Generative AI: ChatGPT, DALL-E, Stable Diffusion, and the rest

Everyone’s talking about it so we will too. Generative AI is taking the world by storm. But is it a good storm or a scary storm? How should individuals think about what’s possible? What about companies?

Our take: generative AI is hugely powerful but will always have flaws and potholes. As probabilistic systems, it will always produce errors—how will you plan for that? As systems that are trained on everything on the internet, they are essentially stealing IP from everyone, everywhere—how do you feel about participating in that theft?

We’ve spent years witnessing companies take a “if we build it (data, analytics, AI), people will use it” approach—and fail. Digital transformation doesn’t happen successfully by itself. Digital transformation is actually all about people. Companies that succeed in integrating data, analytics, and AI are those that undertake thoughtful change management programs to help people understand how to integrate these technologies into their complex human systems.

Generative AI is really exciting. But our prediction is that companies will need to undertake thoughtful change management to ensure they get the best out of these new AI technologies, not the worst.

Nudges of the week

Helen: Synthesize Later. Integrate argument and counter-argument into a decision. Good decisions involve reconciling subjective judgments and resolving clashing causal forces. The best way to do this is to be deliberate and conscious of the need to synthesize. Schedule a meeting titled “synthesis” and set expectations that now is the moment to step slowly through each point of view, iterate, and nudge each side. Have each side make a list of the things that would bring them toward each other. Failing to do this contributes to a sense that the decision is stuck.

Dave: Explain, Teach, Pitch. Explanations and the stories that link cause and effect play a key role in allowing us to adapt flexibly to a changing world. Explaining our decisions is a generative act. We learn more about our own motivations and knowledge. Explanation is active and can help us when we need to rethink, reevaluate, and deal with regret. Teaching is set apart from explanation because good teaching also relies on empathy. A good teacher understands where the student is in their learning process and adjusts their teaching to fit the mental model of the learner.

What We’re Learning

Helen: Joined-Up Thinking by Hannah Critchlow. A great summary of the state of the science about how we can build our collective intelligence. A delightful read that Helen highly recommends.

Dave: Don Norman’s next book who we will interview in the next few weeks! Stay tuned for that interview with one of Dave’s heroes.

About Artficiality from Helen & Dave Edwards:

Artificiality is a research and services business founded in 2019 to help people make sense of artificial intelligence and complex change. Our weekly publication provides thought-provoking ideas, science reviews, and market research and our monthly research releases provides leaders with actionable intelligence and insights for applying AI in their organizations. We provide research-based and expert-led AI strategy and complex change management services to organizations around the world.

We are artificial philosophers and meta-researchers who aim to make the philosophical more practical and the practical more philosophical. We believe that understanding AI requires synthesizing research across disciplines: behavioral economics, cognitive science, complexity science, computer science, decision science, design, neuroscience, philosophy, and psychology. We are dedicated to unraveling the profound impact of AI on our society, communities, workplaces, and personal lives. 

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