Sawubona

Our culture encourages external validation. School grades, better degrees, promotion, pay rises, likes.

It reinforces a dependency on other people, and often people we would not choose to be dependent on.

Its opposite is internal validation. The stuff of soul and self. The warmth that is generated from doing things we love, that we are striving for mastery in. The knowledge that in some small way, we are making a unique contribution to something that matters to us.

This contribution may never be externally validated, and that doesn’t matter. We know, and our community knows.

There is nothing wrong with external validation, unless it is sought at the expense of internal validation. If that happens, we hollow out and become some sort of zombie.

We are at an important inflection point when it comes to how we work.

The way most businesses are structured creates the conditions that encourage us down the zombie road. When shareholder returns are given not just priority, but near exclusive focus, we end up paying lip service to people’s internal validation.

We talk glibly about “engagement”, but it easily becomes yet another lag indicator like margins, and even if the intent is there we look at the metric not sense the emotion.

We use what psychologists term affective empathy (we get upset when employees get upset) but not cognitive empathy (identifying with and sensing how they feel)

As AI absorbs more and more of the routine work, perceived empathy and humanity becomes ever more critical at every level and boundary-employees, partners, customers and community.

Sawubona. It’s an African Zulu greeting that means “I see you.” It has a long oral history and it means more that our traditional “hello.” It says, “I see your personality. I see your humanity. I see your dignity and respect.”

It resonates rather more than “your call is very important to us”

Sawubona is not a “skill”, it’s a way of being in the world. If we want our businesses to succeed in the world that is emerging, we should learn from that.

Do algorithms need psychotherapists?

I’ve become more and more curious about the power of algorithms. They are wonderful things that can take mind numbing hard work out of routine processes, freeing humans to do more meaningful work.

However.

Who writes the algorithm? When you think about it, whoever writes the algorithm passes on their own worldview, biases, heuristics and experience into eternal digital form. That’s a thought.

Algorithms are normally written by engineers – people with powerful, logical brains, skilled in getting from A to B via the most direct route. It is therefore not too fanciful to imagine that the algorithms they write take on something of their creator’s psyche.

Engineers are vital to our society, and we don’t have enough of them. That said, whilst all are different, software engineers, generally speaking, are not renowned for empathy.

So, if I want to create an algorithm for a customer service interface, who should write it? – somebody with really good programming skills, or somebody with real empathy?

I came across this article from Psychology Today as I explored this idea, and it gave me real pause for thought.

There’s a view that up to half of routine jobs will be replaced by algorithms of various flavours by 2030. That’s (probably) an extreme estimate, but even if only partially correct, we will be replacing flawed, inefficient, but essentially human agents with (by definition) soulless algorithms in significant numbers.

That has potential to create emotional havoc.

There’s a huge opportunity here – to combine digital efficiency with empathy and compassion. It will require however a holistic approach to design – one which better represents the way we work together as humans.

As I’ve explored this area, I’m beginning to understand that just a few seconds working with an unsympathetic (but logically efficient) algorithm can very quickly screw up a potentially good experience and relationship.

The future of brand reputation relies, I suspect, on getting the right balance between the messy human and the efficient algorithm.