miércoles, 13 de enero de 2016

MercatorNet: Which diversity matters (if any)? || MercatorNet

Which diversity matters (if any)?

Why do academics fret about racial diversity, but not diversity of thinking?
J. Budziszewski | Jan 13 2016 | comment 1 

Julie R. Posselt, an assistant professor in the Center for the Study of Higher and Postsecondary Education at the University of Michigan, has written a new book, Inside Graduate Admissions: Merit, Diversity, and Faculty Gatekeeping, about what she observed after obtaining permission to sit in during the meetings of the graduate admissions committees of six highly-ranked departments at three research universities and interview some of their members.
I haven’t yet read the book, but it sounds interesting. One of Professor Posselt’s themes is widespread discrimination in admission in favor of everyone but East Asians, against East Asians. I don’t know whether the author herself is upset about this, but some of the reviewers are; they seem to view it as a blow against “diversity.” That’s nonsense, of course.
In my experience, the professors on graduate admissions committees really do believe that they should admit grad students of many different ethnicities and colors, and that’s why they discriminate against Asians. They don’t want lower-scoring non-Asians to be squeezed out.
I am against double standards too, but for a different reason: merit. If Asians dominate college admissions so that non-Asians are squeezed out, so be it. Maybe it will motivate non-Asians to work harder.
The one kind of diversity that does have some claim to consideration in admissions is diversity of thought. However, this is the sort of diversity that professors don’t believe in.

One of Posselt’s anecdotes is most revealing. Admissions committees give enormous weight to GRE scores, and the applicant under consideration certainly looked good by that criterion. The committee also acknowledged that her personal statement reflected the capacity for rigorous independent thought. However, she came from a small religious college. One committee member complained that its faculty were “right-wing religious fundamentalists.” Another joked that the school was “supported by the Koch brothers.” The committee chair said “I would like to beat that college out of her” and asked whether she was a “nutcase.” She wasn’t rejected during that round, but she was during the next.
I have found this sort of thing to be all too typical. It may seem bizarre that even though the members of the committee were being observed, they made no effort to conceal their malice against religion. But this is easy to explain. A great many university liberal arts professors view religion as the very definition of bigotry, and dogmatic rejection of faith as the very definition of open-mindedness. It would never occur to most of them that they might seem narrow-minded to an observer. The notion of a bigoted secularist would seem to them a strange paradox.
That is why when religious students write to me for advice about getting into grad school, I tell them "don’t mention your faith". They can’t be saved from battles, and shouldn’t be; but with luck, the battles can be delayed until they get their foot in the door. Then cry reason and let slip the dogs of argument.
J. Budziszewski, a Professor in the Departments of Government and Philosophy, University of Texas at Austin. This article is reproduced with permission from his blog, The Underground Thomist
- See more at: http://www.mercatornet.com/articles/view/which-diversity-matters-if-any/17444#sthash.4Qnq9JIl.dpuf

Why you’ll never be able to upload your brain to the cloud

The complexity of the brain is unbelievably immense.
Nicolas P. Rougier | Jan 13 2016 | comment 1 

In the first article in this series, we saw how the mind and body literally cannot be separated, and also why robotics isn’t capable of replicating either one.
But let’s assume that we’ve solved the problems of sensors and muscles and all the rest, and accept that the uploaded brain won’t truly reflect our mind. Now comes the big challenge: uploading the brain. But what is a brain exactly? This term usually refers to the cortex and possibly some subcortical structures, including the amygdala, hippocampus and basal ganglia. But the central nervous system is actually made of several other structures that are no less critical, including the cerebellum, thalamus, hypothalamus, medulla and brain stem.
Making the connections  
If we consider the whole central nervous system, we are facing an average of 86 billion neurons, and each of these neurons contacts an average of 10,000 other neurons, representing a grand total of approximately 860 billion connections. This is really huge. So exactly what do we have to upload into the computer? The type, the size and the geometry of each neuron? Its current membrane potential? The size and position of the axon and its state of myelination? The complete geometry of the dendritic tree? The location of the various ion pumps? The number, the position and the state of the different neuro-mediators? Any of these could be critical, and they can only be taken into account in state-of-the-art computer models (and for a few neurons only). The problem is that we do not know exactly what it is that makes us who we are and different from anyone else (and I’m not even talking about learning).
As a fallback – and only if we had the proper tools to record each of these parameters once – we could try to transfer everything. However, this would require potentially some thousands or even millions of pieces of information for a single neuron. If you consider just the number of neurons, we would reach a figure in the zetta domain (for your information, the order is kilo, mega, giga, tera, peta, exa and zetta, multiplying by 1,000 at each step). This number is so huge that it cannot yet be manipulated as a whole by computer science. And we are talking only about the brain’s storage, because we also have to ensure that this model runs in real time, since nobody would happily accept a silicon mind that runs at reduced speed. From a purely technical perspective, we are thus very far (really very far) from making this to happen.
Worse, research indicates that Moore’s Law – which suggests that computer power doubles every 18 months – is reaching its limits, suggesting that we may never attain the necessary level of technology. The Human Brain Project foresaw this problem and planned from the beginning to use only simplified models of neurons and synapses. If you’re interested in more accurate models, take a look at the OpenWorm project, which doesn’t pretend to simulate any more than a few neurons.
The bird in the machine  
This idea of transferring one’s brain into a machine is widespread in both literature and cinema. It has gained renewed interest with recent advances in artificial intelligence. However, there may be some confusion regarding what is actually artificial intelligence (AI) and what are its goals.
When media cover artificial intelligence, they generally refer to machine learning and robotics, neither of which really seeks to understand the brain or cognition (with some notable exceptions, such as the work of Pierre-Yves Oudeyer). This confusion likely stems from the fact that new algorithms have been designed that enable excellent performance on tasks that were previously thought to be reserved for humans – recognizing images, driving a car and so on.
But if machine learning and robotics are progressing at an amazing speed, this does not tell us anything about how the biological brain works (at least not directly). If we want to know, we have to look at neuroscience and more specifically at computational neuroscience. A parallel could be drawn between aeronautics (AI) and ornithology (neuroscience). Even though the early attempts at flying were directly inspired by the flight of birds, this was abandoned long ago in favor of the design of ever more efficient aircraft (speed, payload, etc) using techniques specific to aeronautics. To better understand birds, you must turn to ornithology and biology. Hence, talking about uploading a brain to a computer because of the progress of AI makes as much sense as gluing feathers on an airplane and pretending it’s an artificial bird.
No one knows if it will ever be possible to “upload a brain to a computer.” But what is certain today is that in the current state of science, this statement makes no sense and will remain so without a major epistemological breakthrough in our understanding of the brain and how it works.
Nicolas P. Rougier, Chargé de Recherche, Inria. This article was originally published on The Conversation. Read the original article
- See more at: http://www.mercatornet.com/articles/view/why-youll-never-be-able-to-upload-your-brain-to-the-cloud/17441#sthash.mkACMxrw.dpuf


The sex attacks in Cologne on New Year's Eve seemed like something completely new -- until this week when it turned out that the same sort of thing had happened in another European city nearly six months ago. Only no-one wanted to talk about it. My piece today looks at the wider picture in which official reactions to these events makes sense -- at the expense of women.

Carolyn Moynihan
Deputy Editor,
Was there anything really new about the New Year’s Eve attacks in Cologne?
Carolyn Moynihan | FEATURES | 13 January 2016
Not if you look at the big picture of sexual crimes.
Why you’ll never be able to upload your brain to the cloud
Nicolas P. Rougier | FEATURES | 13 January 2016
The complexity of the brain is unbelievably immense.
Which diversity matters (if any)?
J. Budziszewski | FEATURES | 13 January 2016
Why do academics fret about racial diversity, but not diversity of thinking?
Will Japan bow to immigration pressure?
Shannon Roberts | DEMOGRAPHY IS DESTINY | 13 January 2016
Other solutions to its shrinking population seem hard to find.
This book was a terrible disappointment
Jennifer Minicus | READING MATTERS | 13 January 2016
I could not force myself to finish it.
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