Billions of dollars flow into artificial intelligence. However, AI models are already affected by bias, as evidenced by mortgage discrimination toward potential black homeowners.
It’s reasonable to ask what role ethics play in building this technology, and perhaps more importantly, where investors fit in as they rush to fund it.
One of the founders recently told TechCrunch+ that it’s hard to think about ethics when innovation is so fast: people build systems, then break them, then tweak them. So some of the onus is on investors to make sure that these new technologies are built by founders with ethics in mind.
To find out if this is happening, TechCrunch+ spoke with four active investors in the space about how they think about ethics in AI and how founders can be encouraged to think more about biases and do the right thing.
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Some investors said they deal with this by doing founder ethics due diligence to help determine whether to continue making decisions the company can support.
“The founder’s compassion is a huge green flag for us,” said Alexis Alston, director at Lightship Capital. “These people understand that while we are looking for market returns, we are also looking for our investments so that they do not create a negative impact on the world.”
Other investors think asking tough questions can help separate the wheat from the chaff. “Any technology brings with it unintended consequences, be it bias, reduction of human agency, invasion of privacy or something else,” said Deep Nishar, managing director at General Catalyst. “Our investment process revolves around identifying these unintended consequences, discussing them with the founding teams and assessing whether safeguards are in place or will be put in place to mitigate them.”
Government policies also target AI: the European Union has passed machine learning laws, and the US has submitted plans for an AI task force to start looking at risks associated with AI. This is in addition to the AI Bill of Rights introduced last year. With many venture capital firms pouring money into AI efforts in China, it is important to ask how global ethics within AI can be applied across borders as well.
Read on to find out how investors approach due diligence, the green flags they look for and their expectations from regulations in AI.
We spoke with:
Alexis Alston, Director, Lightship Capital
When investing in an AI company, how much due diligence do you do about how its AI model can detect or address bias?
For us, it is important to understand exactly what data the model takes, where the data comes from and how it is cleaned. We take a great deal of technical care with our AI-focused GP to ensure that our models can be trained to mitigate or eliminate bias.
We all remember our inability to automatically turn on the taps to wash our darkened hands, and the times when a Google image search “accidentally” equated black skin with primates. I will do everything in my power to make sure we don’t end up with models like this in our portfolio.
How might the US passing machine learning laws similar to those in the European Union affect the pace of innovation that the country sees in this sector?
Given the lack of technical knowledge and sophistication in our government, I have very little confidence in the ability of the United States to pass accurate and enforceable legislation around machine learning. We have a long tail when it comes to timely legislation and for technical experts to be part of task forces to inform our legislators.
I don’t actually see any legislation making any significant changes in the pace of money laundering development, given how our laws are usually structured. Similar to the race to the bottom for legislation around designer drugs in the United States a decade ago, legislation hasn’t been able to keep up.