Motivation - in the blink of an AI…. an underestimated dimension of Generative AI

In the blink of an AI, I’ve seen people go from 0 to 60, motivated, keen to learn, creative and more productive. 

In just one example, I have seen Claude have a huge and immediate impact on a small business. Honestly, this is a very real example, with someone I know well. After we showed the CEO what AI could do, he stayed up for hours that night played with it and discovered use after use. I have never seen him more excited about something that he was told would improve his business. For all the networking, business mentors and support he’s had, this blew all of that out of the water and, like a fountain, it has continued to flow. Described by him as “like having a new skilled employee for free” it is the gift that keeps on giving. Make no mistake, this will lead to growth in his business. The sheer enthusiasm of the CEO was infectious. It is particularly satisfying to see the people at the top get the fever as it cascades downward. Not just by example but by giving permission to others to use it in their own jobs. The dam bursts and the water flows.

We need to reflect on dimensions of Generative AI, other than its functionality, and productivity gains, as there is another greater prize to be won – motivation. Dig deeper and we find behavioural change lies at the root of its global use.

High and low agency

There’s a huge difference between high and low agency people in organisations. It’s the difference between those standing still on an escalator and those that briskly walk, even when it’s going down. You can often see and feel this when you deal with its people. High agency in organisations have individuals or teams who have significant autonomy and control over their work.

People are empowered to take ownership of their tasks and projects, and AI scaffolds this activity. They can make decisions, influence outcomes, and take initiative without excessive oversight or restrictive rules. High agency AI environments also foster creativity and innovation, as individuals feel free to experiment and explore new ideas without fear of failure or micromanagement. Of course, with greater freedom comes greater responsibility. High agency implies that individuals are accountable for their actions and outcomes, but this can also lead to a stronger sense of ownership and engagement.

What you tend to see in high agency environments are individuals with the power and autonomy to control their own work, which leads to higher job satisfaction, performance and well-being. Low-agency environments often lead to dissatisfaction, disengagement, and higher turnover rates.

AI and Intrinsic motivation

Self-Determination Theory (SDT) gives credence to this idea of agency. It shows that people have intrinsic motivations to act when they feel autonomous, competent, and connected to others. High agency aligns with these needs, leading to higher motivation and satisfaction.

Everyone has that ‘Holy shit’ feeling when using AI for the first time, feeling More specifically and  Self-determination theory, as defined by Edward Deci and Richard Ryan in their book ‘Self-Determination and Intrinsic Motivation in Human Behaviour’, see the active self, being in control, as the primary driver behind personal growth and fulfilment. It sees intrinsic, not extrinsic motivation as the driver for personal satisfaction and success. Your own need for growth that drives other personal needs. This means growing in competence as well as feeling related or connected to other people. 

The theory has three components:

1. Autonomy - being in control, able to take action that results in actual change. 
2. Competence - learning knowledge and skills to achieve more autonomy
3. Connection or relatedness - feeling attached to other people

AI provides autonomy for people by freeing them to do things felt they were never capable of, so gives immediate agency. It also gives that feeling of rapidly increasing competence, of learning quickly to confirm that feeling of autonomy. On top of this, I’d argue that dialogue with a LLM is like speaking to another person or expert (see research by Nass and Reeves).

AI and wellbeing

Another dimension of motivation in AI, is wellbeing. In ‘Lost Connections: Uncovering the Real Causes of Depression – and the Unexpected Solutions’, Johann Hari, sees the causes of depression and anxiety, not as simply the result of chemical imbalances in the brain but largely social and environmental. Depression, anxiety and unhappiness at work stem from various forms of disconnection in people's lives; disconnection from meaningful work, helplessness, meaningful values, status and respect, a hopeful or secure future and a  disconnection from a sense of meaning. AI can partly help (it is by no means the sole solution) by reconnecting the individual with meaningful work, rebooting intrinsic motivation through a strong sense of productivity and achievement.

We know that personal agency matters in terms of job satisfaction, wellbeing and staff retention. We also know that agency matters in learning. People learn faster when they feel a sense of agency, growth and achievement. AI as door to learning

Low floor, High ceiling, Wide walls 

Intrinsic motivation is amplified by the ease of the interface, along with speed and breadth of results. Donald Norman said good technology should be invisible. The future of online learning is that it will be smart & that these smarts will disappear. The invisible hand of AI will transform why, what and how we learn. But it was Seymour Papert who defined what this should look and feel like in practice. Papert's concept of low floor, high ceiling and wide walls are wholly relevant to AI in both tasks and learning, foundational ideas in the design of productive and learning environments. 

Low Floor is the ease with which a beginner can start using a tool or engaging in an activity. The entry point is astonishingly simple in AI, a chatbot letterbox or voice, simple and accessible, allowing novices, even children or those with no prior experience, to begin learning without feeling overwhelmed. 

High Ceiling offers complexity and depth for those who wish to explore further. It means that learners can continue to build on their knowledge through dialogue, taking on more challenging tasks as their skills develop, something available and evolving fast in AI, with multimodality, coding, data analysis, agents and additional technology built into and around Generative AI.

Finally, we need Wide Walls, a depth, breadth and diversity of knowledge and paths that learners can take within a productive process, learning task or environment. Generative AI seems to have a Degree in every subject, speaking dozens and dozens of languages. It suggests that there are many different ways to engage with the material, catering to various interests and forms of expression. Do you want full exposition, brief summary, checklist? Or writing at the right level in a certain style, even poem or story, in any language? As an image, animation or video? 

Generative AI has, and continues to release these three features. A low floor, high ceiling, wide walls interface promotes inclusivity, creativity, and personalised learning. It encourages the design of educational tools and activities that are accessible to beginners (low floor), offer room for advanced exploration (high ceiling), and provide multiple ways to engage and express creativity (wide walls).

Conclusion

Let me add one other thing. Adding AI to improve productivity, quality and meet individual and organisational objectives, especially if you build proprietary AI applications, adds value for everyone. If you are an individual, you will feel better using this technology, find that a sense of release in being able to do things quicker, have less stress and be more productive. It gives people a release of energy and purpose that many other deliberate interventions, such as courses and edicts from above do not. It has an immediacy, with instant results and gives a sense of wonder.

This is why most use of AI in organisations is ‘on the sly’. Organisations veer towards top-down bureaucratic solutions to try to solve problems, which are often cumbersome, requiring difficult skills to master. We finally have a technology that allows one to be more productive, learn faster and feel better.