Data is critical to building great AI so much so, that researchers in the field compare it to coal during the Industrial Revolution. Those that have it will steam ahead. Those that dont will be left in the dust. In the current AI boom, its obvious who has it: tech giants like Google, Facebook, and Baidu. <\/p>\n
Thats worrying news. After all, many of these companies have near monopolies in areas like search and social media. Their position helps them gather data, which helps them build better AI, which helps them stay ahead of rivals. For the firms themselves, its a virtuous cycle, but without viable competition, companies can and do abuse their dominance. <\/p>\n
Now a new project from the Mozilla Foundation (the nonprofit creator of the Firefox browser) is experimenting with an alternative to data monopolies, by asking users to pool information in order to power open-sourced AI initiatives. The companys first project is called Common Voice, with the Mozilla foundation asking volunteers to donate vocal samples to build an open-source voice recognition system like the ones powering Siri and Alexa. <\/p>\n
the power to control speech recognition could end up in just a few hands. <\/p>\n
Currently, the power to control speech recognition could end up in just a few hands, and we didnt want to see that, Sean White, vice president of emerging technology at Mozilla, tells The Verge. He says to get data, the big companies can just filter everything coming in, but for other players, there needs to be other methods. The interesting question for us, is, can we do it so the people who are creating the data also benefit? he asks. <\/p>\n
At the moment, Mozilla is just collecting data, but plans to have its open-source voice recognition available by the end of the year. (Will it go in the Firefox browser? White wont say, but adds: We have some experiments planned [for that].) Currently, anyone can go to the Common Voice website and donate their voice by reading out sample sentences. They can also supply biographical information like age, location, gender, and accent. This information will help Mozilla avoid bias in creating its voice recognition systems, says White, and ensure that the technology can handle accents something Google and Apple still struggle with. <\/p>\n
Frederike Kaltheuner, a researcher at Privacy International, says these firms often use AI as a pretext for scooping up valuable personal data, telling users it will enable them to improve certain services. This may be true, she says, but the consequences of sharing this data for society at large is less clear. There is [often] a fundamental conflict of interest between what you need as a citizen, and what is in that companys interest, says Kaltheuner. <\/p>\n
What can open-source data offer that companies cant? <\/p>\n
So how does an initiative like Common Voice lure users away from existing and admittedly convenient services? After all, open-source projects have been around for longer than the internet, but with a few exceptions, they have been unable to compete with commercial products. They simply dont offer a comparable service. <\/p>\n
For Mozilla, the answer is personalization. After all, while AI systems trained on population-sized datasets tend to be good enough for the average individual, they often fail when it comes to serving the needs of smaller groups, or those not represented in their data. (More often than not, the data is just biased toward white males, the industry default.) <\/p>\n
For us to be successful with data commons, there has to be a motivation [for users] other than realizing one day that theyve been giving away all their personal data, says White. We have to make their experience better because theyve participated. In the case of Common Voice, White wants as much accent data as possible to improve voice recognition for these individuals. We want the system to work better for you because some of your data is included, he says. <\/p>\n
Offering personalization in exchange for data is a neat proposition, but its not a silver bullet for those fighting data monopolies. For a start, big firms could make similar offers of their own to users. (Alexa doesnt understand you? Read this 10-minute script and well improve its voice recognition.) Or they could spend money to plug the gaps in their own datasets. Google, for example, gets third-party companies to pay Redditors with accents to record their own voice samples. <\/p>\n
White acknowledges that the Common Voice project doesnt have an answer to a lot of these questions, but says Mozilla is still dedicated to the core cause of open data. It feels like a true democratizing activity, he says. And there are plenty of organizations that share this ethos. Theres machine learning community Kaggle, which has a large store of user-contributed datasets for AI scientists to play with; the Elon Musk-funded OpenAI, which open-sources all its work; and Healthcare.ai, which publishes free-to-use medical algorithms. And some of these manage to both share open-source data and research while selling their own commercial products, like self-driving car startup Comma.AI. <\/p>\n
Although the AI systems we interact with on a daily basis are built on proprietary data, theres a whole world of researchers and institutions publishing useful, if rudimentary, open-source alternatives. <\/p>\n
To take these projects to the next level, though, proponents of open-source data may have enlist higher powers to take on the tech giants. Chris Nicholson, CEO of deep learning company Skymind, says, We may need third parties to step in NGOs, governments, coalitions of smaller private firms and pool their data. Nicholson suggests that sharing health care data can improve medical imaging technology, and driver data can make autonomous cars more natural and intuitive on the road. Sharing these types of datasets, he says, has obvious public benefits. <\/p>\n
Donating your voice, then, may just be the beginning. <\/p>\n
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Mozilla is crowdsourcing voice recognition to make AI work for the people - The Verge<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" Data is critical to building great AI so much so, that researchers in the field compare it to coal during the Industrial Revolution. Those that have it will steam ahead. Those that dont will be left in the dust. Continue reading