Hi there,

I often fail to explain myself well; a definite shortcoming I need to work to improve. Let me have a go at addressing your points/questions.

So, to recap and ensure I don’t have things wrong. The recommendation is that customers rate an agent based on dimensions relating to how the task was completed. The financial transaction made lends legitimacy to the scoring. Second, there is a staking system which allows individuals to anticipate high scoring (and therefore more used) agents, using money to legitimise the scoring.

Essentially the customers get asked “was this a good service?” and stakers get asked “do you think future customers will rate this as a good service?”. The latter is therefore a forward looking expectation of the former. So it all comes down to if the customer is happy.

If a big spending org is going to use more than a cold, hard profit-calculation to score, a few things need to happen.

First they’re going to have to want to do so. Which hasn’t really been borne out by current experience. We’re working really hard to establish standards that organisations can use to make ethical choices on AI, but there’s some pretty shitty precedent from other areas which suggests this is going to be kinda tough. There’s also pressure from end customers, but transparency here is difficult - though I found out recently my savings were being used to invest in arms exports… nice.

Second, if they do want to rate on a broader range of criteria, they’re going to need to be able to KNOW if they’re doing shady things. How will they know if the data set used to train the agent has strong bias against minority groups?

Third, this has to be something that is fast and can be automated if SNet is going to work. There has to be metrics around it, measurables. A key SNet USP is that the agents used can be dynamic. Corporates are not going to bother using SNet if they need to go hunting round to see if there is any risk of them invoking a twitterstorm everytime their backend uses a different agent.

For me it’s risky to just use purely utilitarian metrics.

To answer your questions:

Re: “Do you see any evidence that this will happen?” - what is this? - “this” is “use anything other than raw cost/utility to recommend an agent”

Re: “this simplistic and potentially damaging assessment” - my bank’s approach to measuring the reputation of funds is an example. Their measurements was output/cost, so they invested in arming developing countries. Arguably if my bank had no idea that the investments were heading into guns, it’d be difficult to blame them too much. In the case of AI agents they could justifiably say they had no idea the agent they were using was biased otherwise “we’d never recommend it”

Re: “transparency in where our money” - see previous

Re: “disconcerting if the basic metric of reputation in our brave new world is utility vs financial”, so what is your suggestion then? - That will take some more thought, but it’s a conversation worth having.