Home News AI Four investors discuss why AI ethics must not be underestimated.

Four investors discuss why AI ethics must not be underestimated.

Four investors discuss why AI ethics must not be underestimated.

Massive amounts of money are going toward AI. Nonetheless, AI models are facing discrimination, such as when it comes to mortgages being denied to African-American homebuyers.

It is rational to inquire about what place ethics has in the creation of this technology, and possibly even more significant, where do investors fit in as they scramble to put money into it.

A founder recently told TechCrunch+ that due to how quickly ideas and systems are being created, modified, and overhauled, it can be hard for ethical principles to keep up. Therefore, there is a certain responsibility for investors to make sure that these new technologies are being developed in an ethical manner by the founders producing them.

TechCrunch+ deliberated with four venture capitalists concerning how ethical principles are related to AI and how entrepreneurs can be persuaded to be more aware of prejudices and act morally.

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Certain investors said they work to address this by thoroughly researching the morality of a founder to decide if they will keep making decisions the business can back up.

Alexis Alston, principal at Lightship Capital, stated that the presence of founder empathy is an outstanding sign for them. They do not desire their investments to cause any harm to the world while still trying to obtain a profit.

Some investors believe that being inquisitive and asking tough questions is an effective way to distinguish between good and bad investments. Deep Nishar, a managing director at General Catalyst, commented that “all technologies have undesirable results, whether it’s prejudice, loss of autonomy, privacy invasions, or something else. Our investment approach zero’s in on recognizing these negative impacts, conversing about them with the startup personnel, and assessing if any measures have been taken, or will be taken, to counterbalance them.”

The actions of various governments are focused on AI with the European Union having adopted laws related to machine learning, the United States creating an AI task force to investigate potential dangers, and a Bill of Rights created last year. As venture capitalists invest in AI in China, an essential question arises: is there a way to insure ethical principles are followed internationally in regards to AI?

Discover what procedures potential investors use to perform due diligence, the tell-tale signs of a good investment, and their thoughts about legislation regarding Artificial Intelligence.

We had a conversation with:

    Alexis Alston is the principal of Lightship Capital, Justyn Hornor is an angel investor and serial entrepreneur, Henri Pierre-Jacques is the co-founder and managing partner of Harlem Capital, and Deep Nishar is the managing director of General Catalyst.

Alexis Alston is the Head Administrator of Lightship Capital.

When investing in an AI company, what research do you do to determine how its AI model is preventing or creating bias?

It is essential for us to recognize completely what data the model relies on, the origin of the data and how it is being purified. We perform considerable technical research with our general partner, whose concentration is on AI, to guarantee that our models can be educated to lessen or do away with bias.

We all recall when it was impossible to turn the water on with one touch in order to wash our darker hands, and those moments when a ‘mistake’ caused Google image search to link Black people with apes. I promise to make sure no such erroneous models are included in our portfolio.

What would be the consequences for the rate of innovation in the U.S. if laws similar to the European Union’s laws on machine learning were to be passed?

I am not confident in the American government’s capacity to pass efficient and reliable laws around AI as they lack expertisein this area. It takes a while for them to decide on laws and to invite experts to assist in their decision making.

I don’t think laws can have much of an effect on the progress of ML because the way legal systems are typically set up. This reminds me of the law’s response to the widespread use of synthetic drugs in the U.S. a while ago. In that case, even laws never managed to catch up with the development of the drugs.