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AI Is Key to Bias-Free VC

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Getting venture capital funding is a difficult task, especially for founders from marginalized groups. A study by Babson and Wellesley colleges found that only 3% of VC funding between 2011 and 2013 went to women, while companies with all-male executive boards were four times more likely to receive funding.

Biases related to gender and race can affect how VC funding is allocated. However, using artificial intelligence informed by data may help eliminate such biases, allowing VC funding to be based more on a company’s potential than on its founders’ demographics.

The limited funding for minority and women-led startups has been a growing concern. Despite 38% of U.S. companies having women in charge, less than 1% of VC funds go to minority-run businesses and only 2% to companies led by women.

To address these biases, an AI platform called Alice has been created to increase VC funding opportunities for female, minority, and LGBT founders. Additionally, AI can help investors focus solely on a company’s merits rather than biases, leading to more diverse and high-quality startup partnerships.

The PricewaterhouseCoopers Digital IQ Survey of 2017 indicated a substantial investment in AI by industry professionals, with a majority expecting to continue investing in AI in the future. This trend is driven by the increasing visibility and repeatability of metrics and data points defining successful startups, which provides investors with a clearer understanding of investment opportunities.

Venture capital, although centered around people and relationships, is not immune to biases. An example of bias in the industry is June Manley’s experience when pitching her software enterprise company in 2015. To counter such bias, she established Female Founders Faster Forward, a nonprofit organization utilizing a tech-based model to minimize bias and increase funding for female founders.

The organization uses a Startup Investment Model Index, based on attributes from VC-funded businesses, to provide a score that female founders can use to shield their funding pursuit from bias. With this approach, Manley aims to increase female funding from 3% to 20% by 2020.

AI’s ability to analyze metrics and data points can help cut through potential biases and focus on a startup’s potential for success. It fosters a relationship based on data rather than personal connections and biases, making it an ideal tool for VC firms.

As AI continues to learn and process new information, it enables VCs to make decisions based on a company’s potential, free from personal biases or external influences.

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