Getting Past the Binary For More Mindful Product Management

What does a robot making coffee have to do with mindful product management?

Have you ever read an article about the latest development in artificial intelligence and felt your heart drop with the prospect of the robot revolution?

Or have you ever found yourself getting immediately excited about what amazing benefits this technology could bring you or humanity in general?

Don’t worry, this isn’t just another article about AI, though I am going to start by referencing a recent notable development in ‘the rise of the robots’ narrative.

At the weekend I watched a short video featuring ‘Figure 01,’ (a robot) making a cup of coffee. What was interesting was that Figure 01 apparently acquired this skill by observing humans, not through direct programming. It also demonstrated the ability to learn from and correct its mistakes which marks a significant advancement in AI’s evolutionary journey.

Now I said this isn’t about AI despite it having AI as the theme. So what is it about?

Well it’s about your reaction to the article.

The Duality of Perception

When you watch the video (or read any article or headline about AI) what’s your response? Is it…

“Oh this is amazing…soon I’ll have my own team of robots working for me to do all my menial manual tasks” ?

Is it

“Oh no…soon I’ll be out of a job and probably a slave to robot overlords” ?

Of course your response may be neither of those but there is a good chance that it will fall either into “this is good” or “this is bad”.

Your reaction, whether it’s awe or apprehension, is more telling than you might realize.

This isn’t limited to AI; our response to any event, be it a project decision or a personal accomplishment, often falls into binary categories: good or bad.

The Role of Interpretation in Mindful Product Management

This tendency to categorise and judge events is essentially a form of cognitive bias and these biases will naturally have an impact on our thoughts and actions both tactically and strategic.

And it’s completely normal.

Research in cognitive psychology reveals that our brains are wired to quickly categorise experiences for efficiency. This tendency, while useful in many situations, can oversimplify complex phenomena like AI. Studies have shown that embracing ambiguity and complexity can lead to better decision-making and problem-solving skills.

In the context of your reaction to AI developments, such as the self-learning capabilities of Figure 01, your cognitive biases – whether optimism or skepticism – play a significant role. These biases are not just fleeting thoughts; they are deeply ingrained in our decision-making which is crucial in mindful product management.

Sometimes, categorising experiences as ‘good’ can uplift our mood and lead to positive outcomes, a phenomenon akin to confirmation bias. Conversely, perceiving something as ‘bad’ might motivate us to improve or seek change. However, this subjective lens can also lead to complacency or distress.

Anyone that’s been on one of my training courses, workshops or had some 1-2-1 coaching with me will have likely heard one of my favourite mantras that I try to remind myself as often as possible.

“It’s not good, it’s not bad, it’s interesting.”

Consider the case of Figure 01 again. If we label it as ‘good,’ we might overlook the complexities and challenges of integrating such technologies into our daily lives. If we deem it ‘bad,’ we risk missing out on the potential benefits and advancements it represents. By approaching it as ‘interesting,’ we maintain an open-minded stance, fostering a more informed and thoughtful dialogue about AI’s role in our future.

Objective Interpretation Examples

Here are a few more examples of a curiosity-based response:

Unexpected Change in Project Scope:

While our initial reaction might be “This is bad; it will disrupt our workflow and delay the project.” An alternative reaction could be “This change is interesting. I wonder what we can learn from this and what it might lead to. Perhaps it’s an opportunity to reassess our priorities and adapt our strategies.”

A Key Team Member Leaving Mid-Project:

It would be understandable to respond with “This is a disaster; not only are we now one team-member down in terms of capacity, it’s going to be tough to replace their knowledge.”

A more objective interpretation could be “This situation is interesting. I wonder what we can learn from this and what it might lead to. Perhaps it’s a chance to redistribute responsibilities, possibly uncovering hidden talents within the team. It might also prompt a review of our knowledge sharing practices.”

Receiving Critical Feedback from Stakeholders:

An instinctive response could be “This is bad; it means we’re not meeting expectations and we’ve lost goodwill with the stakeholders.”. This could lead to a defensive mindset of avoiding more opportunities for disappointing feedback from stakeholders in the future or perhaps trying to win back favour by giving in to requests that don’t make business sense or align with the strategy.

In contrast, taking the “this is interesting” stance could lead us to reflect on the validity of the feedback (feedback is just an opinion after all and our job isn’t to please everyone all the time) and find ways to better handle the whole feedback process.

Benefits of a more curiosity-driven response

Some common benefits of adopting a more objective and neutral response include:

• Enhanced problem-solving
• Improved decision-making
• Greater creativity
• Boosted resilience
• Increased psychological safety

So how about you?

How do you perceive advancements in AI and technology? Do you find yourself leaning towards labelling them as ‘good’ or ‘bad’?

Does that filter through into your work?

How might shifting to an ‘interesting’ perspective change things for you?