In contrast, and to mix my metaphors, there’s a deafening silence about the other side of the intelligence equation - human intelligence (HI).
I think we need to “say HI to AI”, because AI adoption is only as good as the sophistication of the human beings driving its implementation. You can have the best AI in the world, but if there are bad actors using AI for self-serving reasons then we could all be in trouble. Or to put this more bluntly the problem with AI is human stupidity.
All over the world organisations are spending billions on AI. But very few are adequately investing in upgrading their human intelligence. It’s like most businesses are blind to the relationship between AI and HI.
This is weird, given the fact that AI is modelled on human neural networks. In fact, Geoffrey Hinton, the grandfather of AI, won the Nobel Prize for figuring out how AI can mimic the human mind’s ability for deep learning. He solved something called ‘backward propagation’, which is how our minds create meaning from data. And AI has been trained on massive data sets filled with human information. AI was built to look like us, and since it’s passed the Turing test, it also sounds like us. It has consumed all our publicly available data.
So, why have we become so enamoured by our digital twin to the exclusion or our humanness? Is it because AI now knows 1,000x more than any human expert and it can make connections between things that a human mind could never make. Are we in awe of our silica-based sibling as a result? Or is it because those leading the evolution of this technology are themselves less interested in our humanness than the rest of us.
In my book, Smarter Than You, out next month, we argue that, to win in business with superintelligent AI, it’s key to deepen our understanding of HI.
In the book we describe the three great battles for the future of AI. First of all there’s the classic capitalist battle for vertical integration across the eight layers of the AI ecosystem.
Jensen Huang, CEO of NVIDIA, describes a five-layered AI cake that doesn’t recognise levels 2,5 and 6. He doesn’t separate out the Cloud layer, the Data Centres and Libraries layer or the Operating Systems layer – he puts all this in infrastructure. He also calls the Minerals and Rare Earth Element (REEs) layer the Energy layer.
Regardless of whether we have 5 or 8 layered model, some multi-national organisations or nation states are currently trying to dominate a single layer. For example, China owns 80% of the REEs market and NVIDIA own 80% of the chip manufacturing globally. Some organisations are trying to dominate multiple layers. Most companies are simply playing across many layers.
In addition to the Battle for Vertical Integration, there’s a Battle for Private Data. Most LLMs have already hoovered up all publicly available data so the only data they don’t have is privately held information. Such data sits in corporations’ employee or client data lakes, health care system records, pension fund profiles and so on. Some corporations have already sold their private data as a revenue stream. Synthetic data creation may reduce the need for some private data but if all the data is inside the system nothing will exist outside the system. This is not necessarily a good place to be.
The third and perhaps the most critical for the future of AI is the Battle for Artificial General Intelligence (AGI). Despite OpenAI’s CEO Sam Altman’s claims that they will have achieved AGI within 2 years it’s unlikely that anyone is even close to achieving AGI. Such a feat requires tech companies to understand how humans create sentience, identity and also how human consciousness works. These are some of the most complex problems in science and currently there is zero evidence that any big Tech company is anywhere close to this, despite their proclamations.
To maintain human relevance in an AI-accelerating world the smart move is to focus on HI. More specifically, focusing on the ten different types of intelligence that matter in most organisations. If you’re not measuring and growing your Ten Intelligences, then you’re not setting your business up for the future.
Human can stay relevant and competitive, not by trying to compete on knowledge, AI already has us beat on that. But by using our knowledge more intelligently. If we increase our intelligence levels across multiple ‘lines of development’ we can build a path to a more successful future.
1. Energy Smart – How good are we at managing our energy levels. If we are not very smart then we can easily become exhausted, leading to poor performance. In addition to energy management this intelligence is about the quality of that energy. Are we chaotic or coherent, which alters brain function. We measure energy intelligence using heart rate variability (HRV) technology.
2. Emotion Smart – Leaders must cultivate their emotional awareness, emotional literacy and most importantly their emotional regulation capability. These capabilities underpin a leader’s social intelligence and ability to build strong, sustainable relationships. We assess the 12 levels of emotional and social intelligence.
3. Cognitive Smart – there are multiple aspects to our cognitive sophistication but ultimately this is about the ability to embrace bigger and bigger data sets and take a more expanded and sophisticated view of the world, moving from tactical problem solving to strategic and systemic thinking. We assess the ten levels of cognitive sophistication, including awareness of awareness and transcendent awareness.
4. Values Smart – there are eight motivational systems in the world. They are not variations of each other but evolutions. Value systems are what underpin inner diversity. The more developed a leader is here the better they can engage and motivate others. We assess how Values smart leaders are.
5. Ego Maturity – Most C-suite leaders operate from level 5 or 6 of 12 levels of ego maturity. Less than 20% of leaders reach level 7, and <2% reach level 8.
6. Ethical Maturity – More leaders were removed from office in 2023 for ethical reasons than performance reasons for the first time in history. In a post-truth world, where deceit is the new currency, morality matters.
7. Behavioural Smart – The first six intelligences are internal and thus not visible. But ultimately, they have their effect in the world through changing a leader’s behaviour. There are 11 behaviours that are known to improve performance, and they can be assessed across eight levels of sophistication.
8. Network Smart – Even if we are behaviourally smart we need to be connected to others to achieve an effect in the world. Therefore, the quality and sophistication of our networks matter. Our Organisational Network Analysis (ONA) technology precisely quantifies a leader’s influence, as well as revealing many insights about how the organisation really works..
9. Impact Smart – Even if we are highly networked success depends on the impact we have within our networks. We assess this using a 360-degree impact scale. Converting intention into tangible results requires us to influence stakeholders and shape the environment around us.
10. Team Smart – Smart leaders develop smart leaders. Assessing the sophistication of a leadership team is vital to success. The single greatest determinant of commercial success is how developed the leadership team really is.
Most leadership programmes never even assess any of these intelligences let alone quantify whether the programme or coaching intervention has increased the intelligence of their leaders. If we want to succeed in a world of AI superintelligence we must develop our human intelligence.
First, it’s vital to measure the baseline level of intelligence in a leader or team before intervening to enable a real ROI to be quantified. Then we identify which two or three lines will be key to focus on to drive accelerated growth and better performance in the first few months.
We then design targeted interventions to step change that specific intelligence. This might involve blending physiology, neuroscience, cultural, operational and strategic modules to drive the personal collective and organisational outcomes required.
We re-measure intelligence at agreed milestones to show how leaders and teams have developed and how this has driven a transformation of commercial results.
This is not training or skill building it’s a transformation of ability. And making people smarter also delivers an increase in speed and energy. All this translates to improved commercial cultural and personal outcomes.
If you want to “say HI to AI” and make your leaders smarter and faster just reach out to us. We can help you map your top team, target the right lines of intelligence, and make sure you are set up in a way to deal with the AI future that awaits you.