There is an issue of definition here. Categories of scenario exist where it is unclear if they constitute an “AI takeover” even though there is recognition of a real and likely risk of some type. Almost everyone stakes out positions at binary extremes of outcome, good or bad, without much consideration for plausible quasi-equilibrium states in the middle that fall out of some risk models. For researchers working in the latter camp, it will feel a bit like a false dichotomy.
As another heuristic, the inability to arrive at a common set of elementary computational assumptions, grounded in physics, whence the AI risk models are derived is sufficient reason to be skeptical of any particular AI risk model without knowing much else.
Regarding divestment, *who* owns equity can materially affect value independent of transacted price because other equity owners adjust the models of their long-term position value based on this information. This is reflected in concepts such as “dead equity” (implied dilution risk) in small companies and the notional-only value of founder equity in big public companies e.g. Bezos.
Regarding index funds, the (anti-)correlations are much more complex and less obvious, particularly in the modern globalized economy, than classic diversification and risk management heuristics allow for. The level of diversification within some single companies today does not have precedent. There is an emerging school of thought that a concentrated portfolio of companies with extremely high levels of internal diversification will have lower risk and consistently higher performance than when trying to reduce risk by diversification at the portfolio level. Anti-correlation has become so difficult in practice that optimizing for diversification efficiency and adaptivity is often the more effective strategy.