This video tries to do something very difficult: Explain dimensions beyond the four we are used to. And does a good job of it.
(And to my students – watch this video after having read Neal Stephenson’s In the beginning was … the command line, as an introduction to the course on technology strategy.)
(Via Cory)
Bruce Sterling Schneier has a good article on the dangers of risk analysis when estimating software projects – and, by extension, estimating the risk of terrorist attacks.
It is the everyday risks that kill you – largely because the effect is delayed and the risk itself not very visible. I seem to remember someone proposing that the way to get responsible driving would be not to increase the safety level of the car, but instead decrease it – for instance by outlawing seat belts and mandating a four inch sharp metal spike placed in the middle of the steering wheel.
If too much imagination can make us overly risk-averse, a heavy dose of reality might have the opposite effect.
This presentation from the Google I/O conference is an 80-minute demonstration of a really interesting collaborative tool that very successfully blends the look and feel of regular tools (email, Twitter) with the embeddedness and immediacy of Wikis and share documents. I am quite excited about this and hope it makes it out in the consumer space and does not just rest inside single organizations – collaborative spaces can create a world of many walled gardens, and being a person that works as much between organizations as in them.
Google wave really shows the power of centralized processing and storage. Here are some things I noted and liked:
I can see some strategic drivers behind this: Google is very much threatened by walled gardens such as Facebook, and this could be a great way of breaking that open (remember, programs go from applications to platforms to protocols, and this is a platform built over OpenSocial, which jams open walled gardens). This could just perhaps be what I need to be able to more effectively work over several organizations. Just can’t wait to try this out when it finally arrives.
From surfing the net to surfing the waves….
Update: Here is the Google Blog entry describing Wave from Lars Rasmussen.
Wolfram Alpha just may take us one step closer to the elusive Semantic Web, by evolving a communication protocol out of its query terms.
(this is very much in ruminating form – comments welcome)
Wolfram Alpha officially launched on May 18, an exciting new kind of "computational" search engine which, rather than looking up documents where your questions have been answered before, actually computes the answer. The difference, as Stephen Wolfram himself has said, is that if you ask what the distance is to the moon, Google and other search engines will find you documents that tells you the average distance, whereas Wolfram Alpha will calculate what the distance is right now, and tell you that, in addition to many other facts (such as the average). Wolfram Alpha does not store answers, but creates them every time. And it does primarily answer numerical, computable questions.
The difference between Google (and other search engines) and Wolfram Alpha is not so clear-cut, of course. If you ask Google "17 mpg in liters per 100km" it will calculate the result for you. And you can send Wolfram Alpha non-computational queries such as "Norway" and it will give an informational answer. The difference lies more in what kind of data the two services work against, and how they determine what to show you: Google crawls the web, tracking links and monitoring user responses, in a sense asking every page and every user of their services what they think about all web pages (mostly, of course, we don’t think anything about most of them, but in principle we do.) Wolfram Alpha works against a database of facts with a set of defined computational algorithms – it stores less and derives more. (That being said, they will both answer the question "what is the answer to life, the universe and everything" the same way….)
While the technical differences are important and interesting, the real difference between WA and Google lies in what kind of questions they can answer – to use Clayton Christensen’s concept, the different jobs you would hire them to do. You would hire Google to figuring out information, introduction, background and concepts – or to find that email you didn’t bother filing away in the correct folder. You would hire Alpha to answer precise questions and get the facts, rather than what the web collectively has decided is the facts.
The meaning of it all
Now – what will the long-term impact of Alpha be? Google has made us replace categorization with search – we no longer bother filing things away and remembering them, for we can find them with a few half-remembered keywords, relying on sophisticated query front-end processing and the fact that most of our not that great minds think depressingly alike. Wolfram Alpha, on the other hand, is quite a different animal. Back in the 80s, I once saw someone exhort their not very digital readers to think of the personal computer as a "friendly assistant who is quite stupid in everything but mathematics." Wolfram Alpha is quite a bit smarter than that, of course, but the fact is that we now have access to this service which, quite simply, will do the math and look up the facts for us. Our own personal Hermione Granger, as it is.
I think the long-term impact of Wolfram Alpha will be to further something that may not have started with Google, but certainly became apparent with them: The use of search terms (or, if you will, seeds) as references. It is already common to, rather than writing out a URL, to help people find something by saying "Google this and you will find it". I have a couple of blogs and a web page, but googling my name will get you there faster (and you can misspell my last name and still not miss.) The risk in doing that, of course, is that something can intervene. As I read (in this paper) General Motors, a few years ago, had an ad for a new Pontiac model, at the end of which they exhorted the audience to "Google Pontiac" to find out more. Mazda quickly set up a web page with Pontiac in it, bought some keywords on Google, and quite literally Shanghaied GM’s ad.
Wolfram Alpha, on the other hand, will, given the same input, return the same answer every time. If the answer should change, it is because the underlying data has changed (or, extremely rarely, because somebody figured out a new way of calculating it.) It would not be because someone external to the company has figured out a way to game the system. This means that we can use references to Wolfram Alpha as shorthand – enter "budget surplus" in Wolfram Alpha, and the results will stare you in the face. In the sense that math is a language for expressing certain concepts in a very terse and precise language, Wolfram Alpha seeds will, I think, emerge as a notation for referring to factual information.
A short detour into graffiti
Back in the early-to-mid-90s, Apple launched one of the first pen-based PDAs, the Apple Newton. The Newton was, for its time, an amazing technology, but for once Apple screwed it up, largely because they tried to make the device do too much. One important issue was the handwriting recognition software – it would let you write in your own handwriting, and then try to interpret it. I am a physician’s son, and I certainly took after my father in the handwriting department. Newton could not make sense of my scribbles, even if I tried to behave, and, given that handwriting recognition is hard, it took a long time doing it. I bought one, and then sent it back. Then the Palm Pilot came, and became the device to get.
The Palm Pilot did not recognize handwriting – it demanded that you, the user, wrote to it in a sign language called Graffiti, which recognized individual characters. Most of the characters resembled the regular characters enough that you could guess what they were, for the others you either had to consult a small plastic card or experiment. The feedback was rapid, to experimenting usually worked well, and pretty soon you had learned – or, rather, your hand had learned – to enter the Graffiti characters rapidly and accurately.
Wolfram Alpha works in the same way as Graffiti did: As Steven Wolfram says in his talk at the Berkman Center, people start out writing natural language but pretty quickly trim it down to just the key concepts (a process known in search technology circles as "anti-phrasing".) In other words, by dint of patience and experimentation, we (or, at least, some of us) will learn to write queries in a notation that Wolfram Alpha understands, much like our hands learned Graffiti.
From links to seeds to semantics
Semantics is really about symbols and shorthand – a word is created as shorthand for a more complicated concept by a process of internalization. When learning a language, rapid feedback helps (which is why I th
ink it is easier to learn a language with a strict and terse grammar rather than a permissive one), simplicity helps, and a structure and culture that allows for creating new words by relying on shared context and intuitive combinations (see this great video with Stephen Fry and Jonathan Ross on language creation for some great examples.)
And this is what we need to do – gather around Wolfram Alpha and figure out the best way of interacting with the system -and then conduct "what if" analysis of what happens if we change the input just a little. To a certain extent, it is happening already, starting with people finding Easter Eggs – little jokes developers leave in programs for users to find. Pretty soon we will start figuring out the notation, and you will see web pages use Wolfram Alpha queries first as references, then as modules, then as dynamic elements.
It is sort of quirky when humans start to exchange query seeds (or search terms, if you will). It gets downright interesting when computers start doing it. It would also be part of an ongoing evolution of gradually increasing meaningfulness of computer messaging.
When computers – or, if you will, programs – needed to exchange information in the early days, they did it in a machine-efficient manner – information was passed using shared memory addresses, hexadecimal codes, assembler instructions and other terse and efficient, but humanly unreadable encoding schemes. Sometime in the early 80s, computers were getting powerful enough that the exchanges gradually could be done in human-readable format – the SMTP protocol, for instance, a standard for exchanging email, could be read and even hand-built by humans (as I remember doing in 1985, to send email outside the company network I was on.) The world wide web, conceived in the early 90s and live to a wider audience in 1994, had at its core an addressing system – the URL – which could be used as a general way of conversing between computers, no matter what their operating system or languages. (To the technology purists out there – yes, WWW relies on a whole slew of other standards as well, but I am trying to make a point here) It was rather inefficient from a machine communication perspective, but very flexible and easy to understand for developers and users alike. Over time, it has been refined from pure exchange of information to the sophisticated exchanges needed to make sure it really is you when you log into your online bank – essentially by increasing the sophistication of the HTML markup language towards standards such as XML, where you can send over not just instructions and data but also definitions and metadata.
The much-discussed semantic web is the natural continuation of this evolution – programming further and further away from the metal, if you will. Human requests for information from each other are imprecise but rely on shared understanding of what is going on, ability to interpret results in context, and a willingness to use many clues and requests for clarification to arrive at a desired result. Observe two humans interacting over the telephone – they can have deep and rich discussions, but as soon as the conversation involves computers, they default to slow and simple communication protocols: Spelling words out (sometimes using the international phonetic alphabet), going back and forth about where to apply mouse clicks and keystrokes, double-checking to avoid mistakes. We just aren’t that good at communicating as computers – but can the computers eventually get good enough to communicate with us?
I think the solution lies in mutual adaptation, and the exchange of references to data and information in other terms than direct document addresses may just be the key to achieving that. Increases in performance and functionality of computers have always progressed in a punctuated equilibrium fashion, alternating between integrated and modular architectures. The first mainframes were integrated with simple terminal interfaces, which gave way to client-server architectures (exchanging SQL requests), which gave way to highly modular TCP/IP-based architectures (exchanging URLs), which may give way to mainframe-like semi-integrated data centers. I think those data centers will exchange information at a higher semantic level than any of the others – and Wolfram Alpha, with its terse but precise query structure may just be the way to get there.
Google change their main logo according to whim and season, a practice that I like. The logo I captured here is a reference to the lemur-like fossil recently found in Germany that just may be the missing link in the evolution from ape to man.
Of course, the missing link has been claimed before – the Piltdown man in particular. History will be the judge, but kudos to Google for quick thinking and a really cool illustration. Unapologetic science-geekiness rules!
This is a delightful program which explains how the Gutenberg press works – through the time-honored pedagogic technique of actually building one:
My esteemed colleague and similarly jaded visionary Vaughan Merlyn has written rousing call for a new vision for the IT organization. While I do agree with everything he says – in principle – I think we still have a long way to go before the nitty gritty part of IT has moved from server room to cloud, leaving the users to creatively combine and automate their world in cooperation with their colleagues, customers and suppliers. While I do agree that the IT organization is better served by helping users help themselves than do their work for them, I am not sure all the users out there are ready to fish for themselves yet, no matter how easy to use the search engines, social communities and systems implementations tools become.
The enabling vision is not a new thing. I remember a video (or, rather film) from IBM from the mid-80s about End User Computing – a notion that the role of IT was to provide the tools for end users, and then they could build their own systems rather than wait for IT to build for them. (This, incidentally, was also the motivation behind COBOL in the 70s: The language was supposedly so intuitive that end users would be able to describe the processes they wanted automated directly into the computer, obviating the need for anyone in a white coat.) The movie showed an end user (for some reason a very short man in a suit) sitting in front of a 3270 terminal running VM/CMS. Next to him was a friendly person from the EUC group explaining how to use the friendly terminal, which towered over the slightly intimidated-looking end user like the ventilation shaft of an ocean liner.
It didn’t look very convincing to me. One reason for this was that at that time I was teaching (reasonably smart) business students how to do statistical analysis on an IBM 4381 and knew that many of them could not even operate the terminal, which had a tendency to jump between the various layers of the operating system and also had a mysterious button called SysRq, which still lingers, appendix-like, on the standard PC keyboard. Very few of those students were able to do much programming – but they were pretty good at filling in the blanks in programs someone already had written for them.
Of course, we now have gesture interfaces, endless storage, personal battery-powered devices and constant communication. But as the technology gets better, we cede more and more responsibility for how things work to the computer, meaning that we can use it until it breaks down (which it does) at which point we have no idea how things work. This is not the technology’s fault – it often contains everything you need to know to understand it rather than just use it. Take the wonderful new “computational search engine” Wolfram Alpha, for example: It can give you all kinds of answers to numerical questions, and will also (I haven’t seen it, but if the capabilities of Mathematica are anything to go by, it is great) allow you to explore, in a drill-down procedure, how it reached its answers.
This is wonderful – truly – but how many are going to use that feature? By extension: All of us have a spreadsheet program, but how many of an organization’s users can write a new spreadsheet rather than just use an already existing one?
For as long as I have worked with computers, each new leap in functionality and performance has been heralded as the necessary step to turn users from passive to active, from consumers of information to creators of knowledge. While each new technology generation, admittedly, has achieved some of this, it has always been less than was promised and much less than what was hoped for.
And so I think it is this time, too. Many people read Wikipedia, few write for it (though enough do). More importantly, many of Wikipedia’s users are unaware of how the knowledge therein is instantiated. Online forums have many more lurkers than contributors. And human ingenuity is unevenly distributed and will continue to be so.
So I think the IT department will continue to do what it is doing, in principle. It will be further from the metal and closer to the user, but as long as the world remains combinatorially complex and constantly changing, there will always be room for people who can see patterns, describe them, automate them and turn them into usable and connectable components. They will be fewer, think less of technology and more in terms of systems, and have less of a mismatch in terms of clothing and posture between themselves and their customers than before (much of it because the customers have embraced nerd chic, if not nerd knowledge).
The key for a continued IT career lies in taking charge of change rather than being affected by it. I think the future is great – and that we are still a long way from true end user computing. IT as a technology will be less interesting and more important in its invisible ubiquity. And Neal Stephenson’s analogy of a world of Elois and Morlocks, of the many that consume and the few that understand will still hold true.
I just hope I still will be a Morlock. With an Eloi pay and dress sense.
These are my raw notes from the session with Stephen Wolfram on the pre-launch of the Wolfram Alpha service at the Berkman center. Unfortunately, I was on a really bad Internet connection and only got the sound, and missed the first 20 minutes or so running around trying to find something better.
Notes from Stephen Wolfram on Alpha debut
…discussion of queries:
– nutrition in a slice of cheddar
– height of Mount Everest divided by length of Golden Gate bridge
– what’s the next item in this sequence
– type in a random number, see what it knows about it
– "next total solar eclipse"
What is the technology?
– computes things, it is harder to find answers on the web the more specifically you ask
– instead, we try to compute using all kinds of formulas and models created from science and package it so that we can walk up to a web site and have it provide the answer
– four pieces of technology:
— data curation, trillions of pieces of curated data, free/licensed, feeds, verify and clean this (curate), built industrial data curation line, much of it requires human domain expertise, but you need curated data
— algorithms: methods and models, expressed in Mathematica, there is a finite number of methods and models, but it is a large number…. now 5-6 million lines of math code
— linguistic analysis to understand input, no manual or documentation, have to interpret natural language. This is a little bit different from trad NL processing. working with more limited set of symbols and words. Many new methods, has turned out that ambiguity is not such a bit problem once we have mapped it onto a symbolic representation
— ability to automate presentation of things. What do you show people so they can cognitively grasp what you are, requires computational esthetics, domain knowledge.
Will run on 10k CPUs, using Grid Mathematica.
90% of the shelves in a typical reference library we have a decent start on
provide something authoritative and then give references to something upstream that is
know about ranges of values for things, can deal with that
try to give footnotes as best we can
Q: how do you deal with keeping data current
– many people have data and want to make it available
– mechanism to contribute data and mechanism for us to audit it
first instance is for humans to interact with it
there will be a variance of APIs,
intention to have a personalizable version of Alpha
metadata standards: when we open up our data repository mechanism, wn we use that can make data available
Questions from audience:
Differences of opinion in science?
– we try to give a footnote
– Most people are not exposed to science and engineering, you can do this without being a scientist
How much will you charge for this?
– website will be free
– corporate sponsors will be there as well, in sidebars
– we will know what kind of questions people ask, how can we ingest vendor information and make it available, need a wall of auditing
– professional version, subscription service
Can you combine databases, for instance to compute total mass of people in England?
– probably not automatically…
– can derive it
– "mass of people in England"
– we are working on the splat page, what happens when it doesn’t know, tries to break the query down into manageable parts
300th largest country in Europe? – answers "no known countries"
Data sources? Population of Internet users. how do you choose?
– identifying good sources is a key problem
– we try do it well, use experts, compare
– US government typically does a really good job
– we provide source information
– have personally been on the phone with many experts, is the data knowable?
– "based on available mortality data" or something
Technology focus in the future, aside from data curation?
– all of them need to be pushed forward
– more, better, faster of what we have, deeper into the data
– being able to deal with longer and more complicated linguistics
– being able to take pseudocode
– being able to take raw data or image input
– it takes me 5-10 years to understand what the next step is in a project…
How do you see this in contrast with semantic web?
– if the semantic web had been there, this would be much easier
– most of our data is not from the web, but from databases
– within Wolfram Alpha we have a symbolic ontology, didn’t create this as top down, mostly bottom-up from domains, merged them together when we realized similarities
– would like to do some semantic web things, expose our ontological mechanisms
At what point can we look at the formal specs for these ontologies?
– good news: All in symbolic mathematical code
– injecting new knowledge is complicated – nl is surprisingly messy, such as new terms coming in, for instance putting in people and there is this guy called "50 cent"
– exposure of ontology will happen
– the more words you need to describe the question, the harder it is
– there are holes in the data, hope that people will be motivated to fill them in
Social network? Communities?
– interesting, don’t know yet
How about more popular knowledge?
– who is the tallest of Britney Spears and 50 cent
– popular knowledge is more shallowly computable than scientific information
– linguistic horrors, book names and such, much of it clashes
– will need some popularity index, use Wikipedia a lot, can determine whether a person is important or not
The meaning of life? 42….
Integration with CYC?
– CYC is most advanced common sense reasoning system
– CYC takes what they reason about things and make it computing strengths
– human reasoning not that good when it comes to physics, more like Newton and using math
Will you provide the code?
– in Mathematica, code tends to be succinct enough that you can read it
– state of the art of synthesizing human-readable theorems is not that good yet
– humans are less efficient than automated and quantitative qa methods
– in many cases you can just ask it for the formula
– our pride lies in the integration, not in the models, for they come from the world
– "show formula"
Will this be integrated into Mathematica?
– future version will have a special mode, linguistic analysis, pop it to the server, can use the computation
How much more work on the natural language side?
– we don’t know
– pretty good at removing linguistic fluff, have to be careful
– when you look at people interacting with the system, but pretty soon they get lazy, only type in the things they need to know
– word order irrelevant, queries get pared down, we see deep structure of language
– but we don’t know how much further we need to go
How does this change the landscape of public access to knowledge?
– proprietary databases: challenge is make the right kind of deal
– we have been pretty successful
– we can convince them to make it casually available, but we would have to be careful that the whole thing can’t be lifted out
– we have yet to learn all the issues here
– have been pleasantly surprised by the extent to which people have given access
– there is a lot of genuinely good public data out there
This is a proprietary system – how do you feel about a wiki solution outcompeting you?
– that would be great, but
– making this thing is not easy, many parts, not just shovel in a lot of data
– Wikipedia is fantastic, but it has gone in particular directions. If you are looking for systematic data, properties of chemicals, for instance, over the course of the next two years, they get modified and there is not consistency left
– the most useful thing about Wikipedia is the folk knowledge you get there, what are things called, what is popular
– have thought about how to franchise out, it is not that easy
– by the way, it is free anyway…
– will we be inundated by new data? Encouraged by good automated curation pipelines. I like to believe that an ecosystem will develop, we can scale up.
– if you want this to work well, you can’t have 10K people feeding things in, you need central leadership
Interesting queries?
– "map of the cat" (this is what I call artificial stupidity)
– does not know anatomy yet
– how realtime is stock data? One minute delayed, some limitations
– there will be many novelty queries, but after that dies down, we are left with people who will want to use this every day
How will you feel if Google presents your results as part of their results?
– there are synergies
– we are generating things on the fly, this is not exposable to search engines
– one way to do it could be to prescan the search stream and see if wolfram alpha can have a chance to answer this
Role for academia?
– academia no longer accumulates data, useful for the world, but not for the university
– it is a shame that this has been seen as less academically respectable
– when chemistry was young, people went out and looked at every possible molecule
– this is much to computer complicated for the typical libraries
– historical antecedents may be Leibniz’ mechanical and computational calculators, he had the idea, but 300 years too early
When do we go live?
… a few weeks
– maybe a webcast if we dare…
Bill Schiano and I, between ourselves, solved this one pretty quickly. (That is, we found the computer names, not the extra thing, not mentioned on the site.)
(Incidentally, I also found SAGE, which was a pretty important computer system in its own right (as well as a computer company.). Also UNIX, CEC 80 (which at least sounds like a computer) and "rank" and "crib". Oh well.
The site Nerd Merit Badges sells, well, merit badges for nerds. Not sure what I would attach this to, but since this blog has been Boingboinged trice (here, here and here), I can at least attach an electronic copy, no?
(From Boingboing, of course).
Collaborative platforms are all the rage at the moment – every company wants one, has one, lives and dies by one. Cisco’s CEO John Chambers blogs, Michael Dell is on Twitter, Microsoft is selling Sharepoint by the truckload (well, figuratively speaking) and every software company in the world is busy putting 2.0 behind their offering, from backup to presentations.
I am worrying that all these platforms will lead to less collaboration, not more.
First, a personal observation: I am what Malone and Rockart in 1991 termed an intellectual mercenary. That is, I think of myself as a company of one, working for many organizations, but I am never member of only one community, and never, for a number of reasons, a full member of one. Sure, I have been on the faculty of the same business school since 1996 and had relationships with more or less the same set of people in the consulting world since 1994, and currently I am in year three of what I hope will be an 8 year research project on information access technologies. But that doesn’t change the fact that I am not a full member, at least not technically speaking, of any one of them.
My base job, as an academic, has a technical infrastructure geared towards a physical presence at the campus (at least on a regular basis) and a lack of visibility outside campus. The school has an outdated infrastructure, but since most of the faculty thinks this is just fine, since it works, few things change. So I have to have my own web site and email to project a less antiquated face for the rest of the world. Fine. Then I work with two companies (one mostly in the States and one mostly in Norway) on various projects. In case of their technical infrastructure, it is more modern, but tightly integrated around a different platform than what my main place of work is using.
The interesting thing, of course, is that as long as communication took place via email and collaboration was done sending Word documents around, everything was hunky dory – I could use whatever I wanted. Now each collaboration partner has their own collaborative platform, with integrated calendaring, Twittering, email, directories and Turing knows what else – and I find myself fighting new user interfaces every time I need to do something.
Software evolves from application to platform to standard. The problem is that we do not yet have standards for collaborative activities, only for the end results of those activities: Reports, teleconferences, single emails, and presentations. If you want integration, you have to belong to one organization, and that organization only. Which is fine for most people, but not for those of us who wants to contain multitudes, and do.
At the current state of collaborative software, it strengthens intra-organizational collaboration but weakens inter-organizational collaboration. We are back to the days when some companies used Wordperfect and some Word, and everyone fiddled with translations between them. Now we have to find ways to maintain a personal creative space (in my case, Evernote, Word, and Windows Live Writer) while injecting and extracting the results from various collaborative platforms. I find myself yearning for something that will maintain my collaborative activities in much the same way Live Writer (along with Live Sync, the best product Microsoft has come up with in a decade) allows me to suck down and load up posts to my various blogs. (A bonus would be if you could update the various Wikipedia articles you care about as well, but I digress).
An alternative is a shared platform, such as Google Docs, but again, that forces you to work in a different interface (though it is very similar to Word), does not bring the work inside your own space (where you are reminded about doing it) and forces everyone else to move out of their space. What we need here is some serious standard work in XML, and a recognition by the platform providers that a substantial amount of collaboration (and, I suspect, much of the innovation) comes from those that jump between platforms.
So, here is my message to the collaborative platform vendors: Tear down the walls before you have erected them! Do it by offering APIs or facilitating cross-platform synchronization. While we are at it, some software company with a stake in keeping their operating systems dominance should probably take me up on creating a cross-platform personal collaboration client.
I want my PCC revolution now!
These exercises looks like just the thing, if I can only get into the habit.
(Via Boingboing.)
I recently Twittered that I thought spam levels were going up again (I correlated that with moving to the States in January) and, well, I was right about the increase but wrong about the reason: Spammer are rebuilding their infrastructure (NYT). Here we go again. I do agree with the Gmail assessments in the comments – very few spam messages in my gmail account, and as far as I know, no false positives.
Time to look at filtering through Gmail, especially since more and more ISPs block outgoing SMPT packets (i.e., port 25) which forces me to use Gmail anyway.
Imagine a world where we wouldn’t need locks and passwords…talk about something that would reduce global warming…
Geek and Poke has this wonderful cartoon on the apparent promise of cloud computing:
(and if you don’t grok "Geek and Poke", you sure didn’t program back in the 80s…(hint))
Good article comparing Wikipedia’s development and life as that of a city by Noam Cohen, drawing on Lewis Mumford’s description of how a city comes to be:
Since their creation, cities have had to be accepting of strangers — no judgments — and residents learn to be subtly accommodating, outward looking.
Mumford elaborates: “Even before the city is a place of fixed residence, it begins as a meeting place to which people periodically return: the magnet comes before the container, and this ability to attract nonresidents to it for intercourse and spiritual stimulus no less than trade remains one of the essential criteria of the city, a witness to its essential dynamism, as opposed to the more fixed and indrawn form of the village, hostile to the outsider.”
The marvel of Wikipedia — and cities — is that all the intercourse and spiritual stimulus don’t make living there impossible. Rather, they are exactly what makes living there possible.
[..]
It is this sidewalk-like transparency and collective responsibility that makes Wikipedia as accurate as it is. The greater the foot traffic, the safer the neighborhood. Thus, oddly enough, the more popular, even controversial, an article is, the more likely it is to be accurate and free of vandalism. It is the obscure articles — the dead-end streets and industrial districts, if you will — where more mayhem can be committed. It takes longer for errors or even malice to be noticed and rooted out. (Fewer readers will be exposed to those errors, too.)
Like the modern megalopolis, Wikipedia has decentralized growth. Wikipedia adds articles the way Beijing adds neighborhoods — whenever the mood strikes. It is open to all: the sixth-grader typing in material from her homework assignment, the graduate student with a limited grasp of English. No judgments, no entry pass.
That simple and that beautiful…
Box UK, has a very complete survey of web business models. My concept of business models (though for information content and services, not just services) on the web was four: Free, ad-supported, subscription or some form of micropayment (Skype, I would say, is the largest user of this concept, though they pull it off a regularly replenished account).
This site expands that classification a bit, including things like taking payemnt for physical products and letting the service follow the product (which more and more electronics manufacturers do). What strikes me is that there really is nothing new here – all the business models have been around since time immemorial, something the media industries of the world should take note of.
The answer for more and more of the granulated information providers of the world lies in moving either towards the user (becoming, essentially, an integrated part of the user’s information need, such as Bloglines) or to step further from the individual information consumer, becoming a source of content for others to fight over. Paying a license, of course.
Anyway, a good list, and a good survey. Check it out.
(Via Chris Anderson of Wired.)
James Warren delivers the best defense for traditional newspapers I have yet to read, in The Atlantic. Interestingly, he singles out The Economist as one of the outlets that have done well in the face of the online onslaught. In Norway, the same thing has happened – the few papers that see increasing circulation are the quality niche papers, such as Morgenbladet and the extremely left wing Klassekampen, both of them niche publications that to some extent have shed their political affiliation and instead opened for quality journalism with opinions attached.
I feel encouraged that this is the way forward. Why waste paper on anything that isn’t high quality?
Update March 16: Linked from the same page: The potential disaster for investigative journalism, another good article, by James Warren. Methinks we need to look into funding of investigative journalism outside the subsidy model. Funny, I remember giving a talk about the decoupling of ads and content to Dagbladet, a Norwegian newspaper that is now in dire straits, in August 2000, and by then this wasn’t even news…
Mary Beard has a really interesting perspective on the consequences of openness: Transparency is the new opacity. In the absence of confidential channels (which, given today’s storage and search capabilities, you have no guarantee will remain confidential) very little actual information gets transmitted in student appraisals.
And the only difference between job appraisals and student appraisals, I assume, lies in vocabulary. As a technologist, I could envision all kinds of technical fixes to this, assuming that those in charge of the specifications acknowledge that they are necessary: Fields for comments hidden from the subject, fields that terminate after a certain time after reading, filters to search engines that handle confidentiality – including the fact that there is a confidential comment in the first place (which turns out to be surprisingly hard to do.)
But the more natural fix is the quick conversation in the pub, the hallway, or on the private cell phone – impervious to search, storage and documentation – where the real information can be exchanged. The electronic equivalent? Encrypted Twitter, perhaps, if such a thing exists.
What we need is online coffee shops, offering the same discreet, transient and history-less marketplace for information. Now I spend time on the phone with my colleagues for that, but that doesn’t work well across time zones. So – what would it look like and how to build it?
PS: Come to think of it, Skype is encrypted, at least the phone calls.
As can be established with a quick search, I am somewhat obsessed with keyboards. Now I think I might just have found the ultimate one – a Unicomp Buckling Spring keyboard from PCKeyboard.com. With an integrate mouse, no less. The latter is somewhat clumsy and will take some adjustment, but the keyboard feels like the old IBM keyboards of the 80s and early 90s and sounds like a machine gun. Definitely not the keyboard to use when you are interviewing someone over the phone, but the precise touch and distinct sound has a good effect on reducing mistypes. It also will necessitate some exercise – I had forgotten just how long the key travel was on these babies.
Best of all – they built a Norwegian version for me at no extra charge. Highly recommended – though since the keyboard is not CE-registered, they cannot send it to Europe. Any excuse for a trip to the States…
I am writing this (using my little Asus, which actually fits in a large coat pocket) from Ignite Boston 5, a meetup of techies of various stripes in the Boston area at a bar on Union Street close to Faneuil Hall, arranged by O’Reilly. The format is pretty simple: Get 250 geeks together (with another 250 waiting to get in) in a large bar, have Google buy everyone a free beer, and subject them to presentations on various subjects by volunteers that have been more or less carefully vetted. The result is a sort of geek stand-up-and-shout, with Powerpoint presentations. Right now a guy writing a book about open government and sharing of data – “democratizing data” – is giving the (rather good) keynote presentation, with 12 more, shorter presentations to follow. I suppose this is what Second Tuesday should have been if it hadn’t become all corporatish..
All in all, it is quite interesting to find an environment where being a geek is not only accepted, but kind of cool. Nevertheless, I am the only person with an open computer in this crowd, which is either an indication that I am an über-nerd or that everyone else is Twittering or blogging by iPhone. Oh well.
At least it gets me out of the office for a few hours. Much to be said for that.
I have been here for almost two hours, have seen the list of presenters – and though they are sincere, I think that’s it. For this time. Not that I didn’t like this thing, but there is something to be said for consuming new things in measured doses….
Applied Abstractions 