GPT/LLM links
Scott Belsky on business models; Ethan Mollick on chatbots vs. humans; the Zvi on deepfakes and elections
The classic time-based model of billing for lawyers, designers, consultants, freelancers etc is officially antiquated.
The problem is that with the help of AI a job can be done in very little time. Scott suggests that this will result in new billing systems. I think that the more standard economic analysis would suggest that this raises productivity dramatically. Suppose that the demand for legal services is inelastic (there is a fixed number of legal outputs needed). Then the price of legal services drop, and a lot of lawyers have to exit the market, so that there is enough work available to keep the remaining lawyers in business.
Belsky has a number of other interesting speculations, many of which had not occurred to me.
While books and courses can help, there is nothing like an experienced cofounder… except, as my research with Jason Greenberg suggests, experienced cofounders are not only hard to find and incentivize, but picking the wrong cofounder can hurt the success of the company because of personality conflicts and other issues. All of this is why AI may be the Best Available Cofounder for many people. It is no substitute for quality human help, but it might make a difference for many potential entrepreneurs who would otherwise not get any assistance.
This is interesting. What I call an “early divorce” between cofounders is what ends many start-ups. But I think a cofounder has to do more than brainstorm and develop a web site for your business. There is hands-on work to be done. Read Ethan’s post and see what you think.
You do not need AI to do a poor quality deepfake. We have been creating poor quality fakes forever. The poor quality reflects that it is responding to demand for poor quality fakes, rather than to demand for high quality fakes.
As always, the better fakes are coming. This confirms they are not here yet.
substacks referenced above:
@
@
@
Agree with the elasticity comment, completely. That said, I do think people misapprehend what lawyers spend their days doing, at least what I spend my day doing as a lawyer. It’s not simply producing contracts that could be ‘mad lib’d by an AI. I’m not trying to argue for my value – I think lawyers are generally a value suck. It’s just that most of the questions and much of the job is about exercising judgment related to novel circumstances, and probably not something that an AI would be particularly good at.
That said, I do think something like a trust and estates attorney could do really well with AI. If you took all of the answers from a client questionnaire, and correlated those with the documents that were output, you could probably train an AI model to do a very competent first draft. But, again, the outcome of such a system might very well be to lower the price of providing these services, which would make those services available to more people, which would increase the size of the market, which would result in more rather than fewer trust and estate attorneys. These things are hard to predict, i think, and the impact of technology on markets is often surprising.
One of the most surprising anecdotes I’ve heard is that the cotton gin lowered the price of cotton, which lowered the price of cotton clothing, which increased the demand for clothes because people wanted more than one set of wool underwear, etc., which (paradoxically from my viewpoint) drove an increase in the demand for slaves to grow the cotton. The claim I heard was that slavery was generally petering out before the cotton gin. I don’t know if it’s true completely, but it’s fascinating that the cotton gin could have been the “cause” – at least “a” cause – of the Civil War. So, again, hard to predict how these things will play out.
Legal services are elastic! I have a friend who spent a year in law school before becoming an economist. He told me that the one thing he learned there was “there are many towns too small for a lawyer, but no town is too small for two lawyers”.