Some of the reasoning:
>Preliminary assessment also suggests Imagen encodes several social biases and stereotypes, including an overall bias towards generating images of people with lighter skin tones and a tendency for images portraying different professions to align with Western gender stereotypes. Finally, even when we focus generations away from people, our preliminary analysis indicates Imagen encodes a range of social and cultural biases when generating images of activities, events, and objects. We aim to make progress on several of these open challenges and limitations in future work.
Really sad that breakthrough technologies are going to be withheld due to our inability to cope with the results.
Maybe that's a nice thing, I wouldn't say their values are wrong but let's call a spade a spade.
For example, Google's image search results pre-tweaking had some interesting thoughts on what constitutes a professional hairstyle, and that searches for "men" and "women" should only return light-skinned people: https://www.theguardian.com/technology/2016/apr/08/does-goog...
Does that reflect reality? No.
(I suspect there are also mostly unstated but very real concerns about these being used as child pornography, revenge porn, "show my ex brutally murdered" etc. generators.)
Nowhere there is any precision for a preferred skin color in the query of th user.
So it sorts and gives the most average examples based on the examples that were found on the internet.
Essentially answering the query "SELECT * FROM `non-professional hairstyles` ORDER BY score DESC LIMIT 10".
It's like if you search on Google "best place for wedding night".
You may get 3 places out of 10 in Santorini, Greece.
Yes you could have an human remove these biases because you feel that Sri Lanka is the best place for a wedding, but what if there is a consensus that Santorini is really the most appraised in the forums or websites that were crawled by Google ?