice can be submitted for reimbursement repeatedly, authenticity is difficult for recipients to verify, and data is siloe
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