To get a roundup of TechCrunch's biggest and most important stories delivered to your inbox every day at 3 p.m. PDT, subscribe here. Welcome to Daily Crunch for May 25, 2021. Whether you are a developer, a startup fanatic or merely someone with wanderlust, we have something for everyone today. Well, except for disappointed investors in Lordstown Motors. They are stuck holding the bag today after the American electric vehicle company announced a pretty awful set of earnings.

For years, Amazon's Mechanical Turk (mTurk) has been a kind of open secret in the tech world, a place where fledgling algorithms can hire human labor on the cheap. If you need a hundred people to trace the boundaries of an object or fill out a survey, it's the single best place to make it happen. But while the project itself is well-known, it's always slightly embarrassing when a company turns up there. In 2017, Expensify was spotted asking mTurk workers to enter data from receipts, leading the company to rush out a statement insisting that the mTurk project had nothing to do with Expensify's main app. In part, it was a privacy issue, but mostly it was embarrassing: Expensify was built on a simple piece of technology -- the ability to extract data from a photo of a receipt -- and the mTurk tasks made it look like that technology was a sham. What if it was human beings extracting that data all along?

Today's leading minds talk AI with host Byron Reese In this episode, Byron and David discuss AI, jobs, and human productivity. Today's leading minds talk AI with host Byron Reese Byron Reese: This is Voices in AI brought to you by GigaOm, I'm Byron Reese. Today our guest is David Barrett. He is both the founder and the CEO of Expensify. He started programming when he was 6 and has been at it as his primary activity ever since, except for a brief hiatus for world travel, some technical writing, a little project management, and then founding and running Expensify. Welcome to the show, David. David Barrett: It's great of you to have me, thank you. Let's talk about artificial intelligence, what do you think it is? How would you define it? I guess I would say that AI is best defined as a feature, not as a technology. It's the experience that the user has and sort of the experience of viewing of something as being intelligent, and how it's actually implemented behind the scenes. I think people spend way too much time and energy on [it], and forget sort of about the experience that the person actually has with it. So you're saying, if you interact with something and it seems intelligent, then that's artificial intelligence? That's sort of the whole basis of the Turing test, I think, is not based upon what is behind the curtain but rather what's experienced in front of the curtain. Okay, let me ask a different question then– and I'm not going to drag you through a bunch of semantics. But what is intelligence, then? I'll start out by saying it's a term that does not have a consensus definition, so it's kind of like you can't be wrong, no matter what you say. Yeah, I think the best one I've heard is something that sort of surprises you.

Artificial intelligence (AI) comes in many shapes and sizes. No longer reserved for enterprises, small businesses can leverage conversational chatbot technology in particular for everything from sales and support to maximizing cash flow. It's time to embrace the chatbot revolution. For small to midsize businesses (SMBs), adding a dash of conversational intelligence to your organization is a great way to both drive customer engagement and help streamline your in-house operations with a contextual helper. Chatbots are embedded in all sorts of chat and collaboration experiences today, and you can find thousands of them in Facebook Messenger, WhatsApp, Slack, Skype, and a host of other applications and services we use to communicate and get work done. Chatbots are exactly what they sound like: a chat with a bot.

It's increasingly unremarkable for consumers to use artificial intelligence tools in their daily lives. Machine learning algorithms power your smart assistants, organize your vacation photos, and even analyze your health data. But human beings pick up the slack for those automated technologies more often than you might realize. And that means that real people can sometimes access user data that customers thought would only be seen by machines. In one particularly glaring case, that included detailed, potentially sensitive information culled from expense reports.

The lives of marketing technology officers, chief marketing technologists, and other martech professionals are often complicated and draining. Whether they're in control of buying decisions or implementing new marketing tools, the swing between the excitement for a new solution to the drudgery of actually supporting those solutions can take a large toll. From budget burdens to committing their team's man hours--the payoff for every new implementation has to be worth it. As a marketer for a large B2B company, imagine you're presented with a scalable solution that would improve the efficiency of your customer service, reduce overhead, and could operate 24/7. Oh, and it would be entirely in-house--no third-party service or call center that's likely to muddle your brand image. Sounds like a dream, right?