AI: Open Mind

Lots of thoughtful people are incredibly hostile to AI right now, not least because the most prominent AI spokespeople are billionaire snake-oil confidence men and gangsters. The tenor of discussion in reddit and specialized fora is very low.

Nevertheless, LLMs are amazing. You should not let the hucksters blind you.

What I have learned from building bridges between AI and Tinderbox is the importance of asking the right questions. Too often, I see AI applied to tasks it should not do. For example:

• I need a 3-5 page paper comparing Player of Games to Ender’s Game for my college literature course. The references should use ALA format. I really need at least an A-.
• Take these 500 emails from people who want to cancel their subscription, and write a customized response to each. Your first goal is customer retention, but a secondary goal is to delay beyond the start of next month.

Here, the AI is being asked to do things it cannot do well, and in the process it is actively harming the user. The first user doesn’t need an A-; that user needs to learn how to write. The second user doesn’t need to slow-walk cancellations; they need a better magazine.

Some places where Claude+Tinderbox excels include:

• Locating the best books on nearly any topic, however obscure.
• Finding a specific technical paper from an approximate description.
• Google-style web queries that are infeasible because a homonym gets in the way, such as a young European computer scientist who shares a name with an Olympic athlete.
• Sanity checking a book you like but fear may have been superseded or refuted. (Claude strikes me as far more even handed in this role than Wikipedia, which frequently treats these questions as a political football.)
• Thinking through algorithm selection. For example, Tinderbox uses force-directed graph layouts in several places — “dancing” in map view, Gaudí view, hyperbolic view. I’ve written force-directed layout several different times over the years. Claude has the alternative algorithms, their history, and their performance (both in terms of big-O and in terms of runtime on today’s machines) at its fingertips.

These tasks share important characteristics. If the AI is right, they are helpful both in terms of immediate results and also in terms of process. If the AI is mistaken or badly informed, that is likely to be obvious right away. You’re using the AI’s erudition and breadth, and not depending on it for insight or novelty. Those are what you supply.