Leaders, time to get clear on the technology and its capability
First, let's get really confident talking about the technology. Coming up: a simple, crystal clear explanation so you know what you're talking about.
“AI will have the biggest impact on humanity since the development of the internet.”
👆 too many people to credit this to so let me just pick out Thomas Lahnthaler who wrote this on one of my posts.
AI is a megatrend which will reshape how we live and work - from creating to code to designing new chemical compounds.
In this series, I’m going to walk you through the opportunities and issues AI presents specifically for collaboration.
- How we think, create, plan and execute together.
- How we share information...
- ... and how we build trust.
I will focus on summarising what’s coming (or here) - and exploring the cultural and behavioural implications of this big wave of AI capability.
So other than plug the technology in, what will leaders need to understand about how it will reshape working patterns, relationships, norms, habits and culture?
AI is a paradigmatic shift i.e. a fundamental change in underlying assumptions and structures, not a transactional or step-wise shift. The thinking is that this is the first technology wave that all leaders will need to understand and lead - not just technology leaders.
Of course, I will inevitably only scratch the surface! Please store up these emails for the future. In as little as 3 years time they will be laughably naive (and in 2027, we may need all the laughs we can get!).
Ok, here’s the plan for the next five days.
Day 1: First, I’ll talk you through the core AI technology relating to collaboration and how it works, so you feel completely confident talking about it. And I’ll get you thinking about the main way this tech will change and disrupt our work.
Day 2: We’ll get straight into the 9 main collaboration use cases on the radar right now, so you have a sense of what’s coming.
Day 3: I’ll explore the 14 key human issues and challenges that this vast technology opportunity will raise for your organisation’s culture, norms and behaviours so you feel confident to raise and debate them in your own organisation.
Day 4: We’ll look at the specific skills your teams will need to develop to adapt to the arrival of AI
Day 5: I’ll talk you through the main decisions you’re going to need to make and we can start to develop your thinking and form a simple plan
(and look out for a super-interesting bonus after day 5...)
Let’s get started!
The big picture - where has this new wave of AI come from?
AI is not new. Machine learning has been around for decades. Remember Deep Blue - the first computer to beat a reigning world champion at chess in 1997? A big milestone for AI.
What’s new and coming to your world as a leader of teams is Generative AI (or GenAI) - the ability to create new and original content rather than just finding and organising existing content. Its ability to create realistic text, images and code has stunned the world and opened the door to new behaviours, routines and possibilities. What has catapulted GenAI into the mainstream is the fact you need no technical expertise to use it.
First a simple definition: GenAI is a tool that uses machine learning (practicing and improving over time) to develop a human-like ability to understand and talk to humans (otherwise known as Natural Language Processing or NLP). You could think of it as 'intelligence as a service'.
Next, some context. GenAI is both incredibly powerful - and ridiculously basic compared with what’s coming over the next couple of months (and even centuries!). Here’s one way to classify the types of AI you might have in your mind.
Narrow AI: This type of AI is designed for specific tasks, like playing chess or recommending movies. It's really good at one thing, but it can't do everything a human can.
General AI: This is like the AI you see in movies – it's super smart and can do almost anything a human can do. But we don't have this yet; it's still a goal for the future.
Artificial Superintelligence (ASI): This is AI that's way smarter than humans in every way. It's still theoretical and hasn't been achieved yet. Unlikely any time this century.
What do you need to know about how Generative AI works?
Now, I do think it’s helpful to understand the basic mechanics of GenAI. Here’s my favourite explanation [20min animation] and I’ve broken it down into a simple story here.
- Most of what you’ll experience in the workplace will be a Large Language Models (LLMs). These are a type of GenAI which can generate fluent human language. As an example of how LLMs fit into what you know already, OpenAI (a company) has created GPT3.5, GPT4 etc (LLMs) which are used by ChatGPT (their application).
- GenAI using LLMs is essentially a ‘guess the next word’ exercise - trained both by searching for patterns and through human guidance. Crucially, LLMs has searched for pattens in HUGE quantities of data which takes vast amounts of compute power. Training the GPT models has cost $billions….
- We can access LLMs via applications e.g. ChatGPT, Microsoft Copilot etc. Or you can build your own product e.g. creating and training a chatbot around your product or service using an API. These require surprisingly little code.
- There are lots of LLMs - you might have heard of Google’s Bard or Meta’s Llama and there are many more specialised or technical models. Here’s a guide if you’re interested in the main players.
- Some are stand alone and some are locked into other programmes as copilots (much more on copilots later).
- There are a variety of modalities: text to text, text to image, text to audio (and vice versa) being just a few.
- One key way we interact with them is prompting: asking a question or giving a brief by typing text. They produce a result (text, code or image) and we can refine the result with a further typed prompt. In fact, we can turn this into a whole conversation, exploring and developing ideas and plans.
- LLMs (and therefore GenAI) vary greatly in quality. For example, the leap between GPT-3.5 and GPT-4 is huge.
- Henrik Kniberg explains that GPT 4, when prompted correctly, is a better programmer, marketer, strategiser (and just about anything else) than anyone he has ever worked with. The main bottleneck here is Prompt Engineering Skills (we’ll look at this more in Day 4).
- Autonomous agents are a step on from prompt-based work. You can give the LLM a high level mission and some tools and let it go to work. For example, an LLM can act as your Executive Assistant by giving it some tasks to do and parameters to work to.
Is GenAI a life-changing miracle or disappointing over-hype? It's moving fast and time will tell. Here's a nice visual to show where we are on the AI expectation curve - might help anchor some of your team if they are having different experiences.
If you’ve made it this far - congratulations!
Now we're ready to get into the really interesting stuff. How will we use this technology in the real world? How soon? What might we start seeing our team members experimenting with? What’s coming, how soon and what do we need to do about it...?
In the next guide, I will share the 9 collaboration areas AI can already support (and transform). This will give you a clear idea of what it can do, how it can help you - and where to expect change to come from.
