There are many frameworks with which to evaluate unintended consequences. So far in my writing here I’ve looked at examples arranged around a theme (species introduction, food, government policy, human behavior etc) where there is a somewhat clear relationship between cause and effect (even if sometimes only in hindsight). I haven’t yet touched frameworks of complexity and won’t do so until I go deeper into more second-order effects.
This week I step back and look at basic categories of unintended consequences and call out potential new areas of exposure to second-order effects.
Unexpected Benefits are, as the name describes, positive yet unplanned outcomes. I position the starting point (“Event”) differently since there was no related goal in these cases. In the chart above, the actual event (A) has happened and later on positive outcome (B) is found.
My earlier post calls into question some common examples of this category, such as no-man’s lands, sunken ships turning into reefs, and drugs producing unexpected benefits. And as we look for them broadly, benefits will always be found. Positive benefits are impossible to not find as long as you think broadly and creatively.
But my question is just how applicable the above common examples are as unexpected benefits. If we understand (or eventually understand) a cause and effect relationship, such as the reclamation of nature over a certain time in a new no-man’s land, then the benefit is predictable and even unavoidable. That doesn’t strike me as an unexpected. The new drug effect from above (where inter-reactions are not yet fully understood) is closer to a good example of this category. See my earlier post for details.
Unexpected Drawbacks occur when an intended change in an item or group leads to a worsening in a different item or group. In the chart above, the goal was to improve (A) and later it is learned that (B) has been made worse.
Some of these drawbacks may be to populations smaller than the beneficiaries. For example, relatively larger passenger populations who benefit from rideshare companies do so while traditional taxi companies and taxi medallion owners suffer.
In addition to these examples, I believe a way to identify potential exposure to an unexpected drawback is to be aware of anything new being done at scale.
An example I have not yet written about is the change in media business models in the last couple decades. In general, in the past, access to national news media was limited and controlled in few popular TV networks and large-scale newspaper syndicates. With online distribution and the scattering of media sources from the above to include blogs, podcasts, social media, and more, the business model now revolves around fomenting arguments and taking sides in order to generate more views and shares, which then fuel ad revenue. Good for the media businesses that can do it, but it seems to be bad for media consumers.
Perverse Results are often the most frustrating category, yet they are common. In the chart above, the goal was to improve (A) but what actually happens is (A) becomes worse.
We’ve discussed this category in deep plow farming and agricultural subsidies, self-defeating prophesies, endangered species regulatory protection, the cobra effect, and more.
I do make the claim that in some situations (the animal examples of the cobra effect, especially) the solution is often built into the problem. In other situations, like in deep plowing, small tests could have prevented widescale adoption, but the issue was political, not scientific (or that science became political).
Exposure to Unintended Consequences
This is a short list of areas where there is potential for unintended consequences (though these have not yet become big problems and I hope they never will). I’ll cover this list and others in more detail in the future.
Autonomous vehicles (AVs). There is an expected class of social changes related to AVs that are linear in nature. That’s the problem with them… Traffic reduction (traffic might actually increase), accident reduction (yet there will then be exposure to systemic risk to hacking or bugs), and more.
Cannabis legalization. If cannabis replaces alcohol as the intoxicant of choice, there will be different effects on health and behavior.
CRISPR, the inexpensive gene editing technology was discovered and developed based on the process certain bacteria use. The potential for second-order effects comes from CRISPR’s low cost and availability and that changes made to organisms’ genes could mean that those changes are passed down to progeny. New unpredictable changes in future organisms could appear.
Drones. As surveillance and military tools, drones change the risks shared between adversaries internationally. What will happen if the same technology is applied domestically in the US or other countries? Will the ease of drone weaponization mean that large outdoor gatherings will not be allowed (at least without anti-drone technology)?
Education. The new need for endowment-building (I earlier did cover university funding as a forward-looking second-order effect) puts universities in a timing trade off (raise money now and potentially deal with more problems later).
Another potential effect: while the increase in STEM education has positive roots, what if the education as delivered actually bores students and turns them off to the sciences? Could STEM education have the reverse effect intended?
Also, the large growth in student loans, now at $1.4 trillion in the US, has the markings of a large potential problem waiting for a spark to set off defaults.
Over-encouragement of startups. In some markets, startups are oversold as good choices for talent. But statistically, most of the time talent will earn less building a startup than working at a growth-stage or stable business. Then again, part of startup compensation comes from feeling excited about your work and the potential for asymmetric payoffs. In many markets, where startups are the most hyped, it is not the founders (who take more of the risk), but others who more regularly benefit. Groups more likely to benefit include investors who can spread their risk around, community organizers who build their own brand, and “sellers of shovels” to the startups themselves. So here the unintended consequence could be that by encouraging more startups, you actually make life more difficult for the startup founders.
OK, we stepped back this week and will be back with a new look at second-order effects next week.