The Future Of News (part 3)

In this new supersaturated digital universe of infinite free digital duplication, copies are so ubiquitous, so cheap, free in fact, that the only things truly valuable are those that cannot be copied. The technology is telling us that copies don’t count anymore. To put it simply: When copies are superabundant, they become worthless.

This is an extract from “The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future” by Kevin Kelly. It’s from Chapter 3, “Flowing”. It continues…

Instead, stuff that can’t be copied becomes scarce and valuable. When copies are free, you need to sell things that cannot be copied. Well, what can’t be copied? Trust, for instance. Trust cannot be reproduced in bulk. You can’t purchase trust wholesale. You can’t download trust and store it in a database or warehouse it. You can’t simply duplicate someone’s else’s trust. Trust must be earned, over time. It cannot be faked. Or counterfeited (at least for long).

Since we prefer to deal with someone we can trust, we will often pay a premium for that privilege. We call that branding. Brand companies can command higher prices for similar products and services from companies without brands because they are trusted for what they promise. So trust is an intangible that has increasing value in a copy-saturated world.

There are a number of other qualities similar to trust that are difficult to copy and thus become valuable in this cloud economy. The best way to see them is to start with a simple question: Why would anyone ever pay for something they could get for free? And when they pay for something they could get for free, what are they purchasing? In a real sense, these uncopyable values are things that are “better than free.” Free is good, but these are better since you’ll pay for them.

I call these qualities “generatives.” A generative value is a quality or attribute that must be generated at the time of the transaction. A generative thing cannot be copied, cloned, stored, and warehoused. A generative cannot be faked or replicated. It is generated uniquely, for that particular exchange, in real time. Generative qualities add value to free copies and therefore are something that can be sold. Here are eight generatives that are “better than free.” …


A generic version of a concert recording may be free, but if you want a copy that has been tweaked to sound acoustically perfect in your particular living room—as if it were being performed in your room—you may be willing to pay a lot. You are then not paying for the copy of the concert; you are paying for the generative personalization.

The free copy of a book can be custom edited by the publishers to reflect your own previous reading background. A free movie you buy may be cut to reflect the rating you desire for family viewing (no sex, kid safe). In both of these examples, you get the copy free and pay for personalization.

Aspirin is basically free today, but an aspirin-based drug tailored to your DNA could be very valuable, and expensive.

Personalization requires an ongoing conversation between the creator and consumer, artist and fan, producer and user. It is deeply generative because it is iterative and time-consuming. Marketers call that “stickiness” because it means both sides of the relationship are stuck (invested) in this generative asset and will be reluctant to switch and start over. You can’t cut and paste this kind of depth…


You might be able to grab a popular software application for free on the dark net, but even if you don’t need a manual, you might want to be sure it comes without bugs, malware, or spam. In that case you’ll be happy to pay for an authentic copy. You get the same “free” software, but with an intangible peace of mind. You are not paying for the copy; you are paying for the authenticity. There are nearly an infinite number of variations of Grateful Dead jams around; buying an authentic version from the band itself will ensure you get the one you wanted. Or that it was indeed actually performed by the Dead.

Artists have dealt with this problem for a long time. Graphic reproductions such as photographs and lithographs often come with the artist’s stamp of authenticity—a signature—to raise the price of the copy. Digital watermarks and other signature technology will not work as copy protection schemes (copies are superconducting liquids, remember?), but they can serve up the generative quality of authenticity for those who care…


Deep down, avid audiences and fans want to pay creators. Fans love to reward artists, musicians, authors, actors, and other creators with the tokens of their appreciation, because it allows them to connect with people they admire. But they will pay only under four conditions that are not often met: 1) It must be extremely easy to do; 2) The amount must be reasonable; 3) There’s clear benefit to them for paying; and 4) It’s clear the money will directly benefit the creators.

Every now and then a band or artist will experiment in letting fans pay them whatever they wish for a free copy. This scheme basically works. It’s an excellent illustration of the power of patronage. The elusive connection that flows between appreciative fans and the artist is definitely worth something.

One of the first bands to offer the option of pay-what-you-want was Radiohead. They discovered they made about $2.26 per download of their 2007 In Rainbows album, earning the band more money than all previous albums released on labels combined and spurring several million sales of CDs. There are many other examples of the audience paying simply because they gain an intangible pleasure from it.


The previous generatives resided within creative works. Discoverability, however, is an asset that applies to an aggregate of many works. No matter what its price, a work has no value unless it is seen. Unfound masterpieces are worthless. When there are millions of books, millions of songs, millions of films, millions of applications, millions of everything requesting our attention—and most of it free—being found is valuable. And given the exploding numbers of works created each day, being found is increasingly unlikely.

Fans use many ways to discover worthy works out of the zillions produced. They use critics, reviewers, brands (of publishers, labels, and studios), and increasingly they rely on other fans and friends to recommend the good stuff. Increasingly they are willing to pay for guidance. Not too long ago TV Guide had a million subscribers who paid the magazine to point them to the best shows on TV. These shows, it is worth noting, were free to the viewers. TV Guide allegedly made more money than all three major TV networks it “guided” combined.

Amazon’s greatest asset is not its Prime delivery service but the millions of reader reviews it has accumulated over decades. Readers will pay for Amazon’s all-you-can-read ebook service, Kindle Unlimited, even though they will be able to find ebooks for free elsewhere, because Amazon’s reviews will guide them to books they want to read. Ditto for Netflix. Movie fans will pay Netflix because their recommendation engine finds gems they would not otherwise discover. They may be free somewhere else, but they are essentially lost and buried. In these examples, you are not paying for the copies, you are paying for the findability…


What counts are not the number of copies but the number of ways a copy can be linked, manipulated, annotated, tagged, highlighted, bookmarked, translated and enlivened by other media. Value has shifted away from a copy toward the many ways to recall, annotate, personalize, edit, authenticate, display, mark, transfer, and engage a work. What counts is how well the work flows.

Previous chapter | The next chapter is titled “Screening”.

The Future Of News (part 2)

The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future (by Kevin Kelly). Chapter 2 is about AI:

The AI on the horizon looks more like Amazon Web Services – cheap, reliable, industrial-grade digital smartness running behind everything, and almost invisible except when it blinks off. This common utility will serve you as much IQ as you want but no more than you need. You’ll simply plug into the grid and get AI as if it was electricity. It will enliven inert objects, much as electricity did more than a century past.

Three generations ago, many a tinkerer struck it rich by taking a tool and making an electric version. Take a manual pump; electrify it. Find a hand-wringer washer; electrify it. The entrepreneurs didn’t need to generate the electricity; they bought it from the grid and used it to automate the previously manual. Now everything that we formerly electrified we will cognify.

There is almost nothing we can think of that cannot be made new, different, or more valuable by infusing it with some extra IQ. In fact, the business plans of the next 10,000 startups are easy to forecast: Take X and add AI. Find something that can be made better by adding online smartness to it.

An excellent example of the magic of adding AI to X can be seen in photography. In the 1970s I was a travel photographer hauling around a heavy bag of gear. In addition to a backpack with 500 rolls of film, I carried two brass Nikon bodies, a flash, and five extremely heavy glass lenses that weighed over a pound each. Photography needed “big glass” to capture photons in low light; it needed light-sealed cameras with intricate marvels of mechanical engineering to focus, measure, and bend light in thousandths of a second.

What has happened since then? Today my point-and-shoot Nikon weighs almost nothing, shoots in almost no light, and can zoom from my nose to infinity. Of course, the camera in my phone is even tinier, always present, and capable of pictures as good as my old heavy clunkers. The new cameras are smaller, quicker, quieter, and cheaper not just because of advances in miniaturization, but because much of the traditional camera has been replaced by smartness.

The X of photography has been cognified. Contemporary phone cameras eliminated the layers of heavy glass by adding algorithms, computation, and intelligence to do the work that physical lenses once did. They use the intangible smartness to substitute for a physical shutter. And the darkroom and film itself have been replaced by more computation and optical intelligence to do the work that physical lenses once did. They use the intangible smartness to substitute for a physical shutter. And the darkroom and film itself have been replaced by more computation and optical intelligence. There are even designs for a completely flat camera with no lens at all. Instead of any glass, a perfectly flat light sensor uses insane amounts of computational cognition to compute a picture from the different light rays falling on the unfocused sensor.

Cognifying photography has revolutionized it because intelligence enables cameras to slip into anything (in a sunglass frame, in a color on clothes, in a pen) and do more, including calculate 3-D, HD, and many other options that earlier would have taken $100,000 and a van full of equipment to do. Now cognified photography is something almost any device can do as a side job.

A similar transformation is about to happen for every other X. Take chemistry, another physical endeavor requiring laboratories of glassware and bottles brimming with solutions. Moving atoms—what could be more physical? By adding AI to chemistry, scientists can perform virtual chemical experiments. They can smartly search through astronomical numbers of chemical combinations to reduce them to a few promising compounds worth examining in a lab.

The X might be something low-tech, like interior design. Add utility AI to a system that matches levels of interest of clients as they walk through simulations of interiors. The design details are altered and tweaked by the pattern-finding AI based on customer response, then inserted back into new interiors for further testing. Through constant iterations, optimal personal designs emerge from the AI. You could also apply AI to law, using it to uncover evidence from mountains of paper to discern inconsistencies between cases, and then have it suggest lines of legal arguments.

The list of Xs is endless. The more unlikely the field, the more powerful adding AI will be.

Stay tuned for highlights from Chapter 3! (Chapter 1 highlights here).

The Future Of News according to…

I’m currently reading “The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future”. It’s by Kevin Kelly, founder of Wired magazine and an internet pioneer in the 1980s

It’s brilliant and very relevant to the news industry. Here is a highlight from chapter one.

You are not late

… here is the thing. In terms of the internet nothing has happened yet! The internet is still at the beginning of the beginning… If we could climb into a time machine, journey 30 years into the future, and from that vantage look back to today, we’d realise that most of the greatest products running the lives of citizens in 2050 were not invented until after 2016…

from our perspective now, the greatest online things of the first half of this century are all before us. All these miraculous inventions are waiting for that crazy, no-one-told-me-it-was-impossible visionary to start grabbing the low-hanging fruit – the equivalent of the dot-com names of 1984.

Because here is the other thing the graybeards in 2050 will tell you: Can you imagine how awesome it would have been to be an innovator in 2016? It was a wide-open frontier! You pick almost any category and add some AI to it, put it on the cloud. Few devices had more than one or two sensors in them, unlike the hundreds now. Expectations and barriers were low. It was easy to be the first. And they they would sigh. “Oh, if only we realized how possible everything was back then!”

So the truth: Right now, today, in 2016 is the best time to start up. There has never been a better day in the whole history of the world to invent something. There has never been a better time with more opportunities, more openings, lower barriers, higher benefits/risk ratios, better returns, greater upside than now. Right now, this minute. This is the moment that folks in the future will look back at and day, “Oh, to have been alive and well back then!”

The last 30 years have created a marvelous starting point, a solid platform to build truly great things. But what’s coming will be different, beyond, and other. The things we will make will be constantly, relentlessly becoming something else. And the coolest stuff has not been invented yet.

Today truly is a wide-open frontier. We are all becoming. It is the best time ever in human history to begin.

You are not late.

Chapter 2 talks more about AI. I’ll post a highlight soon…

The smartest book ever?

I’m currently reading Smarter Faster Better by Charles Duhigg. It’s about how individuals and teams can become crazy productive.

It’s brilliant because it summarizes all my favorite books, and also because it’s a gripping collection of stories.

Here are the chapters i’ve read so far…

1. Motivation. What makes the Marines so effective? Drive by Dan Pink and Start With Why by Simon Sinek.

2. Teams. The story behind Saturday Night Live. Social Physics by Alex Pentland.

3. Focus. The nurse’s intuition. Superforecasters by Philip Tetlock.

4. Goal Setting. The Yom Kippur War. Work Rules! by Laszlo Bock.

5. Managing Others. How the FBI solves kidnappings. Agile and Lean.

6. Decision Making. The world’s first female poker champion. The Signal And The Noise by Nate Silver. Thinking, Fast And Slow by Daniel Kahneman.

7. Innovation. How Pixar turned Frozen from a flop into a smash hit. Creativity, Inc and wisdom from Steve Jobs.

8. Absorbing Data. How Cincinnati turned it’s schools around. Lean Startup by Eric Reis.

It even get a dash of Nassim Nicholas Taleb in there somewhere too.

The only big thing it’s missing so far is Made To Stick by the Heath brothers. (The recent People vs OJ Simpson series does a good job of covering that).

What do you think?

SEO has changed: 5 things you need to know

This post is based Quick Sprout’s “7 Obsolete SEO Tactics”. The underlying message: search engines have got way smarter in the last few years. Here are 5 changes you may have missed:

1. Backlinks. The quality of backlinks is more important than the quantity. Relevance matters.

2. Keywords: write for users. Writing keyword-rich text for search engines is counter-productive.

3. Content quality is more important then content quantity. Google’s Panda update started penalizing sites with a high volume of low-quality content.

4. Article quality is more important than article length. Upworthy has shown that articles with minimal text (e.g. 3 sentences) can rank highly. Upworthy focuses on video and images instead.

5. Social media impacts search rankings.


Web Analytics 2.0

I recently stumbled across Web Analytics 2.0 by analytics guru Avinash Kaushik. Here’s the obligatory infographic:

It made me wonder, how much of this do we do at

1. Clickstream. This is provided by the analytics team using Omniture. We have a lot of “event” data as well as the usual page data.

We also have various custom clickstream tools too which are used by the content team.

2. Multiple outcomes analysis. We don’t do much analysis of what leads to shares or follows. There is work to be done here!

3. Experimentation & testing. The dev team does a lot of AB testing. We AB test new features using CheezTest or sometimes Visual Optimizer. The content team AB test headlines.

Experimentation and AB testing has made a big difference🙂

4. Voice of the customer. We do some qualitative guerrilla testing (mainly driven by me). And we have Facebook comments enabled. We used to have a email address that people could contact but it wasn’t overly helpful.

Maybe we should revisit having some sort of “feedback” button, we’ve discussed it before but never implemented one.

5. Competitive intelligence. We’ve done a bit of this. Someone did analysis of content volume vs growth for different sites. I’ve done some basic analysis of competitor image, branding and content strategies.

6. Insights. Our recent “return visits” analysis (top secret) was a good example of pulling together several layers of analytics to offer real insights into user behaviour. Yay!

Overall i think scores ok, but there’s definitely room for improvement. I’d better read more of Web Analytics 2.0!

How the Macintosh was born has this great story about how the Macintosh team was super-charged by the prospect of achieving something great.

“The original Macintosh was designed by a small team that worked long hours with a passionate, almost messianic fervor, inculcated by our leader, Steve Jobs, and the excitement that we felt during its creation shines through in the finished product…

We were excited because we thought we had a chance to do something extraordinary. Most technology development is incremental, but every once in a while there’s an opportunity to make a quantum leap to a whole new level…

the ambiance of the Mac team was spontaneous, enthusiastic and irreverent…

the Mac team was surprisingly egalitarian. Unlike other parts of Apple, which were becoming more conservative and bureaucratic as the company grew, the early Mac team was organized more like a start-up company. We eschewed formal structure and hierarchy, in favor of a flat meritocracy with minimal managerial oversight, like the band of revolutionaries we aspired to be…

At our third retreat in January 1983, Steve reinforced our rebel spirit, which was waning as the team grew larger, by telling us “it’s better to be a pirate than join the navy” (see Pirate Flag).

Enthusiasm is contagious, and a product that is fun to create is much more likely to be fun to use. The urgency, ambition, passion for excellence, artistic pride and irreverent humor of the original Macintosh team infused the product and energized a generation of developers and customers with the Macintosh spirit, which continues to inspire more than twenty years later.”