Confocal Microscopy List - Re: Digital imaging ethics as pertaining to the enhancement of microscopy images with artificial intelligence

Re: Digital imaging ethics as pertaining to the enhancement of microscopy images with artificial intelligence

Posted by Oshel, Philip Eugene on
URL: http://confocal-microscopy-list.275.s1.nabble.com/Digital-imaging-ethics-as-pertaining-to-the-enhancement-of-microscopy-images-with-artificial-intellie-tp7588915p7588932.html

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Good reference, thanks!

Note: I would like to publish an article (or two) on this issue in Microscopy Today. If someone has something they'd like to contribute, please contact me.

Phil
P.S. The clip was from Futurama.
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Philip Oshel
Technical Editor, Microscopy Today
Imaging Facility Director
Biology Department
1304 Biosciences
1455 Calumet Ct.
Central Michigan University
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-----Original Message-----
From: Confocal Microscopy List <[hidden email]> on behalf of Jason Swedlow <[hidden email]>
Reply-To: Confocal Microscopy List <[hidden email]>
Date: Monday, 19November, 2018 at 19:16
To: "[hidden email]" <[hidden email]>
Subject: Re: Digital imaging ethics as pertaining to the enhancement of microscopy images with artificial intelligence

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Hi All-

On a more serious note (although any comment that cites The Simpsons is an
excellent one), see https://www.nature.com/articles/s41592-018-0195-8 for
an update and proposal for image data publication resources.

Cheers,

Jason

On Mon, Nov 19, 2018 at 7:25 PM Oshel, Philip Eugene <[hidden email]>
wrote:

> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> Post images on http://www.imgur.com and include the link in your posting.
> *****
>
> John,
>
> You forgot this clip:
> https://www.youtube.com/watch?v=WwnI0RS6J5A
>
> Phil
> -------------
> Philip Oshel
> Imaging Facility Director
> Biology Department
> 1304 Biosciences
> 1455 Calumet Ct.
> Central Michigan University
> Mt. Pleasant, MI 48859
> 989 774-3576 office
> 989 774-7567 lab
>
> -----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
>
> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> Post images on http://www.imgur.com and include the link in your
> posting.
> *****
>
> 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
>
>
>

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