CreativeVerse: The House with Two Minds
A CreativeVerse story—and practical design reflection—about a home that separates local intelligence from optional cloud capability and makes privacy boundaries visible.
Category: AI Ethics
ENISA’s 2026 Threat Landscape: Your SaaS Stack Is Part of Your Attack Surface
What ENISA’s 2026 cyber findings mean for small digital businesses: map SaaS and AI dependencies, narrow access and prove recovery before disruption.
AI Labels Should Explain the Human Contribution
A binary AI-generated label can hide the person who supplied the idea, judgement and final responsibility. Use a contribution record that shows how human and machine work combined.
Consent Must Travel With the Data: A Rule for AI Personalisation
Responsible AI personalisation requires consent, purpose and revocation to travel with data as it moves from collection to inference and action.
OpenAI’s Misalignment Reporting Framework Signals a New Phase for AI Safety
OpenAI has introduced a framework for investigating and reporting model misalignment, raising an important question about how AI incidents should be documented.
Do Not Give an AI Agent the Keys to Everything: Build a Permission Budget
An AI agent needs enough access to finish its task—not your whole digital life. Build a permission budget with limits, approvals, logs and rapid revocation.
Small Business AI Governance: A Simple Policy That Works
Create a practical AI policy for your small business covering privacy, accuracy, human review, approved tools and accountability.
Why Do Some People Feel More Heard by AI? New UK–China Research Examines the Psychology of Listening
A new cultural case study from Cambridge and SOAS examines how a Chinese migrant woman living across China and the UK used generative AI for emotional support. The paper argues that AI may sometimes function as a temporary “care-patch” where human listening feels scarce, delayed or burdensome.
The AI Mirror: Effects Analysis Framework, AI Regulation and the Human Signals Behind the Machine
Mary Oge Chuks introduces the Effects Analysis Framework (EAF), a psychological and systems-based method for analysing AI through signals, observable effects, framing shifts and institutional outcomes — and asks why humanity regulates the reflection without examining the signals it feeds into the mirror.
Give Your AI Agent a Budget for Decisions
Set clear limits for AI agents: define what they may decide, when they must stop and how people can review the actions they take.