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Presentation Preparation

A big part of doing research is presenting it at a conference. Since many people start out shy of public presentations, this can be a substantial challenge. Here are a few notes which might be helpful when thinking about preparing a presentation on research.

  1. Motivate. Talks which don’t start by describing the problem to solve cause many people to zone out.
  2. Prioritize. It is typical that you have more things to say than time to say them, and many presenters fall into the failure mode of trying to say too much. This is an easy-to-understand failure mode as it’s very natural to want to include everything. A basic fact is: you can’t. Example of this are:
    1. Your slides are so densely full of equations and words that you can’t cover them.
    2. Your talk runs over and a moderator prioritizes for you by cutting you off.
    3. You motor-mouth through the presentation, and the information absorption rate of the audience prioritizes in some uncontrolled fashion.
    4. The rate of flow of concepts simply exceeds the information capacity of the audience. Even with nondense slides and an easy succinct delivery, this can often happen.

    One way to prioritize is figure out: “What would I present in 1 minute?” or “What would I present in 5 minutes?”, and then let this guide your overall presentation.

  3. Unassume. When you are working in an area, it’s typical to buildup an internal shorthand for concepts. This needs to be peeled away when preparing a presentation. Decide what the minimal set of concepts are, and then be sure to define them as they are introduced. For people familiar with the basic concepts, this gives them a way to reconcile choices of language, and others at least have a prayer of following.
  4. Practice Well. Some people try to get a talk right by practicing it relentlessly until it is memorized, and then deliver it as a memorized monologue. This is terrible, because people in the audience know it is a memorized monologue and zone out. A good talk is delivered like a conversation, where it happens to be your turn to speak for awhile, and practicing that is more difficult. Some practice by yourself can be helpful—but not too much. A much better method is to practice on your friends by delivering to them before delivering it to the wider world.

The points above avoid the common failure modes which seem to come up with first-time presenters. There is much more advice to give (and for me to learn) about giving better presentations.

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The Coming Patent Apocalypse

Many people in computer science believe that patents are problematic. The truth is even worse—the patent system in the US is fundamentally broken in ways that will require much more significant reform than is being considered now.

The myth of the patent is the following: Patents are a mechanism for inventors to be compensated according to the value of their inventions while making the invention available to all. This myth sounds pretty desirable, but the reality is a strange distortion slowly leading towards collapse.

There are many problems associated with patents, but I would like to focus on just two of them:

  1. Patent Trolls The way that patents have generally worked over the last several decades is that they were a tool of large companies. Large companies would amass a large number of patents and then cross-license each other’s patents—in effect saying “we agree to owe each other nothing”. Smaller companies would sometimes lose in this game, essentially because they didn’t have enough patents to convince the larger companies that cross-licensing was a good idea. However, they didn’t necessarily lose, because small companies are also doing fewer things which makes their patent violation profile smaller.

    The patent trolls arrived recently. They are a new breed of company which does nothing but produce patents and collect money from them. The thing which distinguishes patent troll companies is that they have no patent violation profile. A company with a large number of patents can not credibly threaten to sue them unless they cross-license their patents, because they don’t do anything which violates a patent.

    The best example (and proof that this method works) is NTP, which extracted $612.5M from RIM. Although this is the big case with lots of publicity, the process of extracting money goes on constantly all around your in backroom negotiations with the companies that actually do things. In effect, patent trolls impose an invisible tax on companies that do things by companies that don’t. Restated in another way, patent trolls are akin to exploiting tax loopholes—except they exploit the law to make money rather than simply to avoid losing it. Smaller companies are particularly prone to lose, because they simply can not afford the extreme legal fees associated with fighting even a winning battle, but even large companies are also vulnerable to a patent troll.

    The other side of this argument is that patent trolls are simply performing a useful business function: employing researchers to come up with ideas or (at least) putting a floor on the value of ideas which they buy up through patents. Unfortunately, this is simply not true in my experience, due to the next problem.

  2. Combinatorial Ideas Patents are too easy. In fact, the process of coming up with patentable ideas is simply a matter of combinatorial application of existing ideas. This is a simple game that any reasonably intelligent person can play: you take idea 1 and idea 2, glue them together in any reasonable way, and get a patent.

    There are several reasons why the combinatorial application of existing ideas has become standard for patents.

    1. One of these is regulatory capture. It should surprise no one that the patent office, which gets paid for every patent application, has found a way to increase the number of patent applications.
    2. Another reason has to do with the way that patent law developed. Initially, patents were for processes doing things, rather than ideas. The scope of patents has steadily extended over time but the basic idea of patenting a process has been preserved. The fundamental problem is that processes can be created by the combinatorial application of ideas.

    The ease of patents is fundamentally valuable to patent troll type companies because they can acquire a large number of patents on processes which other companies accidentally violate.

The patent apocalypse happens when we project forward these two trends. Patents become ever easier to acquire and patent troll companies become ever more prevalent. In the end, every company which does something uses some obvious process that violates someone’s patent, and they have to pay at rates the patent owner chooses. There is no inherent bound on the number of patent troll type companies which can exist—they can multiply unchecked and drain money from every other company which does things until the system collapses.

I would like to make some positive suggestions here about how to reform the patent system, but it’s a hard mechanism design problem. Some obvious points are:

  1. Patents should have higher standards than research papers rather than substantially lower standards.
  2. The patent office should not make money from patents (this is not equivalent to saying that the patent applications should not be charged).
  3. The decision in whether or not to grant a patent should weigh the cost of granting. Many private property afficionados think “patents are great, because they compensate inventors”, but there is a real cost to society in granting obvious patents. You block people from doing things in the straightforward way or create hidden liabilities.
  4. Patents should be far more readable if the “available for all” part of the myth is to be upheld. Published academic papers are substantially more readable (which isn’t all that high of a bar).

Patent troll companies have found a clever way to exhibit the flaws in the current patent system. Substantial patent reform to eliminate this style of company would benefit just about everyone, except for these companies.

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Videolectures.net

Davor has been working to setup videolectures.net which is the new site for the many lectures mentioned here. (Tragically, they seem to only be available in windows media format.) I went through my own projects and added a few links to the videos. The day when every result is a set of {paper, slides, video} isn’t quite here yet, but it’s within sight. (For many papers, of course, code is a 4th component.)

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The Forgetting

How many papers do you remember from 2006? 2005? 2002? 1997? 1987? 1967? One way to judge this would be to look at the citations of the papers you write—how many came from which year? For myself, the answers on recent papers are:

year 2006 2005 2002 1997 1987 1967
count 4 10 5 1 0 0

This spectrum is fairly typical of papers in general. There are many reasons that citations are focused on recent papers.

  1. The number of papers being published continues to grow. This is not a very significant effect, because the rate of publication has not grown nearly as fast.
  2. Dead men don’t reject your papers for not citing them. This reason seems lame, because it’s a distortion from the ideal of science. Nevertheless, it must be stated because the effect can be significant.
  3. In 1997, I started as a PhD student. Naturally, papers after 1997 are better remembered because they were absorbed in real time. A large fraction of people writing papers and attending conferences haven’t been doing it for 10 years.
  4. Old papers aren’t on the internet. This is huge effect for any papers prior to 1995 (or so). The ease of examining a paper greatly influences the ability of an author to read and understand it. There are a number of journals which essentially have “internet access for the privileged elite who are willing to pay”. In my experience, this is only marginally better than having them stuck in the library.
  5. The recent past is more relevant to the present than the far past. There is a lot of truth in this—people discover and promote various problems or techniques which take off for awhile, until their turn to be forgotten arrives.

Should we be disturbed by this forgetting? There are a few good effects. For example, when people forget, they reinvent, and sometimes they reinvent better. Nevertheless, it seems like the effect of forgetting is bad overall, because it causes wasted effort. There are two implications:

  1. For paper writers, it is very common to overestimate the value of a paper, even though we know that the impact of most papers is bounded in time. Perhaps by looking at those older papers, we can get an idea of what is important in the long term. For example, looking at my own older citations, simplicity is it. If you want a paper to have a long term impact, it needs to have a simple algorithm, analysis method, or setting. Fundamentally, only those things which are teachable survive. Was your last paper simple? Could you teach it in a class? Are other people going to start doing so? Are the review criteria promoting the papers which a hope of survival?
  2. For conference organizers, it’s important to understand the way science has changed. Originally, you had to be a giant to succeed at science. Then, you merely had to stand on the shoulders of giants to succeed. Now, it seems that even the ability to peer over the shoulders of people standing on the shoulders of giants might be helpful. This is generally a good thing, because it means more people can help on a very hard task. Nevertheless, it seems that much of this effort is getting wasted in forgetting, because we do not have the right mechanisms to remember the information. Which is going to be the first conference to switch away from an ordered list of papers to something with structure? Wouldn’t it be great if all the content at a conference was organized in a wikipedia-like easy-for-outsiders-to-understand style?
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Best Practices for Collaboration

Many people, especially students, haven’t had an opportunity to collaborate with other researchers. Collaboration, especially with remote people can be tricky. Here are some observations of what has worked for me on collaborations involving a few people.

  1. Travel and Discuss Almost all collaborations start with in-person discussion. This implies that travel is often necessary. We can hope that in the future we’ll have better systems for starting collaborations remotely (such as blogs), but we aren’t quite there yet.
  2. Enable your collaborator. A collaboration can fall apart because one collaborator disables another. This sounds stupid (and it is), but it’s far easier than you might think.
    1. Avoid Duplication. Discovering that you and a collaborator have been editing the same thing and now need to waste time reconciling changes is annoying. The best way to avoid this to be explicit about who has write permission to what. Most of the time, a write lock is held for the entire document, just to be sure.
    2. Don’t keep the write lock unnecessarily. Some people are perfectionists so they have a real problem giving up the write lock on a draft until it is perfect. This prevents other collaborators from doing things. Releasing write lock (at least) when you sleep, is a good idea.
    3. Send all necessary materials. Some people try to save space or bandwidth by not passing ‘.bib’ files or other auxiliary components. Forcing your collaborator to deal with the missing subdocument problem is disabling. Space and bandwidth are cheap while your collaborators time is precious. (Sending may be pass-by-reference rather than attach-to-message in most cases.)
    4. Version Control. This doesn’t mean “use version control software”, although that’s fine. Instead, it means: have a version number for drafts passed back and forth. This means you can talk about “draft 3” rather than “the draft that was passed last tuesday”. Coupled with “send all necessary materials”, this implies that you naturally backup previous work.
  3. Be Generous. It’s common for people to feel insecure about what they have done or how much “credit” they should get.
    1. Coauthor standing. When deciding who should have a chance to be a coauthor, the rule should be “anyone who has helped produce a result conditioned on previous work”. “Helped produce” is often interpreted too narrowly—a theoretician should be generous about crediting experimental results and vice-versa. Potential coauthors may decline (and senior ones often do so). Control over who is a coauthor is best (and most naturally) exercised by the choice of who you talk to.
    2. Author ordering. Author ordering is the wrong thing to worry about, so don’t. The CS theory community has a substantial advantage here because they default to alpha-by-author ordering, as is understood by everyone.
    3. Who presents. A good default for presentations at a conference is “student presents” (or suitable generalizations). This gives young people a real chance to get involved and learn how things are done. Senior collaborators already have plentiful alternative methods to present research at workshops or invited talks.
  4. Communicate by default Not cc’ing a collaborator is a bad idea. Even if you have a very specific question for one collaborator and not another, it’s a good idea to cc everyone. In the worst case, this is a few-second annoyance for the other collaborator. In the best case, the exchange answers unasked questions. This also prevents “conversation shifts into subjects interesting to everyone, but oops! you weren’t cced” problem.

These practices are imperfectly followed even by me, but they are a good ideal to strive for.