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On Tyrants – Recent Reads!

I’ve been on somewhat of a reading binge recently. I enjoy finding common themes and connections between books that I read, so I present to you some of those thoughts. I dislike trying to pin down an exact rating, so let’s go with deserves a read or missed the mark.

Nothing to Envy – Barbara Demick

The story of North Korea can be told through many lenses. It is satisfying and simple to portray North Korea through the lens of an outsider, because in this country’s case reality truly is stranger than fiction. In fact, it is so absurd that at times the narrative changes from describing a dark, totalitarian state to a farce. This has been done with great style by many, including the Vice Guide to North Korea and the graphic novel Pyongyang: A Journey in North Korea by Guy Delisle. I highly recommend them. A much more complicated story, both to obtain and to tell, is that of the people of North Korea. Nothing to Envy not only manages to tell that story, but does so with great empathy and clarity.

Told through the accounts of defectors during the great famine of the early 1990’s, Demick weaves multiple stories into an epic tale of love, family, and sacrifice that had me holding back some tears by the end of the book. It didn’t dawn until me until then, but I had been cheering for these people the entire way through. Although secondary to the stories themselves, as a Communist damnation this book is the best I’ve seen, particularly because Demick finds accounts of people from all across the power spectrum: from the highly favored caste, an eventual Workers’ Party member, to the lowest, the family members of a former POW from South Korea. It’s easy to spot the cracks even without direct pushes or narrative-making from the author, and makes for a compelling exploration of philosophy and systems of government. Through and through, this book deserves a read.

Steve Jobs – Walter Isaacson

Admit it, this dude is an icon. Steve Jobs was pivotal in putting the personal computer on our collective radar. As with any man as influential as this there is always a story to tell; indeed, Isaacson makes use of this to fill up 656 pages. Unfortunately, much of this bulk only serves to hammer home one point: Jobs is unlikable, petulant, emotionally unavailable, and mean. (And even so, occasionally brilliant.) Perhaps this isn’t the author’s fault, but it sure felt like it at times. Early in the book, I simply felt a distaste for the man; he is exactly the kind of manager that I would despise working under. I didn’t expect for him to do a 180 and reveal a warm fuzzy-bear side, but as the book went on I became more discontented.

Jobs never evolves as a person, and I grew to despise him for that. All of his infatuations (drugs, eastern religions, radical diets) do not seem to fundamentally improve him as a human in any way. Steve is static. His lack of personal growth paradoxically peaks with his battle with cancer. It is caught in an early and treatable stage, but Jobs remains recalcitrant to authority, refusing medical advice for a live-saving surgery, deciding instead to rely on extreme diets and alternative therapy. When he finally relents and has the surgery, he ends up aspirating his stomach contents into his lungs because he refuses to have his stomach pumped, against doctors’ advice. Afterwards he complains that he “almost died because the doctors messed up a routine operation.” Cue me throwing down the book in disgust.

I cannot relate to Jobs on any level; his humanity is like a mythical beast listed in some cryptozoological manual. I suppose in that lies the fundamental drama of his life’s story: Jobs was such a stiff arrow that it eventually killed him. Jobs is precisely what I guard myself against becoming, and maybe that scares me; maybe that’s why I hate him so.  From a more technical standpoint, Isaacson could have easily pared the book down to a more manageable 500 pages, leaving out the multitudinous, distracting mentions of Jobs’ “reality distortion field” and its supporting evidence (seriously Walter, we get it) and some of the more nuts-and-bolts descriptions of business deals found in the latter half of the book. Even with the personal insight that this book enabled, I’m going to have to say it missed the mark for all but the most involved Apple aficionados.

The Hardest Question to Answer as a Ph.D Student: “And After You’re Done?”

Image by Stitch, Creative Commons License

It’s one of those nights again. It’s 2 in the morning, and I’m sitting at my computer sweating over job listings. I won’t be graduating for over three years, but I’m going at it like my life depends on it. In fact, I’ve been going at it for hours. Suddenly, it’s 3. When did that happen? I have work tomorrow – I’m going to hate myself when I wake up. Even so, the list continues to expand. Here’s just a taste of places and ideas, which is pretty much stream of consciousness:

Intel, IBM, AMD, Motorola, Momentive, Apple, Labtiva, Udacity, USAjobs listings, PLoS/open access/advocacy/editor/american physical society, shmoop, JoVE, Public Information Officer / Science PR, National Academies, Govt labs, NIST, consulting, Public Impact, community colleges, engineering education, AAAS, Institute For the Future, academic libraries, CASEE, Policy, NSF, journals, institutional research, science writing, nonprofits, program manager

Sounds good, right? I’ve got so many options. Unfortunately, I don’t share that same opinion. I’ve fallen prey to The Paradox of Choice, a not-so-rare phenomenon in modern society whereby abundance of choice paralyzes the decision-maker, and subsequently makes him less satisfied with his decision in the end than if he had less choice. Why? Barry Schwartz, the originator of the idea, thinks it goes something like this:

…it has to do with the irrational way people measure “opportunity costs.” Instead of calculating opportunity cost as the value of the single most attractive foregone alternative, we seem to assemble an idealistic composite of all the options foregone. A wider range of slightly inferior options, then, can make it harder to settle on one you’re happy with.

Indeed, this is what I found myself doing. It’s easy to focus on the negatives, and become disillusioned in the search for that one perfect place to work. I would convince myself that I wanted one job, and then found myself lusting after another after I thought about the pros and cons again. This would happen over and over again (and still is). Right now I’m set on being a science journal editor. Previously, a university professor, then a community college professor, then a science/physics education researcher, then a science policy wonk, then an R&D process engineer at Intel, then a science writer. Who knows what I’ll want to do next week? Science podcaster it is!

No Turning Back

Why am I making this into such a big deal? There is a felt culture in doctoral education, at least in the sciences, that it is important to make “good use” of your degree and your skills. It is like we are apprentices to a fine craft, and it behooves us to follow in our mentors’ footsteps and make them proud. This manifests in both a subtle social pressure and a subtle personal pressure. This problem is compounded because once a person decides to stray outside of a research-heavy career, it is excruciatingly hard to get back in. The reason for this is clearly evident in my rapid-fire RSS feeds: science is moving at a pace unfathomable to all except those who are already immersed in it. Getting off the horse isn’t really an option if you ever want to be competent again.

There’s also an ego component to it. Graduate programs, much more so than college, feel almost like a sacred journey in which one battles through insecurities and setbacks to further the human race. Nobody wants to give up on that “noble quest.” Some get so caught up in the process that it consumes them. What I am consumed by is the idea that I’m doing this degree for all the wrong reasons, and so I am up late at night again, running over the same old ground. It’s hard to keep perspective, which I believe is the single most important thing to have in something I’m committing five years of my life to.  The trailer for the recently screened movie Indie Game (which looks amazing, by the way) sums it up perfectly over and over again:

“I’m so closely attached to it. This is my identity. It’s [my game]. I am ‘guy making [my game.]’ You know, that’s about it.”

“I’m on the line. Me. My name, my career. If this fails, like, I don’t think I’ll work in games again.”

“If, you know, if you just can’t get the work done, then the past two years are basically worth nothing. (Sarcastically) No pressure…”

“All you’ve been doing for four years is look at this, like this close. Like, you can’t see anything else. You don’t even see the mistakes in there anymore.”

That’s kind of like me at times like this.

“This is my identity. It’s my degree. I am guy getting my PhD.”

Science: The Next Great Division of Labor

The greatest improvement in the productive powers of labour, and the greater part of the skill, dexterity, and judgement with which it is any where directed, or applied, seem to have been the effects of the division of labour.

These are the first words in The Wealth of Nations by Adam Smith. Indeed, the division and specialization of labor was fuel for the Industrial Revolution, and I believe that the world will soon encounter another division of labor, this time in the scientific sector.

ENTER STAGE LEFT: Science Exchange.

Science Exchange, at its core, is a service that provides scientists and laboratories a fast, simple way to find and use equipment at other universities. This is extremely important because some disciplines need to maintain a high level of capital equipment to do their research properly. Just in my laboratory, we own multiple high vacuum metal deposition chambers, furnaces, and pieces of electrical characterization equipment. All of this adds up to millions of dollars worth of investment, with significant maintenance costs. Some of the larger, more expensive equipment (scanning electron microscopes, and the like) is held in shared lab space that anybody can use for a price. Research groups are constantly jockeying to get equipment funding; there are at least three big “wish list” items that I hope our department will be able to pick up soon, all costing upwards of $300,000, some over a million. A service like Science Exchange allows researchers to more easily access beyond the traditional route of signing up for national laboratory time.

On the supply side, this is another great way for universities and research groups to make money beyond applying for and winning grants. Taking any pressure off of lab managers and PIs to constantly run in the rat race for funding can only be good for everyone. If services like Science Exchange become extremely popular, we might just see more space opening up in academia for non-graduate professionals and technicians to work on inter-university projects. However, an idea like this is not without its problems…

The New Factory Worker

To take an example, therefore, the trade of the pin-maker; a workman not educated to this business, nor acquainted with the use of the machinery employed in it, could scarce, perhaps, with his utmost industry, make one pin in a day, and certainly could not make twenty. But in the way in which this business is now carried on, not only the whole work is a peculiar trade, but it is divided into a number of branches, of which the greater part are likewise peculiar trades.

These are the next two sentences from The Wealth of Nations. The words apply as strongly in science today as it did for manufacturing centuries ago: will we be reducing scientists to pin makers? Is this just the natural progression, where skilled labor is replaced by unskilled labor, and eventually automated? Should we even fight over this? I’m interested to see whether this will open up the door to serious science outsourcing, as has happened in the programming industry.

China is alive with possibilities in science, but realizing them is a complicated affair. The country’s fondness for speed — for short-term achievements and, increasingly, short-term profits — has worked relatively well in the chemical and physical sciences and in large-scale genomics, where researchers can systematically tick off the chemical compounds or genetic sequences that they have produced – Neuroscience in China: Growth Factor

For those disciplines, there might just be a sea change. Science Exchange is an outsourcing enabler if I have ever seen one. Finally, what if all science was inter-laboratory? Who owns the work? What would it take for us to divorce ourselves from the secretive, cloistered nature of our research? What would have to change? More on that another time, I think. This post has far more questions than answers, most that I’m not even going to pretend to know the answers to. Only time will tell, all I know is that it’s going to be an interesting ride.

Designing for Sanity’s Sake: Using Modular Design

Recently I posted a preview of Starship 1 by Geoff Englestein, a boardgame which I look forward to with bated breath. Come on Geoff, pick up the pace. I know you have publishers knocking down your door! As I described fully in that post, Starship 1 is a game where each player acts as a member of a starship’s crew, all working together to complete various missions. The genius of this game’s design from a sanity standpoint is its use of closed systems.

What I mean by a closed system is one that can be tweaked independently without causing major changes in other parts of the game. In the case of Starship 1, each “mini-game” that the crew members are in charge of are each a closed system. Geoff could tweak the mechanics and difficulty of each crew mini-game without causing unintended changes in the other systems. All of these closed systems are linked by the core gameplay, each affecting it but with the mechanics of each crew member cordoned off nicely.

In addition to designing closed systems, it is also important to not allow a specific parameter to penetrate too many systems. While it may be tempting to do this in the hopes of making a deeper game, it also obfuscates the meaning of a specific parameter, making it harder for the player to assign value to, and also makes changes to the game design much more difficult. When a single parameter affects many different areas, the ramifications of a single change are harder to predict and plan for. A great example of a game that cordons off its parameters very well is Endeavor by Z-Man Games.

Besides Glory (victory points), Endeavor has four parameters of interest, each with very simple effects:

  • Industry: Industry determines the level of building you can build at the beginning of your turn.
  • Culture: Culture determines the number of new citizens you gain at the beginning of your turn.
  • Finance: Finance determines the number of buildings used on the previous turn that can again be used on the current turn.
  • Politics: Politics determines your card limit.

These parameters are so well defined that each one only matters in a specific game phase. This design allows the players to quickly determine the value of each of the parameters, and how their actions throughout the game affect their abilities later in play. As a player, I would immediately know that if taking City X gave me a boost on my Culture and Politics track, that I would be getting more people and would be able to hold more cards. Trying to dole out too much meaning to one parameter will only confuse players.

Designing for Sanity’s Sake: Keep Your Eyes on the Prize

Halbot K Browne, circa 19th century

Every design needs goals. What kinds of goals? Aesthetic goals. I don’t mean just how the game looks. I am speaking from the standpoint of the MDA Framework, a groundbreaking attempt to formally model the elements of gameplay. Let’s explore the three elements of MDA, starting from the canon definitions in the linked paper:

  • Mechanics describes the particular components of the game, at the level of data representation and algorithms

I have italicized data representations and algorithms because there is a very important connection to be made between MDA and the design categories defined in the previous post. Data representation is the equivalent of parameters and algorithms are the equivalent of rules. Specifically, mechanics are the means by which the players and the game affect each other using rules to affect parameters. They are the “actions and events” from the rules description. In essence, a mechanic is an envelope for how the game or the player affects their, others, or the game’s parameters through sets of rules and decisions, with associated content that interacts with but does not directly affect the mechanic. Below is an example breakdown:

Mechanic Name: Weather Event

Mechanic Scope: Game affects players

Mechanic Rules:

  • Weather events happen at the beginning of every turn. (Triggering rule)
  • Weather events affect all players. (Targeting rule)
  • Players must roll their endurance score to avoid being injured. (Resolution rule)
  • If injured the player must lose health points based on the current weather conditions. (Resolution rule)

Mechanic Parameters: Endurance score (player parameter), health points (player parameter), weather conditions (game parameter)

Mechanic Content: Different types of weather events (hail storms, avalanches, cold snaps, etc.)

Some mechanics are too complicated to be defined by this envelope. In those cases, it is pragmatic to reduce the mechanics to their simplest counterparts, and then create mechanics-complexes that include the interactions of multiple mechanics. At this point, it’s simply a matter of organization and semantics. Within the mechanic, the rules and parameters can either be apparent to the player or revealed through feedback from the game.

In boardgames, generally the rules and mechanics are all well-known because there is no automation; everything mechanical is operated by the players and must be learnt from the rulebook. In video games,  rules are often hidden (eg. how damage is calculated in a real time strategy game), as can parameters (eg. your run versus your sprint speed in a first person shooter). Some prominent designers consider the rules or mechanics to be a black box. They certainly can be in some cases, like those I have described, but I believe that dynamics, the next topic, are a universal black box across all types of games. Also, it is important to note that different designers have different ways of organizing these terms (as Mr. Koster has done in his article versus mine), so tread carefully.

  • Dynamics describes the run-time behavior of the mechanics acting on player inputs and each others’ inputs over time

A fairly accurate way to describe dynamics is ’emergent gameplay.’  That is, gameplay that is not built into the game, but comes about from the interaction of the players and the mechanics presented to them. A designers cannot interact directly with them by “adding” them as they could add mechanics, and they are more difficult to plan for than aesthetics.

Dynamics aren’t even necessarily readily observable while one is playing a game; it may take an outside observer to note the patterns in play that emerge given a particular group of players. Because of this, playtesting is the most efficient way to ascertain the dynamics that are evolving from your current rules and current players. If you feel that a particular mechanic is contributing to that dynamic, tweak one (and only one) part of the game and then playtest again with the same group. Playtesting with different groups can be useful to get a broad sense of the dynamics that can evolve, but only after you have finished the tweak and verified the results with a duplicate group.

  • Aesthetics describes the desirable emotional responses evoked in the player, when she interacts with the game system

First, a quick caveat: to generalize aesthetics fully, we should instead describe them as all of the emotional responses evoked in the player, not just the desirable ones. Like I mentioned in the beginning of this post, your ultimate goal as a game designer is to evoke the desired aesthetic responses from your players. Content interacts more directly with aesthetics than rules and parameters, but the aesthetics are not necessarily most heavily influenced by them.

Board game aesthetics are primarily consequences of the gameplay dynamics themselves, not from the game content. However, in more media-intense a games, the content has greater leverage on the aesthetics. Space Marine is a great example of a video game with content finely tuned to enhance the aesthetic experience, specifically its execution animations and brutal, overwhelming sound design. The aesthetics in an equally media-rich game like Dark Souls, most would agree, is more defined by its difficulty curve and combat system than by its content, though!

As described in the original paper, aesthetics can be divided into a number of different categories. The non-definitive list is as follows:

  1. Sensation (Game as sense-pleasure)
  2. Fantasy (Game as make-believe)
  3. Narrative (Game as drama)
  4. Challenge (Game as obstacle course)
  5. Fellowship (Game as social framework)
  6. Discovery (Game as uncharted territory)
  7. Expression (Game as self-discovery)
  8. Submission (Game as pastime)

Content influences certain categories of aesthetics more directly. For example, it would likely influence fantasy, sensation, and narrative more than challenge, fellowship, and submission, which would be primarily dictated by the dynamics of the game.  In other words, some aesthetics are more or less “content aware” or “dynamics aware” than others. Ultimately, every change in design should contribute to your aesthetic goals. This is especially important to think about when determining which mechanics contribute to the game. Every designer has his or her own pet mechanic that seems fun and interesting, but ultimately does not contribute to the vision of the game. While it is painful to tear out pieces of the game, ultimately we must do what is best for the game, not for our ego.

To round things off, here is the way that I interpret the interactions between all of the game ideas and elements that we have explored in this post and the last in graphical form. The missing component, aesthetics, is simply the way that the player interprets the diagram as a whole. Enjoy, and see you next time!


					

Designing for Sanity’s Sake: Starting at the Beginning

Game design is inherently complicated. It involves the interaction of many widgets and doodads, along with the exciting and often unpredictable human element. This complexity is magnified when the game is multi-player, as the vast majority of board games are. Keeping a handle on the numerous design decisions made throughout the development process can be difficult. If left unchecked, the design will become fragmented and ill-focused.

When I first started to design board games, I couldn’t help but write out every interesting thing imaginable. I was high on possibilities, and that manifested itself in page after page of scribbles and notes. A great brainstorm for sure, but that is where it should have ended. I had nothing holding me back from trying to squish all these ideas together, so I did. I would create patchwork games. I figured that the vision would squirm its way out as I continued to refine my design. I was thinking like a prospector: surely some gold dust will settle out of the muck if I shake the pan long enough. This thinking was wrong. I had no anchor, no stable foundation. I didn’t start at the beginning. The natural question to ask next is this: where is the “beginning” for a game design? Dan Achterman has a great answer to that question, which he finds by splitting design ideas into three types, as follows:

  • Parameters are the values that your game systems use to simulate your game, such as health, movement speed, weight, mana cost, critical hit chance, etc.
  • Rules are the functions and formulas that determine the results of actions and events in your game. Rules include things like how combat damage is calculated, how character statistics change when they level up, and how random loot is determined.
  • Content  is all things in your game, including characters, items, monsters, spells, talents, etc. Each type of content has parameters that define it, like damage for a weapon, or attributes for a character.

Now that we know the types of design ideas, which do we pursue first? If your brainstorms are anything like mine, it’s likely that a lot of content will be produced. This is unequivocally the wrong direction to go in at the beginning. Without clearly defining the properties that are important to your game system and the way that the system interacts with those properties, there is no way to put the content in the context of your game. What does the +1 Magic AwesomeSword do, anyway? Does the business tycoon’s “Buy-Out” move cost money, influence, power, or time? Content comes last. Beyond that, it is up to the designer to come up with a pattern that suits them. Dan in his article recommends the following:

  1. Choose the parameters that your game uses.
  2. Design rules that are no more complex than necessary to implement your game vision.
  3. Define the progressions for how parameters change throughout the game.
  4. Design content types that are as complex and interesting as you can manage.
  5. Add new parameters, systems, and content types in layers as needed.

This is not necessarily the best option for you, but it is a place to start. The bulk of the early design process will involve iterating between steps 1 to 3. It is very important to test each major element of the game individually before moving on to adding a new rule or parameter. If you do not do this, the design could become confusing in a hurry. However important it is to start at the beginning, though, it is equally if not more important to have an end goal. Can you guess what the next post will be on? Come back soon!