There's been a reckoning in recent years when it comes to measuring bias in machine learning. We now know that these "unbiased" automated tools are actually far from unprejudiced, and there's a growing demand that researchers think about how their products might screw over or endanger the lives of others before they unleash them on society. It's not just the final products we should be worried about, however, but also the consequences of building them. As the world burns in Facebook feeds and in backyards, the carbon footprints of even the most innocuous things are coming under scrutiny. It's sparked debates around AC units, straws, face scrubs, plastic bags, air travel.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

In January, Liz O'Sullivan wrote a letter to her boss at artificial intelligence startup Clarifai, asking him to set ethical limits on its Pentagon contracts. WIRED had previously revealed that the company worked on a controversial project processing drone imagery. O'Sullivan urged CEO Matthew Zeiler to pledge the company would not contribute to the development of weapons that decide for themselves whom to harm or kill. At a company meeting a few days later, O'Sullivan says, Zeiler rebuffed the plea, telling staff he saw no problems with contributing to autonomous weapons. Clarifai did not respond to a request for comment.

Weights & Biases, a startup building development tools for machine learning, has raised $15 million in its second round of funding. The company was started by CrowdFlower founders Lukas Biewald and Chris van Pelt, along with former Google engineer Shawn Lewis. When Weights & Biases launched last year, Biewald (who I've known since college) said he wanted to create the tools needed to "build and deploy great deep learning models." Its initial product allows companies to monitor those models as they develop and train them. "When people build machine learning models they need to track everything that happens -- the code that went into the model, the hyperparameters that go into the model and then basically how well the model does," Biewald told me this week.

Appen just announced that it's acquiring Figure Eight in an all-cash deal that sees Appen paying $175 million upfront, with an additional payment of up to $125 million based on Figure Eight's performance this year. Both companies focus on using crowdsourced labor pools to annotate data, which in turn is used to train artificial intelligence and machine learning -- for example, Figure Eight (formerly known as CrowdFlower and Dolores Labs) says its technology has been for everything from mapping to stock photography to scanning receipts for expense reports. Appen, meanwhile, is a publicly-traded company headquartered in Sydney. CEO Mark Brayan described its technology -- and its "crowd" of more than 1 million remote workers -- as "highly complementary" to Figure Eight, which he praised for its data annotation and self-serve capabilities. "We know that to compete and to be able to deliver even higher volumes, we need a richer set of technologies," Brayan said.

Machine learning is one of those buzzwords that nearly every tech company likes to throw around nowadays -- but according to Lukas Biewald, it represents a genuinely new approach to programming. "Software has eaten a lot of the world, and machine learning is eating software," Biewald said. In his view, there are "fundamental" differences between the two approaches: "One important difference is if all you have is the code you used to train the program, you don't really know what happened … If I had all the code that was used to train a self-driving car algorithm but I don't have the data, I don't know what went down." Along with Chris Van Pelt, Biewald previously founded CrowdFlower (now known as Figure Eight), which launched nearly a decade ago at the TechCrunch 50 conference, and which has created tools for training artificial intelligence. Biewald (who I've known since college) and Van Pelt, plus former Google engineer Shawn Lewis, have now started a new company called Weights and Biases to build new tools for machine learning developers.

Registration is now open for the O'Reilly Artificial Intelligence Conference in NYC, June 26-29, 2017. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Lukas Biewald, co-founder and chief data scientist at CrowdFlower. In a previous episode we covered how the rise of deep learning is fueling the need for large labeled data sets and high-performance computing systems.

When Google open sourced its artificial intelligence engine last week--freely sharing the code with the world at large--Lukas Biewald didn't see it as a triumph of the free software movement. He saw it as a triumph of data. That's how you'd expect him to see it. He's the CEO of the San Francisco startup CrowdFlower, which helps online companies like Twitter juggle massive amounts of data. But after spending time at the Stanford AI Lab, he knows artificial intelligence.

When crowdsourced labor company CrowdFlower recently raised funding from Microsoft, co-founder Lukas Biewald told me his team was focused on technology that allows businesses to supplement algorithms and artificial intelligence with human judgment from crowdsourced labor pools. Now CrowdFlower bringing on more experts to shape the development of that technology. Specifically it's formed a three-person scientific advisory board, made up of Barney Pell (founder/co-founder of startups including Powerset, LocoMobi and Moon Express, who also led an artificial intelligence team at NASA), Anthony Goldbloom (founder and CEO of Kaggle) and Pete Warden (a staff research engineer at Google, where he's the technical lead on the TensorFlow Mobile machine learning project). "With all these different customers and all these different applications, we wanted them to be confident that they're going to get a high-quality algorithm," said Biewald. He's also a friend of mine from college --although we really only talk about CrowdFlower now, which is kinda sad when you think about it.) "One way to make sure all the product decisions we make really reflect the cutting edge was to get some of the world leaders come in and look at our product."