Of pigs and predictions

The Trump victory has left many of my friends reeling and in disbelief. It has also already brought out criticism of pollsters and polling data. Some sceptical ones go a step further and condemn all prediction makers, and mock machine learning and artificial intelligence. This condemnation is foolish and tantamount to throwing the baby out with the bathwater.

Prediction models turn on data, collected from the right questions being asked of the right statistical sample of people. Reductive questions generate neat data sets which then provide all the right answers.

But as experienced market research people will tell you, far fewer people, than those who enthusiastically nod and say they will purchase a new product, actually do. It is not that people are lying, it is just that human beings tend to give answers to please the asker. On politics and other emotionally charged matters, this tendency to give socially acceptable answers to minimise confrontation is especially pronounced. People also change their minds over time.

If the outcomes of any large exercise, where people actually make active choices, shock us it is worth remembering that the only truth is revealed preference i.e. what our actual choices reveal about our preferences. Human beings do not always seek to maximise utility, often preferring to use simplifying shorthand or heuristics to make decisions. The heuristics could have encoded in them experience and knowledge, as well as prejudices and received wisdom.

The concept of revealed preference is, of course, flawed too. If I pick Candidate A over Candidate B, it does not say I prefer Candidate A, merely that I prefer Candidate A to Candidate B. In the future, if Candidate A is up against Candidate C, I may pick Candidate C not because of Candidate C’s superiority over Candidate A but because my preferences are not immutable. Faced with more than two options, we have a way to simplify the choice for ourselves as well as I have written here.

It may sound nihilistic to suggest predictive modelling is not really reliable. But if we are relying on flawed and mutating preferences, and treating them as immutable truths in our analysis, how can methodologies and predictive models generate anything reliable?

It would be akin to putting lipstick on a pig. We would have used up lipstick but the pig would still be a pig.

In the last UK general elections, the Brexit campaign, and now the US general elections, predictions have failed to, er, predict anything reliable.

It is time we learnt to judge differently — by expanding our comfort zones, by listening more, by asking and seeking to understand more, by being healthily sceptical, and by bringing critical thinking lenses to all those pursuits.

For now, if your side won, good for you. The advice to try and understand the other point of view applies to you too. But if your side didn’t win, dry your eyes, dust yourself up, and go out and talk to someone who is not cohabiting your comfort zone.

The narratives we hear will have rough edges, and not the cleanliness or reductiveness of survey questions. But that texture is the stuff understanding is made of. Less data, more understanding. That is what we need.

Empathy as luxury?

“Empathy is luxury. Think about it. If you have the time to read about other points of view, you have the luxury of time, that you can spend on reading other perspectives and build empathy.”, said my interlocutor, an entrepreneur building a platform for contrarian views. I am paraphrasing a bit but we had been talking about how to break the filter bubble that the liberal metropolitan elite inhabit. Better people than I are already exploring how the word “elite” came to be associated pejoratively with liberal, metropolitan persons.

Research evidence from the USA and the UK however shows us that the poor, who do not have spare time since more time spent working is more money, are more charitable and more community minded. In other words, the poor display more empathy. How can empathy be a “luxury” then?

I believe in the essentialness of empathy though I arrive at it from another perspective.

I see myself as a part of a whole, whether that whole be our neighbourhood or the planet. As such my being empathetic is nothing more than my honouring my self.

She wasn’t convinced.

Further expounding on how I got to this framing of this world, I found that it may have come from imbibing some of the Hinduistic philosophical and cultural values amidst which I grew up in India. The idea of the unity of the macro- and the microcosms of our being is embedded in Aham Brahmasmi, “I am the infinite reality”. The idea is also embedded in the greeting Namaste, “I bow to the divine in you”. The idea of consequentiality of our actions naturally follows, often stated controversially in the western world as “Karma is a bitch”.

It is trivially evident that neither business nor humanity can act as if their shared linkages and connectivity do not matter, and as if they can thrive or even survive without one another.

Both spiritually and rationally, empathy is therefore not a luxury in my view.

The idea of luxury as empathy however appeals to me. More on which, later.

Motivation as a design assumption

Holacracy. MOOCs. Food labels.

Holacracy isn’t working. MOOCs have low completion rates, and an estimated 90% drop-out rate. Food labels to help consumers make informed choices show mixed effectiveness and decidedly no downward impact on public health concerns re obesity.

Other than not working as well as optimistically assumed in their wake, they have one more thing in common.

Their design assumes that people have self-motivation in heaps, and when faced with choices, they draw upon that self-motivation to make the best decisions for themselves.

From organisations, to education, to nutrition and health, the assumption of the “highly motivated and self-interested individual” does not stack up.

The reality is different from the design assumptions made.

As Buffer found out from its year-long no-managers experiment, people were expected to direct and motivate themselves, the lack of managers soon became overwhelming, and an implicit hierarchy emerged nonetheless.

Similarly MOOCs assume that a highly motivated and self-driven student is the only kind around. A self-motivated student will benefit from auto-didactic methods disproportionately more than a peer who isn’t so driven. As a teacher, I can attest to these phenomena too: students have variable levels of motivation, cognition and learning capacity; they may or may not understand the sequentiality of learning certain modules i.e. prior art in a field, which, of course, is more essential in some fields than in others; they may not understand some content and that can be demotivating in itself; they may not have the time or dedication to complete assigned readings; and last but not the least, they will always have have questions and if not, a facilitator teacher can make them question their tightly-held beliefs in a setting that makes them think.

In other words, willpower depletion, by the many demands made on us by life, is a real phenomenon.

The design problem that technology entrepreneurs keep dreaming of does not have to bring about “disruption”. It is more complicated than that.

The design problem is to keep people with varying motivations involved, and progressing.

If at all we achieve step change or “disruption”, the design challenge is to do so the existing tools of facilitation and enabling, along with new tools of technology and emergent social contexts, to address the same problems of variable motivation, cognition, and commitment to learning.

A designer assuming a bottomless pit of self-motivation in its audience sooner than later discovers the ordinariness of the human condition.

The medium is the message

President Obama wrote a piece on Feminism for Glamour magazine.

Curious minds want to know why that specific magazine. Here is whom the magazine is for, according to its owner Conde Nast: “Glamour is for the woman who sets the direction of her own life and lives it to its fullest and chicest. Her point-of-view is unmistakably American, unwavering in its optimism and wide open to the possibilities ahead. The dream job, the perfect look, the right guy: All are in her reach.

How would writing in that magazine ensure the article gets read by men, someone asked. Legit question.

Here is how.

Several media outlets men might read – Vox (under Policy and Politics, no less), New York Times, Rolling Stone, Time, and many others – have picked up and paraphrased the essay’s main ideas for easy reading by men. Obama thus neatly sidestepped men wondering why he is lecturing to them and got a standing ovation from women for his approach as a Dad.

And yet he is getting heard by men, as the conversation on those paraphrased articles shows. Several men are commenting on these paraphrased pieces that while they disagree with Obama politically, as fathers of young women, they agree with him completely on this matter. This is not a surprise. Research evidence shows that when daughters are born, men change their attitudes to traditional gender roles for women. Indeed many young women may be making their dads read the article. There is also the possibility that Hillary Clinton’s popularity among young women could get a boost from this, because he spoke with them but not quite at them by referencing his daughters in the essay.

There is more to this than meets the eye though. More than Obama. More than feminism.

There is a quiet but firm change happening in the magazine world. And so-called millennials are leading it. With guidance and nurture from older, steadier, more experienced hands in the trade.

Here is a Teen Vogue piece on a young woman, presumably a teenager, on how she became a feminist. Here is a piece on how queer identity may make a person a target for violence, and another on how American culture fuels homo and trans phobia.

Glamour and Teen Vogue are not magazines common prejudices about “girlie mags” allow us to expect to do a great job of hosting and enabling such discourse on identity. But they are doing it. Anna Wintour, the tour de force in Conde Nast, is guiding a team of millennials which is doing a great job getting the unfairly reviled younger persons reading serious stuff. In other words, emergent generations are being engaged using old fashioned tools.

Their views have a platform. Their voices are being amplified by “curation” led websites that “grownups” read. Change is quietly happening, while we are too busy stereotyping millennials and younger generations.

The revolution, it is clear, is not being televised.

It is being written and read and discussed on channels that allegedly responsible adults dismiss as pointless, past-it, dying or any number of hand-waving adjectives.

Be there, or be square.

And Obama is no square, as we all know by now.

Towards a multidisciplinary future

Last week, I attended a workshop on movement building for social change.

One of my breakout groups was discussing “shared purpose”. I used the word “asymptote” to make the point that with the best shared purpose, we need to know we only make dents and some progress, and although we never fully bring about the exact change in the exact format we want, the movement gets closer and closer to our purpose over time. It caused some mirth in my breakout group.

Later in the morning, I caught myself likening the ideal scenario of the broadening of the appeal of our vision, our purpose, our movement to “fractalisation“. Both terms were, in my view, efficient, succinct, and the best explanations for what I was aiming to say.

The giggles caused by both set me thinking about the other terms with very specific meaning normally used in maths, physics, communication theory, political science, economics that I often use in specific discussions in business. Some are from secondary school maths and physics, the others from further education. A non-representative list of such words would include vector, variable, f(X), non-trivial, calculus, parametric, SNR (signal to noise ratio), transmission error, attenuation, but also words such as equity which may need to be understood in context.

I asked some of my friends, accomplished in law, business, design and academia, if they found the use of secondary school maths and physics terms odd in a business setting with educated colleagues.

A few admitted they did not know some of the terms. Some friends said they would use plainer words. Another said as a data scientist, she aims not be misunderstood. Yet another, who is the most well-informed social justice aware person I know, pointed out that oversimplification can run the risk of the person oversimplifying being seen in devalued terms. And finally, one friend encouraged me to “go Gurl!” because she is of the view that these terms can often explain business models, industrial design, UX, customer behaviour and other insights well.

I then ran a poll on Twitter and an encouraging 56% of respondents said they understand those terms, and a full 19% said that they would mock such a person.

What the Twitter survey found

What the Twitter survey found

Interesting discussions followed.

Do we mock out of fear instead of curiosity, or do we mock for broader social acceptance rather than standing out as a nerd?

Do we use specific terms to look impressive, or do we actually know what they mean?

Do we use these terms to establish superiority, or to create a shared understanding in the group, explaining with patience and genuine empathy when asked, to move the discussion forward?

Is such language isolating and credentialist, or broadening and embracing of diversity?

Before you dismiss this as an academic navel-gazing exercise, I should add this thinking was propelled by a digital insights event I attended earlier in the week. A futurist on the panel said multidisciplinarity was the future (she also had other predictions about future careers).

If we are to get to that multidisciplinary future, are we really serving ourselves, building our movement, making the right strides toward it, if we like to keep precise terms in their own disciplinary silos behind tightly drawn boundaries?

Why are we not asking to be explained by — and indeed why are we mocking — those, who let these specialty-confined words loose in other contexts, where they may fit and may indeed enrich the shared understanding of what we are building?

History shows that innovation does not always come from those deeply embedded in the specialist disciplinary networks they belong to. It comes from those who are on the edges of their discipline(s), bumping against the others on the edges of their discipline(s), or looking above the parapet to peek into what others are doing, and forming multidisciplinary teams to have a crack at a problem that one discipline alone cannot solve.

Whether leading a team, building a startup, or growing a business. what are you doing to bring that multidisciplinary thinking on board?

How are you building your movement towards the future?