AI Guardrails by Zapier Gives Teams Inline Safety Checks for Every AI-Powered Workflow - citybiz
<a href="https://news.google.com/rss/articles/CBMiwwFBVV95cUxQYnF4UHY5NkdscDd5b1VsOUhCLXpOd2Zjdy16YW93NkxRVXdRV1FiazdEaDFwMXVXSnRLYWltSGpoNkZQRHpyRGpUZGo2UVdaQXJPeVptWU9HTFd6Y203dmNhX3dvcGF5cnppQ2M4T1M0VWtPZnlUYThCUXh2cHVQUDNBX0wwbkRwR0c2YkZhTWhHSHY2b1hQS1ZDdXdRbm9adGdHYTZuQjNDN255Z2s4ZHdwRkRJUmpNRENzd29aM3NjSEE?oc=5" target="_blank">AI Guardrails by Zapier Gives Teams Inline Safety Checks for Every AI-Powered Workflow</a> <font color="#6f6f6f">citybiz</font>
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safetyWorker Discretion Advised: Co-designing Risk Disclosure in Crowdsourced Responsible AI (RAI) Content Work
arXiv:2509.12140v3 Announce Type: replace Abstract: Responsible AI (RAI) content work, such as annotation, moderation, or red teaming for AI safety, often exposes crowd workers to potentially harmful content. While prior work has underscored the importance of communicating well-being risk to employed content moderators, designing effective disclosure mechanisms for crowd workers while balancing worker protection with the needs of task designers and platforms remains largely unexamined. To address this gap, we conducted individual co-design sessions with 15 task designers, 11 crowdworkers, and 3 platform representatives. We investigated task designer preferences for support in disclosing tasks, worker preferences for receiving risk disclosure warnings, and how platform representatives envis
Autonomous AI systems depend on data governance
Much of the current focus on AI safety has centred on models – how they are trained and monitored. But as systems become more autonomous, attention is changing toward the data those systems depend on. If the data feeding an AI system is fragmented, outdated, or lacks oversight, the system s behaviour can become more unpredictable. [ ] The post Autonomous AI systems depend on data governance appeared first on AI News .
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