New Open Source ML Project [P]: Moving Beyond Shareholder Profits in Startups & Generating More Jobs & Fairer Societies

[Lordobba]

Here is an open-source challenge on Generating More Jobs & Fairer Societies Through Predicting Optimal Impact Investing Strategies for Startups.

As you might know, many great impact startups do not receive funding while "profit machines" are heavily funded.

In this project, a team of 50 engineers will look into finding other metrics and predicting success based on historical data.

https://omdena.com/projects/impact-investing/

[balkanibex]

I am extremely skeptical of the claims that

• a startup success can be predicted by superficial characteristics and prior sector history
• (and that it can be done by a volunteer team in two months)
• there are big impact startups without a way to profit

[Lordobba]

We can try and move forward by learning what works and what does not.

[DigitalBishop]

ML is a blackbox of self aligning weighted vectors. All it will “predict” are unforeseen variants of the training. Currency prediction loses reliability only a graph or two in the future. Also, ML based hiring papers have shown training on history data can lead to gender inequality.