Extension usage examples:
Here's how our browser extension sees the article:
How to create, release and share generative AI responsibly | MIT Technology Review
Source: technologyreview.com
Article summary:
1. A group of 10 companies have signed up to a new set of guidelines on how to build, create, and share AI-generated content responsibly.
2. The recommendations call for transparency about what the technology can and cannot do, and disclosure when people might be interacting with this type of content.
3. Regulation attempting to rein in potential harms relating to generative AI is still lagging behind, but these guidelines offer companies key things they need to look out for as they incorporate the technology into their businesses.
Article analysis:
The article is generally trustworthy and reliable, as it provides an overview of the new set of guidelines put together by the Partnership on AI (PAI) in consultation with over 50 organizations. It also provides insights into the implications of these guidelines for both builders and creators/distributors of digitally created synthetic media, such as OpenAI, TikTok, Adobe, BBC, etc., including transparency about what the technology can and cannot do and disclosure when people might be interacting with this type of content.
However, there are some potential biases that should be noted in the article. For example, while it mentions that regulation attempting to rein in potential harms relating to generative AI is still lagging behind, it does not provide any details or evidence regarding why this is so or what steps could be taken to address this issue. Additionally, while it mentions that watermarks on all AI-generated content should be mandated rather than voluntary, it does not explore any counterarguments or provide any evidence for why this should be done.
Furthermore, while the article does mention some possible risks associated with generative AI (such as fraud and disinformation), it does not provide any details or evidence regarding how these risks could be addressed or mitigated. Additionally, while it mentions that there should be more details on how AI models are trained and whether they have any biases, it does not provide any evidence or examples of how this could be done effectively.
Finally, while the article does mention that companies such as OpenAI can try to put guardrails on technologies they create (such as ChatGPT and DALL-E), it does not explore other players who are not part of the pact (such as Stability.AI) who may let people generate inappropriate images and deepfakes without any guardrails in place.
In conclusion, while overall trustworthy and reliable due to its overview of PAI's new set