The Decision Strategist

Every now and then I hear about some linux distribution and end up switching my install to play with it.  I’ve recently moved to Archlinux, which is a minimalist distribution aimed at installing only the basics and letting you proceed from there.  So now I’m in the process of designing my desktop, and it’s got me thinking about how to most efficiently organize my desktop.

The Design Process

I have to begin by asking myself how I use my computer. From there, does it make sense to have an icon-based desktop (I click icons to start programs) or a menu-based desktop (I click a menu that lists my programs that I select)?  Do I want files on my actual desktop, or is it better if it is kept clean?  Do I want a taskbar?  What kinds of information do I want continually displayed?

Regardless of whether I’m using icons or menus, I usually put the programs I use most often in the easiest place to access.  But I realized that the ease of starting a program shouldn’t be based just on how often I use it, but also on how often I close and restart it during a typical session.

For example, I use a web browser basically every time I start a session.  But I also never close it once it’s open.  So while the number of times that I start the web browser is higher than any other program, the number of times per session is relatively low, and in fact, is basically one.

In contrast, I use the terminal often, but not every session.  However, any session that I do use a terminal typically involves multiple terminals and, rarely, closing terminals and starting another one.  So while my frequency overall is lower than for my web browser, my frequency per session is much higher.  The same goes for quick note takers such as tomboy, or quick text editing such as gedit.

So this time around I am organizing my menu in such a way that a terminal, tomboy, gedit, and maybe firefox are at the top of the menu, while my other programs are buried in the typical sub-menu structure under headings like “office”.  The same most-often used programs will get the key shortcuts, along with a generic “run” box.

Why menus instead of icons?  All of this is happening on my laptop, which has a 14″ screen.  As such, I want to keep the entire desktop available for programs.  If I use icons, then I either have icons on the desktop, so I have to move a program that is covering them before I can start them, or I have icons in a taskbar, which takes up permanent space on the top and/or bottom of the screen.

On the other hand, a menu can be brought up with a click anywhere on the desktop, or with a key shortcut, and allows quick access to any program that I need with either the keyboard or the mouse.

Which actually brings up another point: minimizing the need for a mouse.  Touchpads are abominably slow, and there are times when I don’t have a usb mouse with me.  It’s much easier if I can start a program with several keys than by navigating via touchpad.

Finally, there is the multiple desktops aspect.  My use of additional desktops hasn’t changed much since I started using linux back in my first year of college.  I have one desktop for terminals, one for text, one for web, and one for media.  I think this setup is pretty standard, and using ALT+Left or ALT+Right to switch desktops and CTRL+Left and CTRL+Right to move programs between desktops, it’s very easy to effectively have 4 separate spaces that are very fast to switch between.  I wonder though if there isn’t a better setup for these somehow.  At the very least, the order of the desktops can be important.  I’m often referencing the web when programming, writing, or playing with my distribution, so there is a question of whether the web desktop should be between the terminal and text desktops, or to one side.  I’m not sure what the best answer is.

Of course, a lot of this is heavily dependent on the fact that my work is heavily text-based.  If I was doing graphics work, I may want a different setup.

In addition, whenever I do these distribution change and corresponding desktop redesign phases, there is always a little voice telling me that no matter how much time I save by having a key shortcut to start a terminal and all my other little tricks, it’ll never make up for the 20 hours I spent designing the whole thing.  But then, the design process isn’t entirely utilitarian anyway.  A big part of it’s fun is trying new things and new looks.

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Technology is really about information, and our ability to interact and store information has been making some major changes for the past several decades.

Those of us who are researchers have been blessed in the past several years with an explosion of available information for examining nearly every topic we want to look at.

But at the same time, there has been a shift away from objective analysis toward studies completed by organizations with a vested interest in the outcome.

This has resulted, as noted at Overcoming Bias, in a crisis of faith in the use of statistics. No one believes any numbers that are released because they figure that the people who did the analysis have a hidden agenda. This is the most demoralizing aspect of being an analyst.

The problem is essentially that the analysis process is still closed. We don’t trust the numbers because we don’t know the process that went into obtaining them. Until the process of analysis is opened to a public that can understand and take part in a dialog about the methods, we can continue to write analytical work off as a waste of money and resources because someone else will always have a study saying the opposite.

We need the democratization of data analysis.

And I have high hopes for the future. One of my ideas has been to create an online data warehouse and analysis website, and a few groups such as Swivel and Many Eyes are doing just that.

The services are still fledgling, but in a fairly short time I think we’ll see the ability to perform analysis via the web, and to upload and share data. Hopefully this will result in the standardization of data sets and eliminate the monkey work of downloading a text file and formating it in excel.

I cry when I think how many people have done the very same thing with the very same data.

For a time there will be a lot of confusion, attacks, and some really bad work, but ultimately a community of devoted analysts performing essentially open and peer reviewed work will develop. Because it’s been through trial by fire from all sides of the issue, it will be the most objective approach to messy data analysis that we have ever obtained.

The new analytical hotshots will be the people who have weight with communities at Swivel and Many Eyes and others and are known for doing quality work. These people will engage in very public analysis and will be extremely valuable to everyone wanting analysis that can be seen as objective.

Hopefully that means that shoddy and lazy work will slip to the sides and we can regain confidence in numbers that we see.

I guess it could go the other way. That people don’t want objective analysis and we’ll shun those whose results we can’t know ahead of time. We’ll see even more extreme partisanship.

But that way lies certain death.

-zot, pretending to be a futurist.

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Most of you know by now that the RIAA just won a $220,000 settlement against Jammie Thomas for sharing a slew (thousands?) of music over the Kazaa network. This is (I think) the largest settlement to date and one of the first against someone accused of sharing music instead of just downloading it.

At this point technology and the music market have essentially aligned the RIAA against consumers. I say consumers here because an overwhelming number of people download music. And though the RIAA is winning cases, there are also important precedents being set in cases that it is losing.

RIAA Strategy

The RIAA’s motivation is several years of declining record sales. A problem it views as almost solely caused by the availability of music online (pdf link), but which many people argue is due more to releasing bad music(pdf link). Sales have been declining since at least 2001, but part of me can’t help but wonder if it isn’t because of the record-breaking sales of pop artists in the late 1990’s and 2000. If all industries experience bubbles, maybe that was the big music industry bubble. I’ve been trying to find a good data source on record sales but have yet to do so, if you know of one, let me know.

The RIAA’s response has been to use a carrot and stick method, heavy on the stick, to try and change downloading behavior. On the stick side, the main strategies have been:

• Spread FUD (fear, uncertainty and doubt) using a combination of high profile lawsuits and advertising.
• Attempt to develop sympathy with the public for people working in the music industry, particularly artists who they portray as being cheated out of their money.
• As a last resort, allowing for restricted legal downloading through a variety of services including itunes, rhapsody and others. By the way, a non-sponsered plug for emusic, which features a variety of unDRM’d music. You can also now download music from Amazon with no restrictions.

Downloader Strategy

There has emerged a coherent organized resistane among music downloaders, but several different strategies seem to be shared by most proponents of downloading music. Among them,

• Disputing the assumptions put for the by the RIAA, namely that downloading music,
  • leads to less sales or
  • hurts the artists.
• Developing or co-opting anonymous ways of downloading content such as using tor or free wifi spots.

Among the arguments used to counter the RIAA’s statements are that the artists see a tiny percentage of each record sale, that most downloaded songs wouldn’t be purchased if buying was the only option, and that record sale declines are a result of the poor quality of music rather than it’s availability for free online.

Why the RIAA Cannot Possibly Win

Notice any similarities to the US in Iraq, the War on Drugs, prohibition, or any other enforcement of an unpopular law on a population? Unpopular occupations or laws cannot hope to achieve their agenda by increasing costs of disobeying. You simply cannot criminalize a majority of the population.

During prohibition crime rates increased drastically. The drug war has had a similar effect with the result being the extreme cost to the public for hosting people arrested for possession of marijuana.

The pattern is familiar enough that we should be able to map it out fairly easily:

1. An unpopular law or occupation takes effect.
2. Initial resistance is met with increased penalties.
3. Resistance is driven further underground, but due to it’s popularity it still extracts a heavy costs on the oppressor (which may be it’s own government or corporate organizations).
4. Eventually the cost becomes too great, and the occupier leaves or the law is repealed.

That said, I know there are some examples of foreign powers (often the U.S.) overriding popular will to instill a benevolent dictator. However, these cases are different in at least two ways:

1. The local power base was co-opted. It is absolutely necessary that a powerful segment of the population is allied with the occupying force to help enforce the occupying agenda. This was specifically rejected early in the Iraq War, with the result that local power bases resisted U.S. efforts.
2. A segment of the resisting population fractures and begins turning resisters in to the authority.

To the music industry, neither of these options is currently available. The distribution of music over p2p is by design decentralized, and so there is no local power base to co-opt. The closest might be bands themselves, and Metallica for example has done just that. But more and more you have bands rejecting the music industry entirely, including big names like Prince, Radiohead, and others.

A scary possibility, and one the RIAA has no doubt considered, is developing a core group of sympathizers who could turn in their friends for downloading music. For this to happen though, the music downloading issue needs to be reframed as a moral issue in which the RIAA is a victim. The RIAA knows that it will never be seen as the victim, and so instead has tried to shift it to portraying artists themselves as the victim.

But in a world where music superstars are glamorized and idolized, there are precious few tangible pains to be seen.

Until the RIAA can shift public perception so that downloading music is seen as a moral violation similar to being a Jew in Nazi Germany or being against the state in mother Russia, this is not likely to happen.

As always, I’ll post responses in an article next Sunday.

-zot.

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I started writing this as a response to a comment from James Taylor, author of Smart Enough Systems, on Snap Decision Making in Blink, but realized that it was getting long enough to be a post in it’s own right. Here is the comment from James:

One of the interesting areas I found when I reviewed Blink was that of how to apply these conclusions to automated decisions. How can one combine rules and analytics to make decisions more effectively. The importance of continuous learning or adaptive control is key as is the right balance of analytic insight and rule-based decisioning.

The concept of automation to circumvent decision making errors is interesting, but I don’t think it has arrived yet. It is a solution to a problem (from the companies perspective) of having to make repeated decisions in a given situation. Dealing with unsatisfied customers is a typical example. Do we refund, replace, ignore or send a letter of apology? The answer can be systematically determined based on several variables to find the maximum customer satisfaction for the lowest cost.The problem is that these systems remain inflexible. While reducing the cost of having a person decide what to do, they lose out on the subtle nuances that real people, with their years of experience interacting with other humans, can capitalize on.

It’s not a processing power problem, it’s a sensory problem. Any human has years of experience reading body, voice, and other situational cues that a computer faced with the same decision won’t have. We haven’t figured out quite yet how to give that same complexity to a decision algorithm.

Worse, customers hate them.

But can decision systems be used to correct biases and adjust for our mental shortcuts? Perhaps, but only if three things are true:

1. Decision makers in the country use them.
2. They are trained to explicitly avoid the same biases we encounter.
3. They have access to the same information that the decision maker does.

2 is fairly easy. We develop an algorithm that involves explicitly calculating the value of each choice instead of taking the mental shortcuts that we use.

But 1 and 3 are much more difficult. I would wager that quite a bit of the success of a company is determined by the small and seemingly insignificant interactions and decisions. Are employees going to use the decision system for every small choice? It’s impossible and would probably be very detrimental. You can use it to make larger strategic and organizational decisions, but even then it’s more of an assistance to an executive, who takes the results of the decision system as one of many pieces of information and makes a decision from there.

Even if we could solve the problem of having a decision system process and weight all the subtle cues a human receives during the decision making process, we would still need to figure out a way to translate cues into data points and determine what each cue means. We don’t have to do this explicitly, but the decision system needs to know the cues and know what they mean. It also has to be able to pick up on new cues that develop as culture shifts. Adaptive learning may get us there eventually, but we aren’t there yet.

-zot

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