The Global FAIR Space Blog

Well hello again.✈️After a few more bits of travel🚆, I have been back in Finland for the last couple of months, continuing to coalesce my ongoing research in AI governance – thinking, writing, reading, musing, learning, talking to people who are specialists in all sorts of fields. It is important that we think in a multidisciplinary manner and have these conversations with each other, because AI governance takes a lot of collaboration and co-operation.

I want to tell you how I choose my topics for this blog, because I tend to post only when I have something I really want to convey to you. I choose my topics the way most people follow a thread of curiosity. It’s usually whatever I’m thinking about or something I am trying to understand more deeply in my own research. I pull a thread and the whole ball of yarn comes flying out at me.🧶 I definitely go down a lot of rabbit holes🐇 but when I surface, if I feel that you all may find this interesting as well, then I will post about it. My aim for this blog continues to enable anyone and everyone to have conversations around issues of AI governance, equity and technology. I try to explain the fundamentals of things so they are understandable to all, so you can see the forest for the trees, so to speak.🌲

In this “brave new world” we’re living in, we are being inundated every day with new and new-to-you terminology. Catching up with it all can be rather overwhelming. Today, I’d like to talk about a term you may be hearing more and more often: complexity.

Complicated vs. Complex

First, I’d like to explain the difference between complicated and complex. Complicated things can be difficult, but they’re ultimately predictable if you know how to deal with them. Recipes, flat-packed furniture, or car trouble may take time and patience, but they can be handled in a systematic, logical way using a fixed set of steps or rules. Even when the process is super frustrating, there is still a logical path to a reliable outcome. The more you repeat it, the easier it becomes.

Even things with thousands of parts, like your laptop, are still complicated rather than complex. Yes, annoying and frustrating at times, but still ultimately predictable once you understand how they work. Many large, technical systems are complicated as well, like air traffic control or satellite operations. While they involve huge networks and precision engineering, they operate under defined rules, stable physics, predictable behaviour, and established protocols. They are complicated, intricate and difficult, but not complex.

Complex things don’t work like that. They’re shaped by relationships, context, and constant change. Think ecosystems, families, organisations, cities. You can’t pull one lever and expect a neat, straighforward response. Everything affects everything else. One of the simplest ways to understand complexity is through patterns in nature. A snowflake, for example, isn’t random at all. Its shape emerges from countless small interactions like temperature, moisture, and air currents in which each interaction influences the other until you end up with one of a septillion unique snowflakes landing on your nose. No single element determines the final form. Its these relationships that create the pattern.

What makes something complex is that the relationships matter more than the parts, so we can’t look at one component in isolation and expect to understand the whole picture. We have to understand how things connect and influence each other – how things relate, adapt, and respond to one another. Complexity can’t be solved with step-by-step instructions because situations change as the relationships change. And, in complexity, the relationships are always shifting and evolving.

If any of this is making sense to you, it should, because it is exactly how our world works. In our current global landscape, we’re surrounded by systems that don’t sit still and don’t behave predictably. Some of the structures we’ve relied on for decades are struggling under the pressure of rapid change. In many cases, entirely new systems are having to be built in real time just to keep pace (and many are already behind by the time they are stood up). In the scope of this blog, we’re navigating a world where, from security and governance to technology and AI policy, the ground keeps shifting beneath our feet and we are constantly having to find new footing.

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However, in middle of all these constant upheavals, it’s important to remember that there are human beings inside these systems. So many people are navigating uncertainty while still dealing with the same social and economic pressures we’ve always had. Equity issues don’t disappear just because technology advances touted to vastly improve our lives hurtle onwards; if anything, we have even more factors to consider. As AI and other emerging technologies move faster than our existing institutions can adapt, we risk leaving our at-risk communities and priority populations even further behind.

Governance must evolve to be forward-thinking (perhaps even out-of-the-box) and anticipatory, because the systems we built for a different era simply can’t manage our current realities. We are all seeing this as AI governance has had to continuously adapt and evolve. Emerging technologies move far faster than the institutions tasked with guiding them, which means we need more nuanced, human-centred approaches that recognise how people actually live, work, adapt, and struggle as we move through this technoscape.

Furthermore, we need ways of shaping those systems that don’t simply check boxes or assume simple fixes, but respond to real human interactions and lived experiences. This is also why interdisciplinary work matters so much right now. No single field can see the whole landscape on its own. The humanities, the sciences, and technology all shape each other, and the only way to navigate complexity responsibly is for the people doing the work in these disciplines to bring our perspectives together rather than staying in our silos.

What I’m getting at here is that we, as human beings who chose to do work in these fields or related fields, are also relational factors in all of this complexity. The people designing, implementing, and shaping governance are ourselves part of the system and are of course influenced by our contexts, our training, our pressures, our assumptions. There is no outside vantage point, because the system includes us. That means our decisions, our interactions, and most definitely our biases and blind spots all have ripple effects. And if our relationships shape the system, then the quality of those relationships – that is, how we listen to, interpret, communicate, and respond to each other as well as the people we serve – become the mechanisms enabling the evolution of the structures that can contribute to equitable outcomes.

Finally, I’d like to defer to complexity thinker Dave Snowden, who created the Cynefin Framework. Snowden is one of the world’s leading researcher on how complex systems work, particularly in organisations and society. He has spent decades making sense of how systems behave in the real world and helping organisations recognise when they’re operating in truly complex environments. His ideas help us understand why simple solutions don’t fix complicated problems:

Dealing with the present involves getting down and dirty, yes we have some form of purpose or direction, but we don’t preach it, we practice it and see what happens. We don’t attempt to change people per se, or to be more accurate, write or speak about how they should be, instead we change the nature of the system in which they act, and the nature of their interactions.

– Dave Snowden on thecynefin.co

I write this blog to make the conversations around AI, equity, and governance more accessible, because these systems belong to all of us. Even if you’re not working in these fields, you’re still part of the story. You don’t need a title, a degree, or a policy role to matter here. If you’re navigating this world with its shifting systems and emerging technologies, then you’re already part of the fabric that is shaping it. Your presence matters. Your perspective matters. Your lived experiences, your questions, and the intersectionality in which you move through the world should all matter in how these systems evolve.

I hope I’m encouraging you (even a little bit) to have your own conversations so we can all shape these systems together.

#Fairness #AI #Equity #TheGlobalFAIRSpace #AIandEquity #Complexity #EmergingTechnology #ArtificialIntelligence #AIEthics #EmergingTech #ResponsibleAI #AIGovernance #TechGovernance #CynefinFramework #DaveSnowden #BecauseHumans

*All images in this post have either been: 1. generated by Natasha J. Stillman and ChatGPT-4o (DALL-E 3); 2. pictures taken by Natasha J. Stillman; or 3. conceived by Natasha J. Stillman using CANVA.