Deal Dive: AI relationship coach Amorai offers more questions than answers

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By Webdesk


Building and maintaining relationships is hard, and COVID-19 certainly hasn’t helped. Multiple studies have shown that adults have become even lonelier since the start of the pandemic.

Founders try to find technical solutions. There are many startups looking to combat loneliness — some of which emerged years before the pandemic — including senior-focused ElliQ and Replika, which are creating an AI companion, and Infection AI’s Pi, an emotional support bot. But one newer newcomer really caught my eye this week: Amorai.

The startup has built an AI relationship coach to help people grow and foster real-life connections by providing advice and answers to relationship questions. The company was founded by former Tinder CEO Renate Nyborg and was incubated in Andrew Ng’s AI fund. The company just raised an undisclosed amount of pre-seed funding that took just 24 hours to complete, Nyborg told Vox’s Recode Media podcast in April.

While fighting loneliness is a great mission — and some groups of people may be more open to chatting with a bot than a human — it feels like it has the potential to go wrong so quickly. But what do I know? So I pinged an expert.

Turns out I’m not the only one a little wary of this concept. Maarten Sap, a professor at Carnegie Mellon University and a researcher for the nonprofit Allen Institute of AI, shared my concern. Sap’s research focuses on building social common sense and social intelligence into AI. He has also researched the development of deep language learning models that help understand human cognition. Essentially, he knows a thing or two about how AI interacts with humans.

Sap told me that while the idea of ​​creating a tech solution to foster relationships in real life is admirable — and there’s certainly evidence that there will be solid use cases for AI in combating this kind of problem — these makes him think.

“I say this with an open mind, I don’t think it will work,” he said. “Have they done the studies that show how this will work? Do [Amorai] increase [users’] social skills? Because yes, I don’t know to what extent these things will pass.”

The biggest thing that makes him think, he said, is the concern that this type of application will give all users the same advice, good or bad, and that it would be difficult for AI to get the right nuances about certain relationships. . And would people trust AI advice over another person anyway?

“The idea of ​​the pickup artists came to mind,” Sap said. “Is this going to give you the advice to tell a bunch of straight men to nag or sleep with women?” Or are their guardrails for this?

If the model is designed to learn on its own, it can create an echo chamber based on the types of questions people ask. That in turn could point the model in a problematic direction if left unchecked. Bing users may have already learned this the hard way when the AI ​​told people they were unhappy in their marriages.

Juice said one way this could definitely work would be if there was a human touch to it. Human oversight to ensure the app is giving the right advice to the right people could make this a powerful tool. But we don’t know if that’s the case because the company doesn’t answer questions or accept interviews.

This round also shows how deep the FOMO in AI really runs. Someone who researches things like this every day can’t see how this company could really work, and yet Amorai raised money in 24 hours before launch in a bad market.

Of course, investors know more about the company than what’s being released, and these concerns can certainly serve as feedback for the startup. But like many AI startups, I have to assume it was built with good intentions, despite nothing concrete to prove it.

I also don’t believe this was a small pre-seed round – something I usually assume when a company doesn’t disclose the total amount of funding; if it were big you’d want people to know about it – but in this case I think it’s probably the opposite. There is a lot of pressure to raise a lot of money before it is implemented or found to fit the product market.

“When I hear about these kinds of ideas and startups, it’s coming from a good place, but it’s often just the tech solutions mindset,” Sap said.



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