ABC7 News: Using AI Technology for Good

Well, we live in one of the largest, if not the largest tech hubs in the world. And as you might expect, many of the companies right here in the Bay Area are keeping a close eye on the developments with AI technology like ChatGPT. So joining us this morning is Jim Kaskade, the CEO of Conversica, which is a local company that has been working on AI technology.

Good morning and thank you for being with us.

Hi guys. Thanks for having me.

It seems like this world of ChatGPT, AI is so expansive. How does your company fit into all of this?

Well, first, I just have to tell you that this is probably one of the fastest-growing emerging tech in the history of tech.

So we're extremely excited to be a part of this. Conversica has been involved with AI since 2007, so we've been taking advantage of advanced technologies like machine learning, deep learning, but with Generative AI, it is transformative. So now it's a question of, how do you apply this?

Because it's almost infinite in terms of the number of things you can do. Just watching the shooting hoops in the segment just before this, it can't shoot the basket for you, but it can tell you how to do it better. It can analyze. And I think this type of intelligence is really going to provide a lot of really advanced applications across any vertical.

For us, at Conversica, we're just trying to commercialize it. We're trying to make sure it's enterprise-ready. We're taking into consideration the advanced risks that it represents, and making sure that when people apply it for enterprise business and commercial applications, it doesn't get 'em in trouble.

Brands are sensitive to that, of course.

Okay. So if a company would work with Conversica, how do you envision them using your technology?

Well, with the many applications of GPT, ChatGPT and large language model technologies, you can apply it to creative writing and tutoring and education and language translation. But the way we apply it is we've incorporated it into a digital assistant. So essentially allowing companies to create digital workforces that augment their human workforces and offload a lot of menial tasks.

Specifically around revenue generation. So we're trying to help companies during the slow economy figure out how to do more with less. And digital is one of those opportunities. So just imagine every one of your teams focused on, increasing revenue having an assistant, having a helper, somebody who can do a lot of the hard work for you.

I think people would hear that and feel like, okay. If I do that as a person, I might potentially lose my job. Do you feel like we have to shift how we think about what jobs are going to be prioritized or available in the future with the increased use of this technology?

Yeah, job loss is definitely top of mind.

I think whenever there was some major inflection point of technology, starting back at the printing press, to the steam engine, to the telegraph, to the light bulb—and even now, with self-driving cars, it always seems like, okay, if the car's gonna drive itself, I just lost the driver in terms of a job.

But I think what you have to think about is it really gives us an opportunity to think about more high-value tasks and really advance our careers.

And it opens up opportunities for people to come up with new ways to impact and then leading to new careers.

So I don't think any of the past transformations of tech have really caused job loss. It's actually caused job increases.

I know some people might have concerns about this technology, the rate that it's developing and how it might be used. What do you see as the biggest concerns and how is Conversica trying to address those?

Yeah. Big concerns are around the lack of recency in the data that comes from these large language models and how accurate they are. So it's equivalent to people worried about fake news or just inaccuracy in terms of the facts themselves.

And then there's a big fear of inherent bias. These technologies are trained on the corpus of the world wide web, and it comes with its inherent biases.

Those are big ones. There's a little bit of a fear around copyright and the use of the content, and if there are commercial use rights around it.

And all of this boils down to providing a way to package and protect when a client or large brand, you name any top company, applies this.

So you have to make sure that you can actually bring in more recent data into these technologies. Make sure that they're presenting and representing their brands with accurate information about that brand. And that every bias that a brand would be sensitive to is actually filtered out. And those are all the things that we've done since we started leveraging the technology three years ago.

You know, it's kind of hard to believe that it's just taken off as of late last year. And we've been working on it for so long. But it's been a hard problem to be able to harness this type of advanced technology for commercial use cases.

Well, we appreciate you joining us and the years of work you've put into this. And we know in many ways it's still just beginning. So we will keep in touch with you as we continue to see how it evolves.

Well, thank you for having me.

Thank you, Jim. We'll be right back.