Towards intrinsically motivated systems of decision and action

I am going to talk about motivation, and I am going to talk about goal-setting. The two are related, of course. But when we abandon instrumental and deterministic approaches, it gets a little complicated.

(If this post’s title sounds kind of scary, don’t take it too seriously. I invented it while roleplaying an academic, after writing this in one pass.)

1.

Because of my work at Hubbub I read about motivation a lot. I remember during the original gamification debates, a lot was said about intrinsic motivation, and how artificial external incentives actually diminish motivation. The evidence in support of this keeps growing, as described for instance in this recent piece in the New York Times. Here’s a quote:

Helping people focus on the meaning and impact of their work, rather than on, say, the financial returns it will bring, may be the best way to improve not only the quality of their work but also — counterintuitive though it may seem — their financial success.

Self-Determination Theory (SDT) says that a basic human need is to feel autonomous. Extrinsic incentives diminish this sense of autonomy. In a workplace context, I can imagine that a diminished sense of autonomy will lead to diminished motivation to do good work.

I’ve been involved with quite a few workplace “gamification” projects (I continue to dislike the word but I’ll use it here for clarity’s sake). Our biggest challenge was to get clients to decrease the amount of controlling feedback already in place, in stead of adding even more under the guise of “fun”. This is the same thing that Kanaga talks about when he talks about “soft gamification“.

The NYT article also talks about the difference between “internal” versus “instrumental” motives. Internal motives are inherently related to the activity at hand. Instrumental ones are not. They later distinguish internal/instrumental motives from internal/instrumental consequences. If an activity has instrumental consequences, it does not automatically follow that the person engaged in the activity is motivated by them.

Going back to SDT, another need described is competence, the sense of which is increased by offering positive feedback. The study discussed in the NYT article makes the important point that we should be looking for the internal motives people have for engaging in a task, and helping them have a sense of internal consequences. It’s often easier to use instrumental consequences as the basis for our (digital, gamified) positive feedback systems, because they are ofte readily quantifiable, and computers like stuff you can count. But this would actually backfire.

In many ways, I am just rephrasing stuff that has been said much better and more elaborately by Sebastian, and probably also others. But it helps to hash these things out. It makes the concepts stick more.

Let’s shift.

2.

In the land of productivity, goal setting, particularly of the SMART kind, is king. Indeed, in my own practice at Hubbub, one of the things we did when Alper became partner was to adopt Google’s OKR approach to goal setting to help us focus on what we want to achieve, and to provide ourselves with feedback on how we are doing. It’s not perfect, but it works well enough and we continue to use it.

But there’s a danger to goal setting, or maybe a particular kind of goal setting, which is nicely articulated by Scott Adams, of all people, in a blog post titled “Goals vs. Systems“. A quote:

My problem with goals is that they are limiting. Granted, if you focus on one particular goal, your odds of achieving it are better than if you have no goal. But you also miss out on opportunities that might have been far better than your goal. Systems, however, simply move you from a game with low odds to a game with better odds. With a system you are less likely to miss one opportunity because you were too focused on another. With a system, you are always scanning for any opportunity.

Adams talks about setting yourself up to benefit from unexpected outcomes of the things you do. When we plan, and when we set goals, it can be tempting to be very deterministic in our approach. Adams suggests not focusing on goals but in stead creating systems that are generative. When he says systems, I sort of hear him say “habits”.

I think it’s more complicated than abandoning goals, though. Because the kind of systems Adams suggests embracing still serve goals, but like I said, in a less deterministic way. He talks about increasing odds. And I think when he’s thinking about those odds, he also has some potential consequences in mind.

This is basically a Talebian approach to goal-setting. It’s about making what Venkatesh Rao describes as “rich moves” (I can’t find the link to the particular article I had in mind, alas).

The way I think about it for my own practice of goal setting is to keep a loose coupling between the goals I want to achieve and the ways in which I expect to do so. I am basically looking for activities (systems) that get me closer to those goals, without decreasing the possibility of other good things happening too. It’s a game of trade-offs that starts from an acceptance of the unpredictability of reality.

But what about motivation?

3.

This is what I want to think about more. If we accept that motivation is best served by focusing on internal consequences. And if we believe that it is smarter (as in risk-savvy, not as in SMART) to focus on systems in stead of goals, then how do we stay motivated to diligently walk through our systems, in the absence of immediate payoffs, or trackable progress towards a measurable goal?

This is personally relevant for me, as I am trying to get back on the blogging horse (second post of 2015, but it’s already week 4). It is also relevant because I want the OKRs we set at Hubbub to be generative.

Maybe the motivation flowcharts Matt talked about way back when are helpful here. And maybe Sebastian’s engagement loops are also useful. For now, the recipe I will be following for setting up “Adams systems” that are intrinsically motivated looks a little like this:

  • Understand the intrinsic motives for engaging in the activity at hand
  • Determine desired outcomes, both intrinsic and instrumental
  • Brainstorm system-like activities (habits) which increase the chances of these outcomes happening
  • Select the activities which are most likely to have unexpected outcomes (or the least likely to have only expected outcomes)
  • Invent ways of making apparent intrinsic outcomes and reflecting on them
  • Loop back to your intrinsic motives and adjust systems accordingly

It’s a first stab, heavily inspired by Boyd’s OODA-loop, which like I said before I am deeply into at the moment.

Let’s see how it works out, and let me know if it makes sense.

“This game is rigged, man.”

I am going to try my hand at the occasional blogging again. And I have decided to do this not at my tumblr, but back here. It was fine to post things to Tumblr occasionally, but I have started to dislike not having these notes on my own server. And perhaps more importantly, I started to get really annoyed by Tumblr’s lack of a functioning search. So, I’ve imported all the things I posted to Tumblr over the past few years into this blog, and we’ll continue where we left off.

In this first post of the new year, some things related to inequality under late capitalism. To begin with a bit of video from Adam Curtis for Charlie Brooker’s enjoyable end-of-the-year review Wipe 2014.

I was pointed to this by Hans de Zwart and on Twitter I responded that the idea of non-linearity reminds me of the ideas on warfare developed by John Boyd, which I am currently knee-deep in. And Boyd’s ideas of winning by decreasing mismatches between your model of external reality and reality itself while increasing those mismatches for your opponent in turn connects with James C. Scott’s concept of legibility.

Meanhwile, James Bridle has been charting technological infrastructures of control for The Nor, a project commissioned by the Hayward Gallery. The essays James has written on his charting of surveillance cameras, radar and high-frequency trading infrastructure are hugely enjoyable reads because James has gone out there and done the legwork. This isn’t idle theorising, these are ideas grounded in lived experience of today’s reality on the ground. While recounting his experiences tracing these technological infrastructures, James makes many interesting connections to literature, as well as non-obvious observations about how these technologies relate to today’s social injustices. Long story short: you should go and read the lot of them.

Inequality is engineered, and deliberate. It is an arbitraging of social conditions, a perpetuation of the existing situation by those who seek to profit from its differences.

Low Latency, James Bridle

The reason I am blogging these things is that I continue to be interested in new forms of resistance against the non-linear warfare described by Curtis and Bridle’s technologies of control. The first step is to become aware of these strategies, but to return to Boyd, the question then is how to operate in such a way that you can survive on your own terms, by using tempo and agility and basically a better understanding of reality.

To close things off, a few recent things I read which are all about capitalism, and its instrumentalisation of everyday life. First off, Andres O’Hehir on the perceived death of adulthood, a phenomenon which I sort of recognise, and which he aptly describes not as some kind of conscious lifestyle choice or megatrend, but as a thing emerging from the demands put on us by the market and the cultural industry.

The suit-wearing, gin-drinking 35-year-old Organization Man of 1964 and the couch-bound, action-figure-collecting 35-year-old fanboy of 2014 are dialectical mirror images of each other, economic archetypes called forth by their respective eras.

The “death of adulthood” is really just capitalism at work, Andrew O’Hehir

It’s curious to think that “becoming an adult” is something the market does not want you to do.

And finally, two pieces on the sharing economy. One, by Avi Asher-Schapiro, clearly describing how Uber’s blueprint makes the livelihood of workers even more precarious, while at the same time forcing them to tell their customers they love their jobs. The other, by the infamous Evgeny Morozov, rightly points out the sharing economy alleviates some of the pains of living under late capitalism, while doing nothing to solve the root causes of those ails.

But under the guise of innovation and progress, companies are stripping away worker protections, pushing down wages, and flouting government regulations. At its core, the sharing economy is a scheme to shift risk from companies to workers, discourage labor organizing, and ensure that capitalists can reap huge profits with low fixed costs.

There’s nothing innovative or new about this business model. Uber is just capitalism, in its most naked form.

Against Sharing, Avi Asher-Schapiro

There’s no denying that the sharing economy can – and probably does – make the consequences of the current financial crisis more bearable. However, in tackling the consequences, it does nothing to address the causes. It’s true that, thanks to advances in the information technology, some of us can finally get by with less – chiefly, by relying on more effective distribution of existing resources. But there’s nothing to celebrate here: it’s like handing everybody earplugs to deal with intolerable street noise instead of doing something about the noise itself.

Don’t believe the hype, the ‘sharing economy’ masks a failing economy, Evgeny Morozov

I blog these things as a reminder to myself of some of the arguments against the current vogue of digitally mediated service delivery platforms. They can be so seductive and many clients and peers seem blinded by their promises. I am interested in salvaging the good bits of these services, they are after all potentially empowering, while coming up with solutions to the injustices they perpetrate and enlarge.