Marginalia
Traceable to antiquity, the idea of feedback roared to prominence in the 18th century when the Scottish engineer James Watt figured out how to harness the mighty but irregular power of steam. Watt’s steam governor solved the problem of wasted fuel by feeding the machine’s speed back into the apparatus to control it. When the machine ran too fast, the governor reduced the amount of steam fed to the engine. And when it slowed down, the governor could increase the flow of steam to keep the machine’s speed steady. The steam governor drove the Industrial Revolution by making steam power newly efficient and much more potent. Because it could maintain a relatively stable speed, Watt’s steam engine used up to one-third less energy than previous steam-powered engines.
Wiener broadened the definition of feedback, seeing it as a generic “method of controlling a system” by using past results to affect future performance. Any loop that connects past failures and successes to the present performance promises an improved future. But instead of energy, Wiener thought of feedback in terms of information. No matter the machine, Wiener hypothesized, it took in “information from the outer world” and, “through the internal transforming powers of the apparatus,” made information useful. Water flow, engine speed, temperature—all become information.
Positive ratings are a kind of holy grail on sites like Yelp and TripAdvisor, and negative reviews can sink a burgeoning small business or mom-and-pop restaurant. That shift has created a misunderstanding about how feedback works. The original structure of the loop’s information regulation has been lost.
Feedback may matter to the corporations that solicit it, but the nature of the feedback itself—the people who provide it, the relevance of their opinions, and the quality of the information—seems not to matter at all.
Back in the 90’s, John Laws lead an ad campaign for Valvoline. It had the catchphrase of “oil ain’t oil”
[youtube https://www.youtube.com/watch?v=33_dxeRuVHc?controls=0&w=560&h=315%5D
It focused on the supposed quality and excellence of the oil in much the same way as John West did with salmon.
[youtube https://www.youtube.com/watch?v=76ytNbGaX-M?controls=0&w=560&h=315%5D
This focus on quality and excellence had me thinking lately about data and whether in fact ‘data ain’t data’ and that data is not neutral.
In an article for The Atlantic, Megan Ward provides a history of feedback. She touches on the origins associated with improving industrial machine efficiency and focus on finding fault. The problem is that in recent times it has been appropriated as a tool for managing people as a form of human machinery.
Ward explains that this confuses things and in the process we risk making the activity one of noise, rather than any sort of purposeful meaning and change.
I was particularly reminded of this during a recent holiday to Fiji. I had some points of frustration about the place where we stayed and thought that it might be worth providing feedback. However, what I realised the longer I stayed was that such feedback would most likely miss the mark. Rather than improve the experience for others, as I imagined the feedback should, it would more likely be weaponised and lead to worse working conditions for the staff. To put the issues in context, they were each dealt with in a timely manner. In some respects that is all you can ask for. In addition to this, it would take away from what actually made the whole time most hospitable, the people. I decided not to provide feedback.
Another scenario that comes to mind is performance reviews in schools. I remember there was political outrage a few years ago that the vast majority of teachers in Victoria seemingly moved up their increment each year. It was felt by some that the review process was not weeding out under performing teachers. The problem I had then (and have now) is that it is failure for the wrong purpose. Teachers are not steam engines in need of optimisation towards some sort of greatness. Instead, they require feedback and follow-up based on particular contexts and conditions. This is why performance reviews are different to coaching programs. Jon Andrews explains this difference as improvement verses development.
The question that often feels overlooked when it comes to feedback is who or what is it actually for? It is easy enough to collect clicks and likes, but without purpose it can quickly just become noise. Data ain’t data, to treat it so misunderstands its purpose and association with feedback.
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Data Ain’t Data – Reflecting on Feedback by Aaron Davis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Ernie Smith provides a dive into the world of the suggestion box. This seems in contrast to Megan Ward’s investigation of feedback and computational thinking. Smith seems to capture both worlds, however it is confusing as a to whether they are they are actually the same or if feedback is in fact different for different people.