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It's not a totally lost cause — I wrote a piece on what we can do about this: https://www.washingtonpost.com/news/theworldpost/wp/2018/02/22/digital-reality/ ht

by avivo 8y ago

It's not a totally lost cause — I wrote a piece on what we can do about this: https://www.washingtonpost.com/news/theworldpost/wp/2018/02/22/digital-reality/ https://www.washingtonpost.com/news/theworldpost/wp/2018/02/... It's a first step, and my thinking has also evolved since—expect more updates in this space soon.

majos 8y ago
From this article: > AI researchers and platform technologists need similar in-house or third-party societal impact review boards to help them evaluate the potential unintended consequences of their work. As a machine learning researcher myself (albeit one who is probably unlikely to run afoul of one of these boards), this suggestion for research gives me pause. In the context of deepfakes, are you suggesting that it would have been more prudent to stop the research that made it possible before it had a chance to do so? This seems like a good way to ensure that less scrupulous parties harness destructive technologies before more scrupulous parties (the kind who'd adopt review boards). I imagine this debate to some extent has already played out with nuclear weapons and bioweapons. I'm much less familiar with these two spheres, but as I recall research continued in both.
- avivo 8y ago
  Lots of details to be worked out, but yes there are models in other fields. You bring up a real concern and there are ways to address it. I'm not suggesting stopping research on this. But the way in which that research is communicated, what the focus is, and the way which particular sorts of replication is enabled or discouraged has an impact. An example that the HN crowd likely knows better is vulnerability/exploit disclosure. There are good ways to do it and harmful ways to do it. You can perhaps think about deepfakes as an exploit for the human sensors/cognition that handle authentication.

by avivo 8y ago

majos 8y ago

From this article: > AI researchers and platform technologists need similar in-house or third-party societal impact review boards to help them evaluate the potential unintended consequences of their work. As a machine learning researcher myself (albeit one who is probably unlikely to run afoul of one of these boards), this suggestion for research gives me pause. In the context of deepfakes, are you suggesting that it would have been more prudent to stop the research that made it possible before it had a chance to do so? This seems like a good way to ensure that less scrupulous parties harness destructive technologies before more scrupulous parties (the kind who'd adopt review boards). I imagine this debate to some extent has already played out with nuclear weapons and bioweapons. I'm much less familiar with these two spheres, but as I recall research continued in both.

avivo 8y ago
Lots of details to be worked out, but yes there are models in other fields. You bring up a real concern and there are ways to address it. I'm not suggesting stopping research on this. But the way in which that research is communicated, what the focus is, and the way which particular sorts of replication is enabled or discouraged has an impact. An example that the HN crowd likely knows better is vulnerability/exploit disclosure. There are good ways to do it and harmful ways to do it. You can perhaps think about deepfakes as an exploit for the human sensors/cognition that handle authentication.