On 2007-04-06 08:28:00, Allan Engelhardt wrote in CYBAEA Journal:
The Post-GUI era
. I like the expression and I think what it tries to encapsulate is important.
I am back from O’Reilly’s 2007 Emerging Technologies conference. The recurring theme of the conference, at least to my mind, was this: as technology becomes ubiquitous we need to think much harder about how technology interfaces with humans.
You are probably reading this using a computer with a graphical user interface (GUI), i.e. on a screen that uses windows with pictures and text to represent the content and a keyboard and mouse as the input and control elements.
However, when everything has a microprocessor embedded, when everything is a computer, this is not necessarily the best interface. Your microwave oven probably does not have a GUI and it almost certainly shouldn’t have one, despite the fact that it already has significant computing power.
We need new metaphors for user interfaces. The GUI is still for mostly for technically minded people and technical applications, but if computing is to truly become ubiquitous then we need more human, less technical ways of interacting with the technology objects. Casting the technology-savvy “experts” in the role of wizards, Danah Boyd talked about Incantations for Muggles where “muggles” are (apparently) the people without magical powers in the Harry Potter books. How do we make the magic of technology available to the non-magical people?
Magic is one metaphor for how to think about new interfaces, but perhaps a dangerous one. Magic is often hard to understand, hard to learn, and hard to generalize. Maybe ritual religion would be better, but ultimately metaphors are just that and are always going to come with their own problems.
Or how about animism? Humans have always attributed sentience and agency to the external world. The idea that the world is alive, that the objects therein are sentient and can be transacted with, is old and deep and so common to all the cultures of humanity that it may as well be called universal
. Until recently, the world was a place of spirits and the places and objects in the external world were identical with these spirits. Can we re-capture and re-purpose this way of modeling the world which seems to be hard-wired into the human brain to a future where all things indeed are if not completely sentient (artificial intelligence still being a hard problem) then at least behaves as if they are and certainly have agency and purpose and the ability to react to our interactions?
Several speakers talked about games as generally useful metaphors. Games are fun, and fun is good, fun works, to mis-quote a popular 1980-ies movie. Games provide feedback on how you are doing. Games provide challenges that are difficult but not impossible. Games allow you to visibly grow in skill and experience. Games are risky. All of this makes for a fun experience for humans. It is a useful exercise to think about what that would mean for your web site.
The world already has an interface, and it isn’t a GUI. We should learn from that.
Two other sessions were particularly interesting: a Birds-of-Feather session with Nilofer Merchant and a couple of presentations from Jeff Jonas on data mining and in particular data mining of anonymized data, but they probably deserve their own entries. Missing out on Kathy Sierra's presentations was a big disappointment.
On 2010-07-13 07:47:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
I am not sure apeescape’s ggplot2 area plot with intensity colouring is really the best way of presenting the information, but it had me intrigued enough to replicate it using base R graphics.
The key technique is to draw a gradient line which R does not support natively so we have to roll our own code for that. Unfortunately, lines(..., type="l") does not recycle the colour col= argument, so we end up with rather more loops than I thought would be necessary.
We also get a nice opportunity to use the under-appreciated read.fwf function.
Read more (~535 words).
On 2010-06-22 11:45:00, Allan Engelhardt wrote in CYBAEA Journal:
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is scary.
We now re-do the analysis four years later and, just because we can, we are using the leading companies of the London stock exchange instead of the largest American companies.
The results still hold. We called it the 3/2 rule: treble the number of workers and you halve their individual productivity. Large companies with ten times the number of employees are ¼ as productive as their smaller competitors.
Employee productivity is a big issue. If all the FTSE-100 companies achieved their average profits per employee, then the index would generate almost £1 trn of additional net profits for the economy.
Read more (~245 words).
On 2010-06-22 11:20:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is mildly scary.
We revisit the analysis for the FTSE-100 constituent companies and find that the relation still holds four years later and across a continent.
Read more (~763 words, 5 comments).
On 2010-06-17 09:05:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
Following on from my previous post about improving performance of R by linking with optimized linear algebra libraries, I thought it would be useful to try out the five benchmarks Revolutions Analytics have on their Revolutionary Performance pages.
Read more (~300 words, 2 comments).
On 2010-06-15 10:21:00, Allan Engelhardt wrote in CYBAEA Data and Analysis:
Can we make our analysis using the R statistical computing and analysis platform run faster? Usually the answer is yes, and the best way is to improve your algorithm and variable selection.
But recently David Smith was suggesting that a big benefit of their (commercial) version of R was that it was linked to a to a better linear algebra library. So I decided to investigate.
The quick summary is that it only really makes a difference for fairly artificial benchmark tests. For “normal” work you are unlikely to see a difference most of the time.
Read more (~934 words, 1 comments).
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