It’s Not Always About Technology
Edition #150
Introduction
Welcome to The ContraMind Code.
The ContraMind Code provides you with a system of principles, signals, and ideas to aid you in your pursuit of excellence.
The newsletter shares the source code through quick snapshots for a systems thinking approach to be the best in what you do.
The Code helps you reboot and reimagine your thinking by learning from the best and enables you to draw a blueprint on what it takes to get extraordinary things done. Please share your valuable thoughts and comments and start a conversation here.
Take a journey to www.contraminds.com. Listen and watch some great minds talking to us about their journey of discovery of what went into making them craftsmen of their profession to drive peak performance.
The Unbelievable Slowness Of Thinking
We always believe we can think fast and sometimes chide ourselves for not being ‘quick-on-our-feet’ in certain situations. We tend to compare ourselves with others when it comes to thinking fast and are always in awe of people who can think at lightning speed to problems posed at them. Do human beings, by nature, think fast? According to a recent article published in Scientific American, some stunning findings question some of these assumptions and beliefs:
According to research published in Neuron, human beings think at a fixed, excruciatingly slow speed of about 10 bits per second—they remember, make decisions and imagine things at that pace.
‘The Musk illusion’: Human sensory systems gather data at about one billion bits per second. This is precisely the opposite of how humans think. This biological paradox contributes to the false feeling that our mind can simultaneously engage in seemingly infinite thoughts—a phenomenon the authors call “The Musk illusion.”
“Nature, it seems, has built a speed limit into our conscious thoughts, and no amount of neural engineering may be able to bypass it,” according to a leading neuroscientist, Tony Zador.
One intriguing question that neuroscientists will need to research, which can fundamentally reshape their work, is, “Why can our peripheral nervous system process thousands of items in parallel, but we can only do one thing at a time?”
You can read the entire article here.
What’s The Difference Between Digital Transformation And AI Transformation?
Buzzwords come and go, but for organisations and their leaders, they represent a significant investment in money and time that cannot be recouped. AI is a big buzzword today, just as digital transformation was significant in the last few years and continues to be one.
Harvard Business School Assistant professors Iavor Bojinov and Edward McFowland III highlight the differences between digital and AI transformation and the challenges companies need to overcome.
Here are some key takeaways:
Digital transformation is where companies move from having an analog workflow to a digital workflow. Digital transformation is really about automating workflows and digitizing manual processes.
AI transformation takes it one step further. It recommends how you should think, act, or analyze something, and it, in fact, shows that what you think may not be the optimal or right way. What AI transformation does is ‘Tell us the objective, not the rules, not the process. The system then figures out what it thinks is the best.’
To get AI transformation right, the first pillar is trust - building trust between AI and humans, the second pillar is building trust with the development team, and the third pillar is the overall process the organization puts in place.
Whether digital or AI transformation, it's about people and getting the culture right. It’s all about change management—‘ Technology is there, people are not.’
You can also listen to this episode on:
Nobel Minds 2024
How would it be to get all Nobel Laureates on one table for a conversation?
This is precisely what happened recently at Nobel Minds 2024. The 2024 laureates in physics, chemistry, medicine, and economic sciences were in conversation with Zeinab Badawi and students in the audience at the Royal Palace in Stockholm.
Here are some interesting takeaways from this conversation with Nobel Laureates:
Their humility will surprise you. Here are some verbatims from the discussions:
Geoffrey Hinton: “The University of Toronto gave me an office… yes, they didn't think I was worth an office before that..”
James Robinson: “People take what I say much more seriously. I've always proceeded on the assumption that no one was ever actually listening..”
Their practical and realistic approach to discoveries can be very refreshing:
David Baker: “Humans, since the beginning of civilization, have created things that are better than them in almost every domain. You know, cars can go infinitely faster, planes can fly, humans can't, you know, for a long time, we've had computers that can do calculations that humans can't do… I think we just take this kind of thing in stride. I don't think we worry about losing control, so I guess that's the key..”
Their optimism and possibilities mindset serves as a foundation in their quest for research, and they are not afraid of the potential disruptions their discoveries can create:
Daren Acemoglu: “We all have to work in order to make things better, including technologists, so that we actually use the scientific knowledge to create new tasks and more capabilities for humans rather than just sidelining them..”
David Baker: “Everyone thought it was a crazy way to try and solve hard problems.”
Their passion and conviction to do what they believe in, irrespective of what the world around them thinks about them, is key:
Demis Hassabis: “If you're fascinated enough and passionate enough about the area you're going to(work), I was going to do it no matter, and actually, I can't think of anything more interesting to work.”
You can click on the above video to watch this fantastic conversation.
It’s Not Always About Technology
Digital and AI technologies disrupt industries, business models, and more. Typically, companies invest heavily in buying and using these technologies, defining new processes, redefining existing workflows, etc.
However, the core challenge in successfully adopting these disruptive technologies is the people and culture surrounding them. As much as these technologies disrupt industries, they also disrupt people. Hence, when such an enormous transformation occurs, the problem is not always the technology; change management is the biggest barrier. However, this is what gets the least attention.
In their conversation, Prof. Iavor Bojinov and Prof. Edward McFowland III emphasize the importance of people and culture in successful digital and AI transformation. Usually, it is not hard but soft factors that make all the difference.
How do we get people to align and get the culture right?
Breaking the status quo: Transformation cannot happen without breaking the status quo. People change at an excruciatingly slow pace. People tend to get comfortable with what has been working for a long time, and breaking the shackles is hard. Because it creates a sense of volatility and uncertainty in people. Building a culture of ‘continuous improvement’ is vital. This ensures a constant relook at what is being done and assessing how it can be done better. A leader’s role in transformation is to break the status quo.
Bias is the biggest enemy: When you want to do a transformation like AI or digital at the workplace, removing bias in people is essential. People have information, knowledge, experience, and capability biases, while data may show contrary results. This makes people take defensive positions as it questions their credibility and expertise. They then vehemently oppose and question everything. Setting the context of allowing mistakes and accepting things that may not always been right in the past, is vital. Bias is the most significant barrier to adoption.
Identity early adopters and influencers: Not all people can accept change. However, identifying people who are willing to experiment, open to new working methods, and strong influencers who can, when convinced, make people adopt these changes is essential. Working with a small cohort of such people who are not insecure about themselves and are open can accelerate adoption.
Manage the middle layer tightly: In companies, change starts at the top, and the bottom layer gets it done. The ones in the middle can make or break the transformation. They are emotional, find it challenging to handle uncomfortable truths, show a lack of commitment in their behaviour, and may not communicate the need to transform to people below with enough conviction. Strategic alignment of these people is critical to making change happen.
Set clear benefit metrics: Sometimes, when transformation programs happen in companies, many qualitative benefits get discussed. However, converting benefits into clearly defined quantitative benefit metrics is key. It sets a milestone that people can aspire for and get recognised for achieving them. Just saying productivity and efficiency will improve means nothing to people. Converting them into identifiable benefit metrics is the hardest part. Technology cannot do that for you. For example, Gen AI implementation in supply chain, HR, sales, marketing, or production can save time for people, but that is not good enough. Convert them into KCI(Key Change Indicators) - time or money saved, incremental productive sales visits, number and turnaround time for collaterals, etc.
Digital and AI transformation needs the right balance of hard and soft metrics.
Some of the lessons we learnt from this week’s mission:
Humans gather data through sensory organs rapidly but synthesize this information far more slowly.
In most organization transformation initiatives, technology may be ready, but people may not be prepared as yet.
Humility, passion, conviction, optimism, patience and an infinite possibility mindset are the foundation for new discoveries.