http://confocal-microscopy-list.275.s1.nabble.com/Digital-imaging-ethics-as-pertaining-to-the-enhancement-of-microscopy-images-with-artificial-intellie-tp7588915p7588931.html
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>
> John,
>
> You forgot this clip:
>
https://www.youtube.com/watch?v=WwnI0RS6J5A>
> Phil
> -------------
> Philip Oshel
> Imaging Facility Director
> Biology Department
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> -----Original Message-----
> From: Confocal Microscopy List <
[hidden email]> on
> behalf of John Oreopoulos <
[hidden email]>
> Reply-To: Confocal Microscopy List <
[hidden email]>
> Date: Friday, 16November, 2018 at 21:33
> To: "
[hidden email]" <
[hidden email]>
> Subject: Digital imaging ethics as pertaining to the enhancement of
> microscopy images with artificial intelligence
>
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> To join, leave or search the confocal microscopy listserv, go to:
>
http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy> Post images on
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> posting.
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>
> Earlier today a few people (including myself) brought up Doug Cromey's
> excellent treatise on digital imaging ethics in a related thread that dealt
> with training new microscope users within a research setting. Lately I've
> been hearing a lot about applications of machine learning and artificial
> intelligence to "improve", "de-noise", or "fix" images (microscopy or
> otherwise), extracting new information from low-resolution images, and even
> creating new 3D views of samples with very little information. Here is just
> one such example from Nvidia and MIT:
>
>
>
https://news.developer.nvidia.com/ai-can-now-fix-your-grainy-photos-by-only-looking-at-grainy-photos/>
>
https://www.youtube.com/watch?time_continue=84&v=pp7HdI0-MIo>
> It's clear that the microscopy world will eventually come to a head
> with this technology. I think I've seen a few research articles on this
> topic now, and this month's issue of Nature Methods has a paper on this
> topic too:
>
>
https://www.nature.com/articles/s41592-018-0194-9>
> I've been wondering if and how Cromey's guide for digital imaging
> ethics should be altered when it comes to AI-assisted microscope imaging.
> Should it be allowed/accepted? Other readings of mine on AI show that
> machine learning algorithms can produce biased results if the training
> datasets are incomplete in some way, and the very nature of machine
> learning makes it difficult to understand why it produced a certain result,
> since the deep learning neural networks that are used to generate the
> results are essentially black boxes that can't easily be probed. But on the
> other hand, I'm constantly blown away by what I've seen so far online for
> other various applications of AI (facial recognition, translation, etc.).
>
> I also just finished a good read about AI from the perspective of
> economics:
>
>
https://www.predictionmachines.ai/>
>
https://youtu.be/5G0PbwtiMJk>
> The basic message of this book is that AI makes prediction cheap. When
> something is cheap, we use more of it. Other processes that complement
> prediction, like judgement (by a human or otherwise) becomes more valuable.
> It's easy to see how the lessons of this book could be re-framed for
> imaging science.
>
> Curious to know the community's opinion on this matter. I used to
> laugh at the following video, but now I'm not laughing:
>
>
https://www.youtube.com/watch?v=LhF_56SxrGk>
> John Oreopoulos
>
>
>