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privacy

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first_img The Bank for International Settlements released the second phase report of the digital cash project Aurum, exploring privacy-enhancing technologies

On October 13, 2026, the Bank for International Settlements Innovation Hub released the second phase report of the Aurum project, themed "Exploring Privacy-Enhancing Technologies for Digital Cash." This phase implements a privacy-protecting digital cash prototype based on the existing Aurum codebase, helping policymakers understand how relevant technologies can alleviate the dilemma between privacy and compliance in digital cash.The prototype adopts the principles of privacy by design and default privacy, demonstrating practices that lie between complete anonymity and complete transaction transparency, and achieving customizable features to meet business needs in compliance and operations. The project indicates that privacy can be embedded in the design of digital cash through technology, rather than solely relying on institutional guarantees, thereby reducing unnecessary exposure of personal and transaction data while maintaining compliance and system integrity.Privacy-protecting designs can assist central banks and policymakers in understanding the relevant considerations and trade-offs. The prototype's functionalities demonstrate policy flexibility between privacy, transparency, compliance, and other attributes, which can be calibrated according to different policy choices and risk preferences. In addition to digital cash, central banks can further explore privacy-enhancing technologies in more use cases, with the report listing several usage experiences.

first_img Privacy Infrastructure Hinkal Joins Mastercard Crypto Partner Program

Privacy infrastructure Hinkal announced on October 9, 2026, its participation in the Mastercard Crypto Partner Program. This program connects crypto and blockchain teams, Mastercard teams, and its global payment network, with members including stablecoin issuers, infrastructure providers, fiat exchange service providers, crypto card supporters, and blockchain and blockchain service providers. Mastercard positions it as a way to transform technological capabilities into compliant use cases for global commerce; some members can also access financial institutions within the card issuing and acquiring networks and receive regulatory and compliance support aligned with global standards.Related use cases include cross-border payments and remittances, B2B transactions, fund and settlement flows, stablecoin payments, and card projects that allow users to spend digital assets at regular merchants. Hinkal can provide embeddable privacy capabilities for wallets, payment platforms, and chains, allowing stablecoins to settle in private balances and transfer using zero-knowledge proofs, ensuring that the amount, sender, or receiver is not disclosed during on-chain transfer verification. This capability is already live on Ethereum, Polygon, Solana, TRON, and other major EVM chains, accessible via SDK and API.Existing integrations include Private Send in Polygon Wallet, Hinkal Private Send in the Tether wallet development kit, Turnkey wallets that can enhance privacy features through Hinkal SDK, and Avvio running Hinkal private payments on its own interface.

NEAR co-creation sharing ecological application construction direction and distribution suggestions, covering AI, cross-chain payment, and privacy transactions, among other directions

Illia Polosukhin, co-founder of NEAR, stated that recently the activity of developers within the ecosystem has increased and the development threshold has further lowered, focusing on what kind of applications to build and how to establish distribution channels.In this regard, he proposed a series of potential construction directions, covering AI electronic pets that combine NEAR AI on-chain verifiable reasoning with non-fungible tokens (NFTs), a universal checkout component that supports full-chain intent payments, a decentralized encyclopedia that combines prediction markets with AI-generated content, a privacy off-chain trading (OTC) market based on NEAR Intents and management of anti-liquidation lending and perpetual contracts, a cross-chain activity registration custody tool in the form of a staking deposit, privacy code review agents, enterprise equity structure management tools, Delta neutral strategy management, privacy tracking single transactions based on view keys, end-to-end encrypted medical auxiliary diagnostic systems, privacy voice transcription desktop applications, and AI benchmarking based on private test sets.Regarding product distribution, he suggested combining NEARLegion with community channels like X, achieving multi-chain wallet compatibility through Aurora Intent Connect to lower cross-chain thresholds, and actively expanding across communities and platforms like Product Hunt.

first_img OpenAI is facing a class-action lawsuit, accused of allowing outsourced personnel to read ChatGPT conversations

Two ChatGPT users from California filed a proposed class action lawsuit against OpenAI in the United States District Court for the Northern District of California this month, accusing the company of failing to adequately inform users that their real conversations were being handed over to external contractors for processing. The lawsuit was served to OpenAI on September 2, focusing on its internal initiative Project Lily. According to the complaint, "AI data reviewers" and "chatbot evaluators" recruited through a third-party staffing company read real ChatGPT prompts and complete conversations, summarize user intent, and score and comment on responses from four models on a scale of 1 to 7.This process is known in the industry as reinforcement learning from human feedback (RLHF), which is a fundamental method for enhancing chatbot capabilities. The complaint states that users were never explicitly informed that a person, rather than a machine, might be reading their conversations. OpenAI filters conversations through an automated system before human review, but the complaint alleges that the filters cannot intercept all content, and personal details sometimes still reach contractors. 404 Media first reported on the project on September 14 and found that the reviewers' dashboard included "user memory summaries," which could expose users' approximate locations, occupations, or private life information, even though usernames had been removed.OpenAI stated that such reviews aim to reduce two behaviors: chatbots behaving too much like humans and overly catering to users, referred to by researchers as "flattery." The complaint raises eight legal claims, including violations of California's Unfair Competition Law, Consumer Privacy Act, and common law claims for intrusion into private affairs, with the plaintiffs seeking damages, restitution of unjust enrichment, and punitive damages.
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