Never, Brent

"Over the course of three years, Large Language Models (LLMs) have become amazingly ubiquitous in our lives; ChatGPT helps us write our emails, set up our shopping lists for the grocery store, and even tell us a bit about Taylor Swift’s newest album. As these tools become more integrated into our lives, we are also facing a rapid growth in their power. Sam Altman, one of the most prominent creators in this space, projects that LLMs will be able to reason as well as, if not better than, humans in a “few thousand days”, so called Artificial General Intelligence (AGI). As we hurtle towards a profoundly new era of technological development, where machines can think as well as humans, this paper considers a particular set of institutions built into a prominent LLM, Anthropic’s Claude. What is the nesting of institutions in so-called Constitutional AI and what are some of the implications for how knowledge develops over the coming near term?

This paper uses the concept of nested institutions as found in the Institutional Analysis and Development (IAD) Framework: constitutional-, collective choice-, and operational-level rules and applies it to a specific process created to refine the development of Claude. Constitutional AI (Bai et al., 2022) uses a predetermined ‘constitution’ to guide Claude (a deontic) in how it grows its knowledge, a process that ultimately limits the role of humans after the initial creation of the ‘constitution’. The paper follows the process of constitution development and its implications for collective-choice and operational rules. The paper concludes with thoughts about future iterations of AGI-capable LLMs where humans are not part of the institution creation process.

Bai, Y., Kadavath, S., Kundu, S., Askell, A., Kernion, J., Jones, A., ... Kaplan, J. (2022). Constitutional AI: Harmlessness from AI feedback. arXiv. https://arxiv.org/abs/2212.08073"

There is increasing interest in the concept that philanthropy, the giving of money and time, can be considered a commons: a resource system that can be self-reinforcing and additive. Historically, philanthropy has been place-based whether channeled through faith institutions or community agencies. In the American context, philanthropy grew steadily over the course of decades to represent a major force in prosocial community action, yet in recent years this trend has substantially changed: the average donor gives less, while the wealthy donor gives much more. This paper asks the question: what are the implications for the philanthropy commons as giving becomes more concentrated across socioeconomic strata, with particular concern for the geography of this giving?

Using data from the National Center for Charitable Statistics (NCCS) Core Files, we document the increasing geographic concentration of nonprofit contributions across American metro areas. Measured by two means – a Gini coefficient and a Moran’s i statistic – there is a statistically significant increasing concentration in nonprofit contributions as the population of a metropolitan area increases. In effect, as the size of a city increases, the nonprofits who receive the sources of philanthropy become more geographically concentrated.

The paper considers how philanthropy might be better construed as a club good in large American cities, where the ‘haves’ of philanthropy are able to crowd out of a geographic neighborhood the ‘have nots’ in the nonprofit sector. At the same time, smaller municipalities have been able to maintain a philanthropic resource system that better fits with the definition of a common pool resource. Conclusions are drawn as to the impact of this concentration effect on the ability of diverse communities to be represented in large American cities as compared to their smaller metro areas.