AI interactions: not a copilot, but a coach

This doesn’t have to stop at the edge of the technical practices. Instead of asking Coach 365 to draft a memo or a piece of marketing material, what if it took a competitive approach? It could follow our lines of argument, pointing out common logical pitfalls, places where our reasoning doesn’t hold up to superficial scrutiny, or we otherwise exhibit some clear bias. In doing so, it could even start to coach us out of insulation, ignorance, and complacency.

Meanwhile, back at the farm, Copilot seems to be offering us a hodgepodge of disconnected, supposedly time-saving conveniences. Apart from narrow use cases, such as the Edge browser or the current page of a Word Document, there is a serious disconnect between the content we are currently working with and the feedback Copilot provides. Even Microsoft’s front-page piece, the Copilot system prompt on Windows 11, seems devoid of context.

Simple contextual queries are met with confusion. “What’s on my screen right now?” Let me search the web for that, it says. “Who am I?” An interesting philosophical question, Copilot quips. “What’s on my calendar?” Let me search the web for that, too. Though placed in a window of prestige, Copilot seems to still believe that it is housed firmly in the Bing search browser, ready to help me search for and purchase self-help books in the pursuit of answering that burning “Who am I?” question. These are real interactions, by the way…

A series of basic contextual questions for Microsoft Copilot

To the Copilot team’s credit, though, these problems are presently expensive to solve. It is by no means a small undertaking to index, compare, and generate text for so many, potentially unrelated interactions. Local device limitations, the speed of existing models, as well as other frictions, play a part. Nevertheless, Microsoft offers some services that begin to approach the level of self-referential connectivity I spoke of above — they’re just hidden behind the Microsoft Copilot 365 “For Enterprise” banner. Even then, the number of messages a user can make are limited. Worse though, it’s tailored in such a way that it just gives us more fish than the unpaid tier.

These limitations are quickly receding, though. In a paper, last month, researchers at Apple outlined a method by which we might be able to sidestep the memory limitations of personal devices, to locally run ever larger, more precise models. Even as the implementations of our machine learning models become more clever, our personal technologies are still getting faster and faster, hurtling toward the physical limits of computation. We will be able to equip language-generating models with more context, very soon.

So what will we do with them? Will we continue to ask our systems to give us fish, or will we learn how to fish? We need an artificially intelligent assistant that is aware of our personal data and our relationships with others. It should be equipped with mechanisms that allow it to retain our interactions with it, as well as use sentiment analysis to perform fine-tuning in response to the feedback we give it. It should help us to create new connections with and recommend new applications for the information we curate. It should be competitive, and not just passive, refining our existing workflows and helping us make the most of our computational systems. It should coach us out of complacency, too, helping us recognize where the solutions we generate are inefficient or insufficient.

If we get this right, imagine the problems we could solve. I believe that building Coach 365 is imperative — something that will equip each of us to build, create, and solve problems at levels of performance previously only achieved by a choice few. I believe that creating these systems will be a bootstrap of sorts, raising our collective problem-solving capacity such that it allows us to solve the greatest challenges facing humanity today and whatever the future has to throw at us. Let’s do it. Let’s build it. Let’s go fishing.

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