Google Ventures uses algorithms to approve or kill VC investments

And risk losing thousands of existing paying customers if it ever came out?

Not a smart choice, considering you're betting on the company you're illegally spying on to get profitable at some point.

Isn't that what a lot of Excel spreadsheets do? I think investments and acquisitions have used algorithms for a long time.

The article has uncovered sources that claim the algorithm makes the ultimate decision and other sources that claim it doesn’t.

If it does make the ultimate decision and not just for political reasons then this is very interesting. Having input data that is sufficiently informative is important on a number of levels. Firstly this means that it is possible to pick winners on the basis of other VCs etc Secondly it means one doesn’t have to be personally concerned with the story if others can vet it for you.

If the machine doesn’t make the ultimate decision then — as others point out — it’s just old fashioned screens and checklists with a new interface.

If the main input is quality of other VCs, then at some point a VC has to decide to invest based on fundamentals rather than what other investors are doing. a group of "fundamental" investors with good track records then would dictate what the rest of the market invests in.

you sort of see this dynamic play out in reality. YC is an example: they invest early, before other investors often, so they cant rely on other investors as a signal. they've done well though, so many investors follow them. there are more follow-on investors than successful "fundamental" investors, so there's often a valuation step up when follow on investors join that benefits the fundamental investors

same thing plays out in biotech. theres been a massive influx of capital into biotech VC, but not a big increase in the number of funded startups. most startups that go on to raise money are seeded in house by a handful of VCs. these VCs then fund the series a. they get big step-ups for series b and beyond deals and capture nice returns

im working on a more rigorous analysis to understand whether these anecdata are true in reality

there is very little public data available on startups as compared to private companies. so id imagine for an algorithm to be useful there would have to be a lot of proprietary data. further, id imagine a lot of this data is somewhat subjective -- ratings of management team, market potential (when a market is still not defined enough to quantify), etc. so its possible that many of the quantitative inputs have some degree of subjectivity -- the human element is still very present, its just hiding behind data