[Nov 15th Event] Margaret Mitchell: On Values in ML Development
Use this topic to ask your questions to Margaret Mitchell during her talk:On Values in ML Development.You can watch it onYouTubeor onTwitchat 9:30am PST
2021-11-15T17:35:48Z
How could we balance the filtering of bias between freedom of speech and offensive/biased content?
2021-11-15T17:37:32Z
And also to what extent we can do it.
2021-11-15T17:37:42Z
How do we protect against machine learning systems designed primarily without ethics in mind?How do we push for adaptation of more ethical datasets (Not Imagenet. CC4 or LAION, for example) in major conferences?What about retraining models that are already trained on unethical data?P.S. If making jokes reflects poorly, I will take that all day, everyday. More power to you, Margaret! Keep doing all the good work
2021-11-15T17:42:17Z
If a model could be fine-tuned for human values, couldn’t it be fine-tuned for anti-values in the same way?
2021-11-15T17:44:39Z
what’s the easiest way to determine whether a text generation model is not racist or sexist? And how do we solve this quickly without losing too much training data?
2021-11-15T17:44:52Z
Model transparency seems to be a precondition of the mentioned ethical goals. Dr. Mitchell seems to emphasize the role of input data. Isn’t the model’s way of decision-making equally important (feature importance etc.) for ethical AI?
2021-11-15T17:47:30Z
shamikbose89:How do we push for adaptation of more ethical datasets (Not Imagenet. CC4 or LAION, for example) in major conferences?This is answered at 1:44:40 in the main stream.
2021-11-15T17:48:03Z
When Dr. Mitchell was talking about loss functions and what they emphasize or optimize for, I believe this was what was being talked about
2021-11-15T17:49:00Z
While training the pretrained models, is it possible to add a step including debiasing algorithms (there are emerging algorithms today), could this make some intrinsic bias disappear?
2021-11-15T17:59:28Z
What does the regular day-to-day work look like for you?
2021-11-15T17:59:38Z
Is making it mandatory and forcing to create datasets where each participant is highly paid going to put a lot of pressure on researchers from low-resource institutions and researchers from low-resource countries?
2021-11-15T18:07:28Z
about  False Positive vs False Negative):  I think that that the choice should match the goal of our Model or application. For example if it is about coronvirus or other task of medical diagnosis, The Goal is to detect the maximum of positive cases (having the illness), in this case we should focus on False Neagtive (False Positive doesn’t matter, even if the model predcit healthy subjects as ill: it is not very dangerous). but if it is about detecting credit card frauds(for example): yes,we should focus on the False Positive (because we must be careful not to calssify a non-fraudulent(negative) case as fraudulent(positive)).
2021-11-15T18:12:07Z
tceron:How could we balance the filtering of bias between freedom of speech and offensive/biased content?This is answered at 2:04:20 in the main stream.
2021-11-15T18:12:33Z
NDugar:what’s the easiest way to determine whether a text generation model is not racist or sexist? And how do we solve this quickly without losing too much training data?This is answered at 2:02:25 of the main stream.
2021-11-15T18:12:57Z
shamikbose89:How do we protect against machine learning systems designed primarily without ethics in mind?This is answered at 1:56:35 of the main stream.
2021-11-15T18:13:22Z
sebabruch:Model transparency seems to be a precondition of the mentioned ethical goals. Dr. Mitchell seems to emphasize the role of input data. Isn’t the model’s way of decision-making equally important (feature importance etc.) for ethical AI?This is answered at 1:57:55 of the main stream.
2021-11-15T18:13:54Z
shamikbose89:What about retraining models that are already trained on unethical data?This is answered at 1:59:00 of the main stream.
2021-11-15T18:14:19Z
Abirate:While training the pretrained models, is it possible to add a step including debiasing algorithms (there are emerging algorithms today), could this make some intrinsic bias disappear?This is answered at 2:00:10 of the main stream.
2021-11-15T18:14:52Z
NDugar:What does the regular day-to-day work look like for you?This is answered at 2:08:32 of the main stream.
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