How Institutions Must Adapt More Quickly to Our Exponential World

This interesting Wired article ‘The Exponential Age will transform economics forever‘ provides some extracts of Azeem Azhar’s new book ‘Exponential‘. The statement is that the economy and society will be fully transformed by exponential growth of technology – with the risk that institutions, only able to adjust linearly, will lag behind.

Starting with the observation that we are not well geared to understand exponential development (see for example ‘How We Get Always Surprised by Exponential Growth – But We Shouldn’t‘ or ‘The Exponential Deception, or Why We Always Underestimate Incremental Change‘), the author states that economy is going to be transformed by exponential development of new technology and capabilities.

But is exponential growth really new? Looking back at the emergence of new industries in the 19th and 20th century, I am not so sure. Of course what has changed in the last decades is that markets are now global, and the speed of development and spread of new technologies (in years, not decades), but fundamentally this type of development has always been there since the start of the industrial age. Companies that have achieved full dominance of a particular new industry have existed before (Rockefeller – Standard Oil in oil, AT&T in communications…), and institutions have struggled to catch-up (for example with anti-trust laws). The same is happening now, but is it really worse?

The main point made by Azeem Azhar is the difference between ‘linear’ institutions and ‘exponential’ technology and industry growth. This has always existed, and institutions have always caught up, if sometimes a bit too late. Effort will be needed to adapt more quickly, but this remains I believe quite feasible.

We live in an exponential age, full of changes – but that has been the case for last 150 years at least, albeit it happens now more quickly. Institutions will catch up eventually to regulate the new world.

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How Insurance Companies Can Leverage Technology to Control Behaviors

Insurance companies have always influenced behaviors through basic rules underlying their contracts, for exemple historically in terms of fire prevention. There can be a fine line between imposing some rules and actually controlling behavior. In this article ‘Draining the Risk Pool: Insurance companies are using new surveillance tech to discipline customers‘, modern practices of insurance companies are described that border on spying individual behaviors.

The trend is particularly acute in the US where health insurance is provided by private companies. It starts with some shocking statements about examples of companies prohibiting smoking or other possibly health-impacting behaviors because of insurance fees; and other companies promoting health-welness programs which appear to be quite mandatory. “Wellness programs are about exercising that leverage, reducing the risk profile of employees and thus cutting the employer’s costs for health insurance plans.”

However in the modern world, this means using apps and other devices to monitor progress and connect with colleagues, and those could ultimately be used for control purpose. Examples are give, from insurers that require wearing of personal health monitoring devices, or fitting cars with black boxes to determine driving patterns. All leaving to possible insurance access and price discrimination, leading to a much more personalized behavior influence. Boundaries to this approach and rules around fairness will have to be imposed by law.

With the development of personal devices and technology, insurance companies will certainly find a field of improved insight into client behaviors. Lawmakers will have to follow those trends closely to put the right boundaries.

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How Face-to-Face Work is Needed for Innovation

This article ‘New Microsoft Study of 60,000 Employees: Remote Work Threatens Long-Term Innovation‘ provides much food for thought on the limitations of remote work in creative endeavors.

While productivity seems to remain stable or even benefit from remote work in certain areas, creative areas lag behind. “a massive new peer-reviewed study from Microsoft […] found that, while remote work is fine for plowing through day-to-day work, it has the potential to put a serious damper on collaboration and innovation long-term.“

Thus if one’s work is pure production without distraction, remote work is great. If it requires a lot of informal communication and exchange, nothing replaces face-to-face. While this is quite intuitive and not a discovery, the fact that it is described in a peer-reviewed paper enhances the validity of the findings.

“Microsoft CEO Satya Nadella calls this ability of remote work to simultaneously improve heads-down productivity and harm creativity the hybrid work paradox.” 

In a world where most value lies in innovation and creativity, a return to the office is inevitable at least for part of the time, and that’s exactly what most organizations are doing now.

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How We Overvalue Fast-Growth Companies

This article by Tim O’Reilly ‘Two economies. Two sets of rules‘ bounces back on the question about why Elon Muks is so rich to conclude that there are really two different economies: the real economy and the gambling – stock market economy. And betting on the stock market leads to unrealistically high valuations.

In effet, stock valuation today is generally very high, and for some companies like Tesla it is unrealistic by any measure. I also observe this trend in (unlisted) start-up valuation, which are sometimes quite unrealistic – it is very difficult to expect a real economic payback in the foreseeable future.

We also know that the valuation of a company being listed is always significantly higher than when it is privately held – some of it the value of floating shares that can be sold at any moment, and some of it simply the effect of the market and a large number of possible buyers.

This is quite strange because at the same time we always underestimate exponential growth, which is what we could expect in this case ; but we tend to overestimate future company economic return in a situation where demand far exceeds supply of scarce stock or shares. I would tend to agree with Tim O’Reilly that there is an element of irrational gambling behavior in those cases (possibly compounded by the fear of missing out one of life’s greatest opportunities).

Stock market and high-growth start-up valuations being thus generally exaggerated, either one keeps away from it, or one sales before reality catches up again. Those are the only possible strategies!

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How Network Effects Create Negative Marginal Costs

In this post ‘Negative marginal cost‘, Seth Godin highlights that non only digital allows to produce at zero marginal costs, but that when network effects are added, marginal cost can actually be negative.

Negative marginal cost means that it costs more to produce less, or that it costs more to have less people connected and contributing. The network effect being exponential creates situations where the value generated by one additional user actually benefits the community by its presence.

As Seth Godin writes, “Moving from expensive to cheap to free to “it’s a bonus to add one more person” changes our economy and our culture forever.” Zero marginal cost was already the internet revolution; negative marginal cost is the social network revolution.

While this explains the exponential development and success of social networks, it is still useful to remember that internet uses a lot of resources and energy, and I am still not sure whether the marginal cost would remain effectively negative when we add those in – that’s actually quite an interesting research topic.

We always underestimate network effects like we underestimate exponential growth, and they indeed create an advantage to add users. We are just at the beginning of the network revolution!

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How Amazon is Becoming a Very Significant Private Employer

Amazon is expanding and hiring worldwide – and is now employing a sizeable share of the workforce, as underlined in this post ‘Amazon now employs almost 1 million people in the U.S. — or 1 in every 169 workers‘. And actually, global hiring at Amazon continues in an exponential curve.

Distribution businesses have always been very significant employers (such as for example, supermarket chains) because of the labor-intensive nature of their trade. Amazon in the US (1.3 million employees or direct contractors) is on the way to overtake Walmart the first employer (1.6 million).

Those numbers mean that we can expect in the next few years some unionization of the relationships between employees and Amazon (and potentially some struggles too), and also that any decision taken by Amazon HR regarding general policies will have far-ranging effects on local economies. Amazon also certainly is developing its political influence where unemployment is a major local issue.

Amazon will probably soon become the first employer in many countries. This will necessarily change the nature of its social relationships both inside and outside the company.

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How Browser Fact Checker Extensions are Coming

With the spread of fake news, fact checking is becoming a hot subject. In this Gartner blog ‘Fact-checker Extensions Should be Standard on Every Browser‘ a possible evolution of browsers is described where news would be automatically rated according to their truthfulness

“A pop-up warning that a news item or website contains dubious or disputed information will not save us from bad information, but it will at least get people thinking. They will need to make a conscious decision to ignore the warning. Hopefully they will instead consider the links and references provided to more reality-based sources. This is basic digital literacy.“

It happens that many of those plug-ins seem to be already available (at least in English) and some are mentioned in the post. They will provide warnings and truthfulness indexes to sites and news consulted by the user. At least this would prompt verification across sources.

Of course this will not prevent some people from believing that this would be some additional conspiracy preventing them to spread their truth, or people just igniring the warnings. Fake news are not new: what’s new is that they can spread globally and exponentially for zero cost. Identifying fake news is a first step in regaining our freedom.

I am looking forward to good quality fake news checking to become standard. Of course in this weapon race fake news will become better at evading the checks and there will be an ever continuing race to uphold real facts.

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How Deep-fakes Become a Public Concern for Companies

In this interesting post by Darin Stewart ‘Executives Need a Deep-Fake Defense Strategy‘, the issues of deep-fakes being used for fraud are highlighted. Examples show how deep-fakes can induce personnel to believe they are being actually addressed by their CEO and make them commit inappropriate actions.

“AI and machine learning permeate modern business and communications. It should come as no surprise that these technologies are being turned to illicit purposes. Deepfakes are audio, images, and videos that appear real but are actually AI-generated, synthetic creations. They are just the latest manifestation of disinformation in what the RAND Corporation describes as a culture of “truth decay.“

Swindlers may increasingly used those techniques in the future. They may also be used to compromise people and exercise pressure on them, or in public or political settings to destroy the reputation of adversaries.

Therefore, finding ways to detect deep-fakes is becoming an important issue and quite some resources need to be devoted to this challenge. We can expect in the near future to have deep-fake detectors embedded in our communication software. In any case, we need to be ever more watchful for signs of deception in any communication!

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How Content on Any Social Platform Needs to be Curated and Administered

Seth Godin in this post ‘The inevitable decline of fully open platforms‘ shows how fully open platforms (i.e. without any content curation and filtering) fall pray to spammers and inappropriate content. Still, there is also a need to maintain some balance in the administration of the network so as to benefit from its full capability.

“The tension is simple: If a platform is carefully vetted and well-curated, it meets expectations and creates trust. If it’s too locked down and calcifies, it slows progress and fades away. […] Too much curation stifles creativity, opposing viewpoints and useful conversation. But no curation inevitably turns a platform over to quacks, denialists, scammers and trolls.”

Even on private social networks, such as the ones that can be implemented by large organisations, curation and administration is required. This is something that is often forgotten, and it is clear that it can sometimes be seen as purely censorship. The balance needs to be clearly set between removing offensive content and removing content just because it would not please the owners of the network. One does not want to end up like an autocratic regime where any content contrary to the currently acceptable political opinion is removed.

Debate rages whether the Facebooks, twitters and other social networks do curate sufficiently or too much; whether they use enough resources for that. The balance is not easy, but as any social network founder, curation is probably one of the most strategic activities when operating social networks.

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How Engineering Processes Need to Be Upgraded with Digitalization

In engineering circles, an interview of Elon Musk a few months ago has created quite a few ripples. Elon Musk expressed himself about his engineering philosophy, mainly in the context of SpaceX. This article for example summarizes his views: ‘Elon Musk’s Design Process Starts With Making Things ‘Less Dumb’‘

The 5 principles defended by Elon Musk are the following:

  • Make the requirement less dumb
  • Try to delete part of the process and of the design
  • Simplify or optimize (and don’t optimize something that should not exist in the first place!)
  • Accelerate cycle time (but not before you have sorted out the 3 first principles)
  • Automate the design process to move more quickly through the design cycles.

Those principles seem founded quite in common sense, although of course they are very hard to implement as experience shows. In my world of large industrial projects it is a constant battle to try to simplify requirements developed over decades and comprising of layers of knowledge and experience. No surprise that a newcomer like SpaceX can do better without the institutional history.

What I find particularly interesting is the fact that Elon Musk recognizes that automation as a way to accelerate iteration today needs to be an intrinsic part of engineering approaches.

Digitalization provides new possibilities and we definitely need to re-interrogate the traditional engineering processes to take advantage of the new capabilities made available, simplify and produce more straightforward designs.

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How Space Is a New Strategic Field for Big Tech

In this interesting post ‘Big Tech, The New Space Invaders’, Frederic Filloux explains how Big Tech is invading space services with the money and brutality that will change significantly this market.

He describes all the emergence in the field of space-based services and how the GAFA are now launched on a frenzy of acquisitions. “Space has become an inescapable part of their core business of data collection, transfer and processing, with multiple layers of applications, including a growing demand for AI processing.
For the consumers of satellite images and signals — insurance companies, defense, agritech sector, financial services — working in Amazon, Microsoft or Google Cloud environments is almost the natural thing to do as the tools are de facto standards.” For example, ““Amazon played it quite well by offering to the US Geological Survey and NASA to process the huge volume of data generated by its Landsat program. They did it for free in exchange for bulk access to the data. That was meant to be mutually beneficial.”. It was particularly beneficial to Amazon Web Services which is now the standard gateway to access and process satellite data. AWS provides unparalleled storage and computing power with dozens of easy to use applications dedicated to spatial analysis, refined and trained by Landsat’s trove of data“

This of course creates questions about strategic dependence on those strategic services to American companies. According to Frederic Filloux this would also be a strategy aimed at minimizing the impact of the current antitrust drives – making the GAFA indispensable to the US national security.

In any case this is clearly a deeply preoccupying evolution to see space-generated data being increasingly captured by the GAFA and an awakening of governments on the topic would be useful.

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How Mediocre Generalists Could Be Quickly Endangered by AI

In a newsletter, Christopher C Penn (link to his blog Awaken your Superhero) writes about the ‘demise of the T-shaped marketer’ with the argument that AI is eating the concept rapidly – producing quickly mediocre content but thus replacing the generalist aspect.

The ‘T Marketer’ is someone with a vast array of generalist skills and a particularly deep area of specialization. It is widely recognized to be a rare beast – and that such people have a very high value on the market. It is quite rare because it is difficult to be both a strong generalist and a strong specialist as this requires quite different intellectual approaches.

Any way, Christopher C Penn’s point here is that as AI develops (and while it is still producing quite mediocre output), it is much better at bringing together all sorts of information and it thus in competition with the generalist aspect.

“Why does this myth of the T-shaped person endure in marketing and business? The reality is that most of the time, mediocrity is sufficient to get the job done.” “As the line of mediocre output from AI advances, it will do more and more of the mediocre work, the stuff that everyone can do to some degree. That line advances a little more each year; three years ago, natural language generation was in a sorry state of affairs. You wouldn’t even consider using machine outputs for final product. Today, machines can write the same bland press releases humans can, with the same average level of quality. Three years from now? Those machines will probably crank out better blog posts than the average person.” The conclusion would thus be rather to focus on being really good at something special. “Good enough isn’t good enough any more.”

It is quite a good question before I personally strive to achieve something like a T-shaped competency, because I believe complementing deep expertise with the breadth of generalist approach is quite beneficial. The question is really how much generalist thinking can inform and make even better the specialization area. I am convinced that while one must definitely be very good at a narrow domain, keeping a broad overview is still quite essential.

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