14How do you handle copyright and IP risk with generative AI (training data and outputs)?▼mediumOpenAIGoogleMicrosoft1 replies○ sign inCopyright is among the largest unresolved risks in generative AI, on both the training and output side. What lands is naming both exposures and the engineering mitigations for each rather than offering a legal opinion. Here is the engineer's framing.Open full answer →
16How do you watermark AI-generated content and establish provenance (e.g. against deepfakes)?▼mediumGoogleOpenAIAdobe1 replies○ sign inAs generated output grows indistinguishable from real, knowing what is AI-made matters for trust, misinformation, and regulation. What lands is the split between in-content watermarks and attached provenance metadata, plus the fact that detection is an arms race. Here is the answer.Open full answer →
32What are the supply-chain risks in AI (models, data, dependencies), and how do you manage them?▼mediumGoogleMicrosoftAnthropic1 replies◆ premiumEvery third-party model, dataset, and library widens the attack surface: backdoors, poisoning, arbitrary code on load, license landmines. The signal is treating models and data as supply-chain artifacts that need provenance and vetting. Here is the answer.Open full answer →
