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AIs content-creation capabilities have skyrocketed in the last year, yet the act of writing remains incredibly personal.
But on its own, this isnt enough to make a model safe.
What if a model produces content that is entirely innocuous in isolation but becomes offensive in particular contexts?
As AI developers, its not enough for us to block toxic language to claim our models are safe.
Responsible AI team, Grammarly.
And we know that AI makes mistakes.
This gets more complicated as technology advances and as developers rely more on LLMs.
The stakes of inappropriate outputs are much higher, with harmless errors no longer the only outcome.
Product builders can follow these three principles to hold themselves accountable:
1.
These principles can guide the industry’s work and commitment to developing publicly available models like Seismograph.
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