Frequent thinker, occasional writer, constant smart-arse

Tag: wikipedia (Page 1 of 2)

How we get told what to think

Have you ever wondered who decided to add that question when filling out a form? If you have, like me, then maybe you’ve also thought, what’s the hidden force influencing what we think, say, and do? A thinker, Curtis Yarvin, has a hypothesis that has had me thinking for a while now.

The default answer people give is “the government”. But Yarvin makes an interesting point. Governments, such as that “beacon of freedom” like America or that reincarnation of evil in Putin’s Russia (quotation marks to make you aware, we’ll get to this later), work very differently, to say a small business. They do what he calls bottom-up decision-making. That is to say, by the time it lands on President Biden or Putin’s desk, it’s because it is escalated as a problem. Or rather, a decision that someone below wanted to avoid making. Meaning a lot of decisions happen by the little people. Governments “leak power”.

So where do the little people who make these decisions get their ideas from?

The Cathedral

Yarvin invokes European medieval trauma by naming these influencers “the Cathedral”. A group of unaccountable thinkers who pass their ideas onto the media and high society for digestion and who then poo it out onto the rest of us to gobble on. Like the Catholic Church of the past, you cannot criticise them (or they will gobble you up).

So who is the Cathedral? Academia comes up with the thought and the media propagates it. People with the profession (or the time) to write and publish opinions. And so drives Yarvin with his authoritarian fan base to an accepted conservative view: blame the universities! Those damn bastions of lefty talk. In America, this is the source of the culture war or at least where pronouns are defined. In Russia, Alexander Dugin has been called Putin’s brain, and his work lays out Eurasia’s remaking of the world order that is shifting before our eyes.

But not so fast, Yardin: it takes work to popularise new ideas in universities, and it’s brutal. Something just did not click for me in what is an otherwise thought-provoking analysis of Western society. That’s because experts are people trained in its conventions and practices, meaning new ideas face resistance. How does a professor bootstrap support in their new ideas?

She could write some books. He could donate to some groups and encourage others to support his views. They might tap into a marginalised group and broker their support for this new worldview through their podcast. Google was built on the idea that good ideas get a lot of citations in universities, so likewise, a website with a lot of links should rise to the top of search results. I don’t know the game for how a professor gets their work cited. But I do know how online marketing works and what is the top search result for nearly every topic in the world. 

And click: I finally understood how the Cathedral works.

The editors of human knowledge

Wikipedia is one of the most amazing creations of humankind. Unpaid editors, usually with a pseudonym, write content that synthesises the sum of human knowledge. They do this in two main ways. The first is by curating what academic opinions to include, and the second is the behind-the-scenes discussions that decide what to present, shaping how articles get narrated. It goes deeper than that as well: baked into Wikipedia policies are a set of conventions that reflect a philosophical worldview. For example, the use–mention distinction comes from one of the West’s three main schools of philosophy, an idea that amounts to outright manipulation in my eyes when used for narratives like in the telling of history. (I might write more about that rabbit hole once — or maybe it’s if — I get out of it.)

 

Wikipedia is the 7th most visited website in the world.

Wikipedia has a dynamic process where articles are rewritten, merged, monitored, and reclassified. It embodies the original hypertext vision of Ted Nelson, whereby knowledge is linked. But what’s Wikipedia and the Cathedral have to do with anything?

Because search engines love content with lots of links. (And so does Artificial Intelligence.)

The machines — search engines and AI — are smart. But it’s not so much that they tell us what to think. Instead, what’s happening is that the machines transmit what one group of humans is saying to the other. Those who create and transmit the knowledge and those who search for knowledge—the everyday intellectual who educates their social group. More impactfully, the profession of journalism– underpaid people, on deadlines — trying to whip some knowledge on a topic quickly. According to the Economist, a newspaper whose business model is to be in every dentist’s office, you’d be surprised how many journalists copy content from what they find on the web, especially Wikipedia. That’s to say directly copying; what I’m talking about is even bigger: it’s the indirect impact,

Play it again, Sam

If I lost you, let’s play this out in sequence.

Step one: The academics produce and publish the ideas in books and journals. “America is a beacon.” Check.

Step two: Wikipedia’s community cherry-picks the knowledge by adding it randomly or through intense debates behind the scenes reverting someone’s edit. “America is a beacon that has consensus by people we deem to matter”. Check.

Step three and four: Search engines capture Wikipedia on any topic journalists use for background reading, and it narrates their writing. “America, widely accepted as a beacon…”

Steps 5 to 89: The content journalists generate transmits to dentists, government administrative staff, and beyond where pictures of beacons bamboozle the public. People talk about it on social media (“beacon! beacon! beacon!) and the media keeps talking about it, which feeds the academics to keep writing and shifting their practices that define the standards (“We evaluated 112 studies in pre-prints and with a badass new regression model have determined beacon is what fly-eating plants imply when prodded to describe America’s free society”). And like a virtuous cycle, these ideas eventually morph into the new conventions of the day. With the Wikipedia editors ready to upgrade it from a footnote to a lead sentence. And when the deputy assistant of forms uses a search engine, they see all the results with a concise, authoritative summary from Wikipedia, giving them the confidence to use beacon.

It’s a process. The sausage does not get made overnight. But that, in my unprofessional opinion, is how we get told what to think as free citizens of democracies. What’s my advice for the next time you see a weird question appear on a form?

Yell out the word beacon. It may make you feel better.

Explaining APML: what it is & why you want it

Lately there has been a lot of chatter about APML. As a member of the workgroup advocating this standard, I thought I might help answer some of the questions on people’s minds. Primarily – “what is an APML file”, and “why do I want one”. I suggest you read the excellent article by Marjolein Hoekstra on attention profiling that she recently wrote, if you haven’t already done so, as an introduction to attention profiling. This article will focus on explaining what the technical side of an APML file is and what can be done with it. Hopefully by understanding what APML actually is, you’ll understand how it can benefit you as a user.

APML – the specification
APML stands for Attention Profile Markup Language. It’s an attention economy concept, based on the XML technical standard. I am going to assume you don’t know what attention means, nor what XML is, so here is a quick explanation to get you on board.

Attention
There is this concept floating around on the web about the attention economy. It means as a consumer, you consume web services – e-mail, rss readers, social networking sites – and you generate value through your attention. For example, if I am on a Myspace band page for Sneaky Sound System, I am giving attention to that band. Newscorp (the company that owns MySpace) is capturing that implicit data about me (ie, it knows I like Electro/Pop/House music). By giving my attention, Newscorp has collected information about me. Implicit data are things you give away about yourself without saying it, like how people can determine what type of person you are purely off the clothes you wear. It’s like explicit data – information you give up about yourself (like your gender when you signed up to MySpace).

Attention camera

I know what you did last Summer

XML
XML is one of the core standards on the web. The web pages you access, are probably using a form of XML to provide the content to you (xHTML). If you use an RSS reader, it pulls a version of XML to deliver that content to you. I am not going to get into a discussion about XML because there are plenty of other places that can do that. However I just want to make sure you understand, that XML is a very flexible way of structuring data. Think of it like a street directory. It’s useless if you have a map with no street names if you are trying to find a house. But by having a map with the street names, it suddenly becomes a lot more useful because you can make sense of the houses (the content). It’s a way of describing a piece of content.

APML – the specification
So all APML is, is a way of converting your attention into a structured format. The way APML does this, is that it stores your implicit and explicit data – and scores it. Lost? Keep reading.

Continuing with my example about Sneaky Sound System. If MySpace supported APML, they would identify that I like pop music. But just because someone gives attention to something, that doesn’t mean they really like it; the thing about implicit data is that companies are guessing because you haven’t actually said it. So MySpace might say I like pop music but with a score of 0.2 or 20% positive – meaning they’re not too confident. Now lets say directly after that, I go onto the Britney Spears music space. Okay, there’s no doubting now: I definitely do like pop music. So my score against “pop” is now 0.5 (50%). And if I visited the Christina Aguilera page: forget about it – my APML rank just blew to 1.0! (Note that the scoring system is a percentage, with a range from -1.0 to +1.0 or -100% to +100%).

APML ranks things, but the concepts are not just things: it will also rank authors. In the case of Marjolein Hoekstra, who wrote that post I mention in my intro, because I read other things from her it means I have a high regard for her writing. Therefore, my APML file gives her a high score. On the other hand, I have an allergic reaction whenever I read something from Valleywag because they have cooties. So Marjolein’s rank would be 1.0 but Valleywag’s -1.0.

Aside from the ranking of concepts (which is the core of what APML is), there are other things in an APML file that might confuse you when reviewing the spec. “From” means ‘from the place you gave your attention’. So with the Sneaky Sound System concept, it would be ‘from: MySpace’. It’s simply describing the name of the application that added the implicit node. Another thing you may notice in an APML file is that you can create “profiles”. For example, the concepts about me in my “work” profile is not something I want to mix with my “personal” profile. This allows you to segment the ranked concepts in your APML into different groups, allowing applications access to only a particilar profile.

Another thing to take note of is ‘implicit’ and ‘explicit’ which I touched on above – implicit being things you give attention to (ie, the clothes you wear – people guess because of what you wear, you are a certain personality type); explicit being things you gave away (the words you said – when you say “I’m a moron” it’s quite obvious, you are). APML categorises concepts based on whether you explicitly said it, or it was implicitly determined by an application.

Okay, big whoop – why can an APML do for me?
In my eyes, there are five main benefits of APML: filtering, accountability, privacy, shared data, and you being boss.

1) Filtering
If a company supports APML, they are using a smart standard that other companies use to profile you. By ranking concepts and authors for example, they can use your APML file in the future to filter things that might interest you. As I have such a high ranking for Marjolein, when Bloglines implements APML, they will be able to use this information to start prioritising content in my RSS reader. Meaning, of the 1000 items in my bloglines reader, all the blog postings from her will have more emphasis for me to read whilst all the ones about Valleywag will sit at the bottom (with last nights trash).

2) Accountability
If a company is collecting implicit data about me and trying to profile me, I would like to see that infomation thank you very much. It’s a bit like me wearing a pink shirt at a party. You meet me at a party, and think “Pink – the dude must be gay”. Now I am actually as straight as a doornail, and wearing that pink shirt is me trying to be trendy. However what you have done is that by observation, you have profiled me. Now imagine if that was a web application, where this happens all the time. By letting them access your data – your APML file – you can change that. I’ve actually done this with Particls before, which supports APML. It had ranked a concept as high based on things I had read, which was wrong. So what I did, was changed the score to -1.0 for one of them, because that way, Particls would never show me content on things it thought I would like.

3) Privacy
I joined the APML workgroup for this reason: it was to me a smart away to deal with the growing privacy issue on the web. It fits my requirements about being privacy compliant:

  • who can see information about you
  • when can people see information about you:
  • what information they can see about you

The way APML does that is by allowing me to create ‘profiles’ within my APML file; allowing me to export my APML file from a company; and by allowing me to access my APML file so I can see what profile I have.

drivers

Here is my APML, now let me in. Biatch.

4) Shared data
An APML file can, with your permission, share information between your web-services. My concepts ranking books on Amazon.com, can sit alongside my RSS feed rankings. What’s powerful about that, is the unintended consequences of sharing that data. For example, if Amazon ranked what my favourite genres were about books – this could be useful information to help me filter my RSS feeds about blog topics. The data generated in Amazon’s ecosystem, can benefit me and enjoy a product in another ecosystem, in a mutually beneficial way.

5) You’re the boss!
By being able to generate APML for the things you give attention to, you are recognising the value your attention has – something companies already place a lot of value on. Your browsing habits can reveal useful information about your personality, and the ability to control your profile is a very powerful concept. It’s like controlling the image people have of you: you don’t want the wrong things being said about you. 🙂

Want to know more?
Check the APML FAQ. Othersise, post a comment if you still have no idea what APML is. Myself or one of the other APML workgroup members would be more than happy to answer your queries.

Don’t get the Semantic Web? You will after this

Prior to 2006, I had sort of heard of the Semantic Web. To be honest, I didn’t know much – it was just another buzzword. I’ve been hearing about Microformats for years, and cool but useless initiatives like XFN. However to me it was simply just another web thing being thrown around.

Then in August 2006, I came across Adrian Holovaty’s article where he argues journalism needs to move from a story-centric world to a data-centric world. And that’s when it dawned on me: the Semantic web is some serious business.

I have since done a lot of reading, listening, and thinking. I don’t profess to be a Semantic Web expert – but I know more than the average person as I have (painfully) put myself through videos and audios of academic types who confuse the crap out of me. I’ve also read through a myriad of academic papers from the W3C, which are like the times when you read a novel and keep re-reading the same page and still can’t remember what you just read.

Hell – I still don’t get things. But I get the vision, so that’s what I am going to share with you now. Hopefully, my understanding will benefit the clueless and the skeptical alike, because it’s a powerful vision which is entirely possible

1) The current web is great for humans; useless for machines
When you search for ambiguous terms, at best, search engines can algorithmically predict some sort of answer that partially answers your query. Sometimes not. But the complexity of language, is not something engineers can engineer to deal with. After all, without ambiguity of natural languages, the existence of poetry is impossible.

Fine.

What did you think when you read that? As in: “I’ve had it – fine!” which is like another way of saying ok or agreeing with something. Perhaps you thought about that parking ticket I just got – illegal parking gets you fined. Maybe you thought I am applauding myself by saying that was one fine piece of wordcraftship I just wrote, or said in another context, like a fine wine.

Language is ambiguous, and depending on the context with other words, we can determine what the meaning of the word is. Search start-up company Powerset, which is hoping to kill Google and rule the world, is employing exactly this technique to improve search: intelligent processing of words depending on context. So by me putting in “it’s a fine”, it understands the context that it’s a parking ticket, because you wouldn’t say “it’s a” in front of ‘fine’ when you use it to agree with something (the ‘ok’ meaning above).

But let’s use another example: “Hilton Paris” in Google – the worlds most ‘advanced’ search engine. Obviously, as a human reading that sentence, you understand because of the context of those words I would like to find information about the Hilton in Paris. Well maybe.

Let’s see what Google comes up with: Of the ten search results (as of when I wrote this blog posting), one was a news item on the celebrity; six were on the celebrity describing her in some shape or form, and three results were on the actual Hotel. Google, at 30/70 – is a little unsure.

Why is Paris Hilton, that blonde haired thingy of a celebrity, coming up in the search results?

Technologies like Powerset apparently produce a better result because it understands the order of the words and context of the search query. But the problem with these searches, isn’t the interpretation of what the searcher wants – but also the ability to understand the actual search results. Powerset can only interpret so much of the gazilions of words out there. There is the whole problem of the source data, no just the query. Don’t get what I mean? Keep reading. But for now, learn this lesson

Computers have no idea about the data they are reading. In fact, Google pumping out those search results is based on people linking. Google is a machine, and reads 1s and 0s – machine language. It doesn’t get human language

2) The Semantic web is about making what human’s read, machine readable
Tim Berner’s Lee, the guy that invented the World Wide Web and the visionary behind the Semantic Web, prefers to call it the ‘data web’. The current web is a web of documents – by adding this extra data to content – machines will be able to understand it. Metadata, is data about data.

A practical outcome of having a semantic web, is that Google would know that when it pulls up a web page regardless of the context of the words – it will understand what the content is. Think of every word on the web, being linked to a master dictionary.

The benefit of the semantic web is not for humans – at least immediately. The Semantic Web is actually pretty boring with what it does – what is exciting, is what it will enable. Keep reading.

3) The Semantic web is for machines to interpret, not people
A lot of the skeptics of the semantic web, usually don’t see the value of it. Who cares about adding all this extra meta data? I mean heck – Google still was able to get the website I needed – the Hilton in Paris. Sure, the other 60% of the results on that page were irrelevant, but I’m happy.

I once came across a Google employee and he asked “what’s the point of a semantic web; don’t we already enough metadata?” To some extent, he’s right – there are some websites out there that have metadata. But the point of the semantic web is so that machines once they read the information, can start thinking like how a human would and connecting it to other information. There needs to be across the board metadata.

For example, my friend Michael was recently looking to buy a car. A painful process, because there are so many variables. So many different models, different makes, different dealers, different packages. We have websites, with cars for sale neatly categorised into profile pages saying what model it is, what colour it is, and how much. (Which may I add, are hosted on multiple car sites with different types of profiles). A human painfully reads through these profiles, and computes as fast as a human can. But a machine can’t read these profiles.

Instead of wasting his (and my) weekends driving around Sydney to find his car, a machine could find it for him. So, Mike would enter his profile in – what he requires in a car, what his credit limit is, what his prior history with cars are – everything that would affect his judgement of a car. And then, the computer can query every online website with cars to match the criteria. Because the computer can interpret these websites across the board, it can evaluate and it can go back to Michael and say “this is the car for you, at this dealer – click yes to buy”.

The semantic web is about giving computers the information to be able to interpret data, so that it can do what they do really well – compute.

4) A worldwide database
What essentially Berner’s Lee envisions, is turning the entire world wide web into a database that can be queried. Currently, the web looks like Microsoft Word – one swab of text. However, if that swab of text was neatly categorised in an Excel spreadsheet, you could manipulate that data and do what you please – create reports, reorder them, filter, and do whatever until your heart is content.

At university, I was forced to do an Information Systems subject which was essentially about the theory of databases. Damn painful. I learned only two things from that course. The first thing was that my lecturer, tutor, and classmates spoke less intelligible English than a caterpillar. But the second thing was that I learned what information is and how it differs from data. I am now going to share with you that lesson, and save you three months of your life.

You see, data is meaningless. For example, 23 degrees is data. On its own, it‚Äôs useless. Another piece of data in Sydney. Again, – useless. I mean, you can think all sorts of things when you think of Sydney, but it doesn‚Äôt have any meaning.

Now put together 23 degrees and Sydney, and you have just created information. Information is about creating relationships between data. By creating a relationship, an association, between these two different pieces of data – you can determine it’s going to be a warm day in Sydney. And that is what information is: Relationship building; connecting the dots; linking the islands of data together to generate something meaningful.

The semantic web is about allowing computers to be able to query the sum of human knowledge like one big database to generate information

Concluding thoughts
You are probably now starting to freak out and think “Terminator” images with computers suddenly erupting form under your computer desk, and smashing you against the wall as a battle between humans and computers begins. But I don’t see it like that.

I think about the thousands of hours humans spend trying to compute things. I think of the cancer research, whereby all this experimentation occurring in labs, is trying to connect new pieces of data with old data to create new information. I think about computers being about to query the entire taxation legislation to make sure I don’t pay any tax, because it knows how it all fits together (having studied tax, I can assure you – it takes a lifetime to only understand a portion of tax law). In short, I understand the vision of the Semantic web as a way of linking things together, to enable computers to compute – so that I can sit on my hammock drinking my beer, as I can delegate the duties of my life to the machines.

All the semantic web is trying to do, is making sure everything is structured in a consistent manner, with a consistent dictionary behind the content, so that a machine can draw connections. As Berner’s Lee said on one of the videos I saw: “it’s all about creating links”.

The process to a Semantic Web is boring. But once we have those links, we can then start talking about those hammocks. And that’s when the power of the internet – the global network – will really take off.

Facebook is doing what Google did: enabling

The hype surrounding the Facebook platform has created a frenzy of hype – on it being a closed wall, on privacy and the right to users having control of their data, and of course the monetisation opportunities of the applications themselves (which on the whole, appear futile but that will change).

We’ve heard of applications becoming targeted, with one (rumoured) for $3 million – and it has proved applications are an excellent way to acquire users and generate leads to your off-Facebook website & products. We’ve also seen applications desperately trying to monetise their products, by putting Google Ads on the homepage of the application, which are probably just as effective as giving a steak to a vegetarian. The other day however was the first instance where I have seen a monetisation strategy by an application that genuinely looked possible.

It’s this application called Compare Friends, where you essentially compare two friends on a question (who’s nicer, who has better hair, who would you rather sleep with…). The aggregate of responses from your friends who have compared you, can indicate how a person sits in a social network. For example, I am most dateable in my network, and one of the people with prettiest eyes (oh shucks guys!).

The other day, I was given an option to access the premium service – which essentially analyses your friends’ responses.

compare sub

It occurred to me that monetisation strategies for the Facebook platform are possible beyond whacking Google Adsense on the application homepage. Valuable data can be collected by an application, such as what your friends think of you, and that can be turned into a useful service. Like above, they offer to tell you who is most likely to give you a good reference – that could be a useful thing. In the applications current iteration, I have no plans to pay 10 bucks for that data – but it does make you wonder that with time, more sophisticated services can be offered.

Facebook as the bastion of consumer insight

On a similar theme, I did an experiment a few months ago whereby I purchased a facebook poll, asking a certain demographic a serious question. The poll itself revealed some valuable data, as it gave me some more insight into the type of users of Facebook (following up from my original posting). However what it also revealed was the power of tapping into the crowd for a response so quickly.
clustered yes
Seeing the data come in by the minute as up to 200 people took the poll, as a marketer you could quickly gauge how people think about something in a statistically valid sample, in literally hours. You should read this posting discussing what I learned from the poll if you are interested.

It’s difficult to predict the trends I am seeing, and what will become of Facebook because a lot could happen. However one thing is certain, is that right now, it is a highly effective vehicle for individuals to gain insight about themselves – and generating this information is something I think people will pay for if it proves useful. Furthermore, it is an excellent way for organisations to organise quick and effective market research to test a hypothesis.

The power of Facebook, for external entities, is that it gives access to controlled populations whereby valuable data can be gained. As the WSJ notes, the platform has now started to see some clever applications that realise this. Expect a lot more to come.

Facebook is doing what Google did for the industry

When Google listed, a commentator said this could launch a new golden age that would bring optimism not seen since the bubble days to this badly shaken industry. I reflected on that point he made to see if his prophesy would come true one day. In case you hadn’t noticed, he was spot on!

When Google came, it did two big things for the industry

1) AdSense. Companies now had a revenue model – put some Google ads on your website in minutes. It was a cheap, effective advertising network that created an ecosystem. As of 30 June 2007, Google makes about 36% of their revenue from members in the Google network – meaning, non-Google websites. That’s about $2.7 billion. Although we can’t quantify how much their partners received – which could be anything from 20% to 70% (the $2.7 billion of course is Google’s share) – it would be safe to say Google helped the web ecosystem generate an extra $1 billion. That’s a lot of money!

2) Acquisitions. Google’s cash meant that buyouts where an option, rather than IPO, as is what most start-ups aimed for in the bubble days. In fact, I would argue the whole web2.0 strategy for startups is to get acquired by Google. This has encouraged innovation, as all parties from entrepreneurs to VC’s can make money from simply building features rather than actual businesses that have a positive cashflow. This innovation has a cumulative effect, as somewhere along the line, someone discovers an easy way to make money in ways others hadn’t thought possible.

Google’s starting to get stale now – but here comes Facebook to further add to the ecosystem. Their acquisition of a ‘web-operating system‘ built by a guy considered to be the next Bill Gates shows that Facebook’s growth is beyond a one hit wonder. The potential for the company to shake the industry is huge – for example, in advertising alone, they could roll out an advertising network that takes it a step further than contextual advertising as they actually have a full profile of 40 million people. This would make it the most efficient advertising system in the world. They could become the default login and identity system for people – no longer will you need to create an account for that pesky new site asking you to create an account. And as we are seeing currently, they enable a platform the helps other businesses generate business.

I’ve often heard people say that history will repeat itself – usually pointing to how 12 months ago Myspace was all the rage: Facebook is a fad, they will be replaced one day. I don’t think so – Facebook is evolving, and more importantly is that it is improving the entire web ecosystem. Facebook, like Google, is a company that strengthens the web economy. I am probably going to hate them one day, just like how my once loved Google is starting to annoy me now. But thank God it exists – because it’s enabling another generation of commerce that sees the sophistication of the web.

John Hagel – What do you think is the single most important question after everything is connected?

I recently was pointed to a presentation of John Hagel who is a renowned strategy consultant and author on the impact the Internet has on business. He recently joined Deloitte and Touche, where he will head a new Silicon Valley research institute. At the conference (Supernova 2007), John outlined critical research questions regarding the future of digital business that remain unresolved, which revolved around the following:

What happens after everything is connected? What are the most important questions?

I had to watch the video a few times because its not possible to capture everything he says in one hit. So I started writing notes each time, which I have reproduced below to help guide your thoughts and give a summary as you are watching the presentation (which I highly recommend).

I also have discovered (after writing these notes – damn it!) that he has written his speech (slightly different however) and posted it on his blog. I’ll try and reference my future postings on these themes here, by pinging or adding links to this posting.
Continue reading

BarCampSydney2

Things I learned at this BarCamp

  • It was a very different crowd from the first one.
  • It’s so easy to network – it was as difficult as breathing in, breathing out! I gave a presentation, and as a consequence, I had people throughout the day approach me and introduce themselves.
  • In the morning, collaboration was a bit of a hot theme. John Rotenstein from Atlassian asked the question of how do people define collaboration: “when two or more people work together on a business purpose”, was my answer. We agreed. Everyone else, kind of didn’t.
  • How to raise money – was the afternoon’s theme. Great points were brought up by Marty Wells, Mike Canon-Brookes and Dean McEvoy who led the discussion.
  • Some things mentioned:
  1. Aussie VC’s lead you on. “Nice idea- let’s keep in touch” is their way of not burning bridges
  2. VC’s work in a cycle that are in five or so year cycles – raise money at the beginning of the cycle
  3. Rule of thumb: give 30% away on the first round, 30% on the second round
  4. Advisor’s that give out Comet grants work on a 2% commission of future venture capital that you raise.
  5. No one understands the advertising market – everyone in the room wanted something they could read to learn more (check back here soon – I promise!). For example, Google’s adwords programme is largely supported by the property market – the mortgage lending market that is affected by the current credit crisis, is going to affect start-ups relying on adsense as the money drops out of these ads.
  • I met Jan Devos, who randomly approached me and blew me away with what he has done in his life. Basically (and from the age of 17), he created an implementation of the MPEG4 compression technology (for non-tech readers – MP4 as opposed to the older MP3) and he licenses out the technology to major consumer appliance companies like Samsung, who incorporate the technology into their products.
  • I met Dave O’Flynn – self-described as a “tall Irish red-head” developer; Matt June – a former Major in the Australian military, and now pursuing a project based around social innovation; I discovered Rai of Tangler is a commitmentphobe; Mick thinks he can skip most of BarCamp because he thinks organising a wedding is so hard; Mike Canon-Brookes over beer revealed he is a Mark Zuckerberg wannabe; and Christy Dena one of the lead (un)organisers of the conference looks completely different from the person I thought she was!

I got a positive reaction to my half hour session on five lessons I have learned on successful intrapreneurship due to a large internal project I started at my employer, with people throughout the day getting into a chat with me about it. Richard Pendergast, who is starting a online parenting site, said he was going to write a blog on one the points with his own personal battle of creating credibility. Glad I helped! I said to him I was going to blog what I talked about it so we could turn it into a discussion, but I have decided, this exam I have to sit in 12 8 days might need to start getting my attention. Anyway, here were the five points I made, however given the discussion during the session by everyone, is a very rough framework as people brought up some great points when talking:

1) It is a lot easier to seek forgiveness, than permission when doing something in an organisation. Or in other words, just do it.

2) Be proactive, never reactive. By pushing the agenda, you are framing the agenda for something that works for your project. Once you start reacting to others, your idea will die.

3) The more you let go – the bigger your idea will get. Use other people to achieve your vision. Give other people a sense of ownership in it. Let them take credit.

4) It’s all about perception. It’s amazing how much credibility you can build by simply associating your idea to other things – and which in the process, builds your own personal brand to push through with more later on.

5) Hype build hype. Get people excited, and they will carry your idea forward. People get excited when you communicate the potential, and have them realise it.

Thank you to all those involved – both the organisers and the contributors – and I look forward to the next one.

A casual chat with a media industry insider

Today I had the chance of picking the mind of Achilles from the International Herald Tribune, who last year was appointed Vice-President, circulation and development. Achilles is a family friend and I took the opportunity to talk to him about the world of media and the challenges being faced.

The IHT is one of the three daily financial newspapers of the world, along with the Wall Street Journal and the Financial Times. It is currently owned by the New York Times, and has a global circulation of 240,000 people. I had a great chat on a lot of different themes which could have me blog about for a week straight, but here are some of the facts I picked up from our discussion, which I will summarise below as future talking points:

  • On Murdoch’s acquisition of the Wall Street Journal: “very interested to see if he will remove the paid wall”.
  • The IHT experiemented with a paid wall for it’s opinion content, but they will be removing that later this year
  • He says the Bancroft family sold it because they are emotionally detached from the product. It was just an asset to them.
  • A lot of the content is simply reedited content from the NYT and internationalising it. For example, replacing sentences like “Kazakhstan in the size of New York state” doesn’t work well for an international reader who has no idea how big New York state is.
  • On the threat of citizen journalism with traditional media: “they are a competitive threat because we are competing for the same scarce resource: the attention of readers”
  • The problem with citizen journalism and bloggers is the validity of their information – behind a newspapers brand, is trust from readers of the large amounts of research and factchecking that occur. They have no credibility.
  • A blog may develop credibility with an audience greater than the New York Times. But this poses problems for advertising as advertisers might only advertise because of its niche audience. Blogs are spreading the advertising dollars, which is hurting everyone – it’s become decentralised and that has implications which are problematic.
  • The IHT’s circulation is spread thinly across the world. For example, it has 30,000 readers in France and six in Mauritius.
  • Their target market is largely the business traveller, which has its own unique benefits and problems. For example, a business traveler will read it for two days but when they get back home, they will revert to their normal daily newspaper. It’s not a very loyal reader.
  • Readership is a more important concept than circulation as it tells advertisers how big the actual audience of a publication is. For example, the average newspaper has 2.7 readers per copy. However due to the nature of the IHT’s readers, despite having high circulation, they have low readership.
  • IHT is in a unique position of relying on circulation revenue more than advertising. For example, a normal daily relies on circulation revenue as 20% of its total revenue; the IHT counts on it for 50%.
  • It’s hard to get advertising because a readership of university professors is less desirable than fund managers that might read the WSJ. Advertisers prefer to target key decision makers.
  • It doesn’t rely on classifieds as a revenue source – a key thing hurting the newspaper industry currently.
  • Although they place more reliance on circulation revenue, they still get some good advertising opportunities as a lot of readers are politicians and government decision makers.
  • They get a lot of advertising for fashion
  • Psychographic data is more important to advertisers than circulation and it shows what type of readership a publication has.

Some things will never change: how to create credibility

This weekend in my office with a half dozen colleagues, we toiled away on an (academic) assignment due tonight. When you spend 11 hours in one day around one table, on something that drives you mad – conversation is a aplenty on things not related to what we were doing. And when there as no conversation, procrastination was aplenty with Facebook being the prime culprit amongst all of us.

An interesting scenario happened, which made me revisit something I have long wondered. One of the girls asked how does Facebook make money, and I went on a rant about their $200 million Microsoft deal, how they are heading towards an IPO, and other random facts I just happen to know. They all looked at me stunned, in the sense how could I possibly know such things, and I replied I read a lot – I read a lot of blogs.

“…but how do you know that stuff you are reading is accurate?” with reference to that $200 million that I don’t even know where I read that. The funny thing about the question, is that it’s smart and stupid at the same time. The answer seems too obvious – but it isn’t: how DO I know those facts I stated where true?

Why I bring this up, is because this is an issue I have long tried to come to grips with – what makes information credible? How do you know when you read something on the internet, that it is reliable? The answer is we don’t. Sort of.

This “new media” world isn’t the reason why we have this apparent problem: information credibility has long been an issue, first realised by the citizens of western democracy after the Great War when they recognised newspapers could no longer be taken as fact (due to the propaganda efforts). So its been a problem long before computers and hypertext had even been invented – it’s only that with us being in an Information Age, the quality of information has been under higher scrutiny with its abundance.

How do we know what makes something reliable? Is it some gee-whiz Google algorithm? Perhaps it’s the wisdom of the crowds? Maybe – but there is something else even more powerful that I have to thank Scott Karp for making me realise this, back in the days when he was starting out as a blogger: it’s all about branding.

Why makes an article about the New York Times, more credible than one written by a random student newspaper rag? What makes a high profile author, more credible in what they say, than a random nobody who puts their hand up in a town hall meeting? And going back to the question my colleague asked earlier – how do I know the blogs I am reading have any credibility – over say, something I read in an established newspaper such The Economist?

Simple: branding establishes information credibility. And a brand – for any type of entity be it an individual journalist or a news organisation – is dependent on recognition by others. There could be absolutely no credibility in your information (like Wikipedia) and yet you could have a brand that by default establishes credibility – just like how people regularly cite Wikipedia as a source now, despite knowing it’s inherently uncredible.

The power of branding is that no matter how uncredible you are – your brand will be enough to make anything you say, incredible.

The attention economy needs a consistent base

Okay, enough naval gazing. The journalist in me (by experience), the accountant in me (by education), and the businessman in me (by occupation) is going to synthesise my understanding of the world and propose a new metric for the attention economy. I don’t know the answer yet, but I am going to use this blog to develop my thinking. I can’t promise a solution, however I am sure breaking the issue down into key requirements, assumptions, and needs of what this magical metric is – will add value somewhere for someone.

So let’s start with the most important assumption of all: what are we measuring? As Herbert Simon coined it, and smart guys like Umair, Scott and Chris have extended (at least for my conceptual understanding) – it is called the attention economy. It is important to note however, that the attention economy is an aspect of the Information Sector (see below). And as I described in a previous posting, the attention economy needs a metric for two reasons: monetisation and feedback.


What incorporates the attention economy?
Well, this is a bit like a related problem I had when I first came to grips with what new media was. A few years back, I did some active research trying to understand how a book, a television, a newspaper, and a search engine – could all somehow be classed as “media”. I found my question answered by Vin Crosbie’s manifesto (read this for a recent summary). Take note of what he considers is the key element of new media (the technology aspect).

I am going to propose one of my key assumptions of the future, which will answer this question. It might not happen for another 5, 10 or even 20 years – but I am convinced this is the future. The Internet will act as infrastructure.

I believe the unifying aspect, and the backbone of the attention economy, will be the Internet. All enterprise software, all consumer software, all (distributed) entertainment, all (distributed) communications and all information – will be delivered digitally over the Internet. I think the people at the US Census bureau?Ç? conceptually have already worked this out by defining the information sector of the economy, which classes the above mentioned and more into this one diverse category. The Internet is the enabler of the Information Age, just like how the production line was for the Industrial Age

I’m not saying we are going to live, sleep, and eat on computers in the future. However just think – anything that runs on electricity, can connect to the Internet. And look at the technologies being developed that enable the Internet to live beyond the computer screen like electronic paper and?Ç? dynamic interfaces. Even more powerfully, is that the Internet has brought entire industries to their knees – like the newspaper and music industries – because it is providing a more efficient way of delivering content. If it’s information, communication or entertainment related – then it probably works better in digital format, over the Internet. (Excluding of course the things like theme parks and the like, which are more about physical entertainment and not distributed entertainment like a television programme).

I think this is an important issue to be recognised, that the Internet will the the backbone of the attention economy. By being the core back-end, it means that no matter the output device – whether it is mobile phone, a computer, or a television – it will be providing a consistent delivery mechanism for digital information. For a measurement system to work, it needs to be consistent. The Internet infrastructure will be that consistency. If you can recognise that, then that is a big step forward to solving the issue.

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