Technogonies

Hesiod’s Theogony (pronounced with a hard “g” as in polygon) describes the origins and genealogies of the Greek gods. [1] By analogy, I’ll use the term technogonies for stories that describe the origins of technology. In traditional myths, technologies come from the gods, who are usually benefactors. In modern stories, tech comes from inside society, although the stories are complicated and sometimes contested.

Scale change and regulatory change

The current and forecast growth in the number of satellite systems is putting strain on how the FCC and other agencies regulate satellites. There’s a lot of talk of regulatory reform, and calls for comprehensive rather than incremental change.

That leads me to wonder: are there instructive precedents where a step change in the scale of an industry or activity forced a complete restructuring of regulation; or conversely, where change in regulation let to a change of scale?  Perhaps there are examples where one might take lessons for the reform of space governance.

The internet is not an ecosystem, but…

The “internet ecosystem” metaphor is ubiquitous; I’ve used it myself, though with some trepidation. I think I can now reconcile why it’s both wrong and useful.

It’s wrong, strictly speaking, since many aspects of the ecosystem-internet mapping are questionable. As I blogged in 2007 about the “business ecosystem” terminology, the validity of the metaphor is undermined by quite a large number of mapping mismatches:

Number: a food web consists of billions of interactions among animals and plants; a business web comprises a relatively small number of companies

Metrics: Biomass a typical rough measure of an ecosystem; does that map to total revenue, profitability, return on investment, or something else?

Topology: An ecosystem is a lossy, one-way energy flow; as each organism is eaten by the next, energy is lost. Business relationships are reciprocal, and generate value.

Time scales: Species change slowly, but companies can change their role in a system overnight through merger, acquisition or divestiture.

Choice: Interactions between firms can be changed by contract, whereas that between species is not negotiable except perhaps over very long time scales by evolution of defensive strategies.

Foresight: Humans are pre-eminent among animals in their ability to anticipate the behavior of other actors, explore counter-factuals, think through What If scenarios, etc. The response of a system containing humans to some change is therefore much more complex than that of a human-free ecosystem. “Dumb” agents in an adaptive system respond to the change; humans respond to how they think other humans will respond to their response to those people’s responses etc.

Goals: Biological systems don’t have goals, but human ones do. There are no regulatory systems external to ecosystems in a state of nature (if such things still exist on this planet), but there are many, such as rule of law and anti-trust, in human markets. Natural processes don’t care about equity or justice, but societies do, and impose them on business systems. If ecosystems were a good model for business networks, there would be no need for anti-trust regulation.

The connotations of the metaphor are also misleading. Ecosystems are often used to connote stability and vibrant self-regulation; in fact, they often suffer catastrophic collapses. Companies are exhorted to invest in their ecosystem with the goal of becoming a keystone species. It’s not clear why they should do so, from the ecosystem perspective: keystone species don’t typically represent a lot of biomass. Their “bottleneck position”, however, is attractive from the perspective of a company that wants to extract rents through market power.

However, the ecosystem concept has gained traction because there is a deeper truth: both the internet and ecosystems are both examples of complex adaptive systems. (A complex adaptive system may be defined as a collection of interacting, adaptive agents; other examples include the immune system, the human body, stock markets, and economies. Note that adaptive systems are often nested.)

Thus, the internet is to an ecosystem as a whale is to an elephant. It could be useful to think in terms of elephants if one has to manage oceans but doesn’t know much about whales, since both are large, social mammals. However, one can just as well explain whales in terms of elephants – and the differences, e.g. living on land vs. in water – can be decisive in some cases.

With this realization, the utility and limitations of using an ecosystem metaphor when thinking about the internet, as I did in my Internet Governance as Forestry paper, have become much clearer to me. Lessons from managed ecosystems can illuminate the dynamics and pitfalls of managing the internet, and principles (such as the Resilience Principles I outlined in my recent talk at Silicon Flatirons; my presentation starts around time code 01:36:00 of the video) derived from one can be applied to the other.

Forever blowing bubbles

In a Wall Street Journal op-ed (PDF) Paul Rubin* suggests that bubbles and crashes are a natural part of capitalist markets. More to the point, the very factors that have recently increased the efficiency of markets – notably the internet – have also facilitated the formation of bubbles.

Technology is double-edged, as always: the internet facilitates both the functioning and malfunctioning of markets. Of course, the difference between function and malfunction is in the eye of the beholder. As John Sterman famously said, “There are no side effects—only effects.”

While this is a perennial problem, the internet may have caused a qualitative change in the degree of interconnection, which leads to significantly less resilience. Note the paradox: The internet is more resilient as a communication system, but it causes the systems that use it to be less resilient.

The corollary is that regulators face an impossible task: one can’t eliminate the downsides of the internet without simultaneously eliminating the benefits.

My study of the complex adaptive systems literature leads to the same conclusion:

• more interconnected systems are less resilient
• crashes are healthy, because they allow new entrants to flourish
• the regulatory task is not to avoid crashes (this just makes the eventual correction worse) but to manage them

As if the regulatory job weren’t tough enough, the political challenge is even harder. “This should never happen again” are the first words out of a politician’s mouth after a catastrophe. That’s what people want to hear, but it’s not realistic – and not desirable either. It will surely happen again, and it’s necessary for renewal and innovation. Managing crashes includes both reducing their severity and mitigating their impacts.

[*] Paul Rubin is a professor of economics and law at Emory University and a senior fellow at the Technology Policy Institute. He served in a senior position in the Federal Trade Commission in the 1980s.