AI, the Transcription Economy, and the Future of Work

Gabriel is a professional transcriber, and for years he earned a middle-class living. In the early 2000s he'd make up to $40 an hour transcribing corporate earnings calls. He'd sit at his desk, “knock it out” for hours using custom keystrokes, and watch the money roll in. “I sent my son to private schools and university on transcribing,” he tells me. “It was a nice life.”

But in the past decade, the bottom fell out. As audio recordings went digital and broadband spread, clients could ship work to India and the Philippines. Meanwhile, buzzy Silicon Valley startups emerged—like Rev, a sort of Uber and 800-pound gorilla of the transcription world. It has moved the industry toward an on-demand gig model. Since Rev charged customers a flat rate of $1 per audio minute—less than half what transcription firms historically charged—Gabriel's pay sank even further. On top of it all, AI started nipping away at the industry, with machines now able to rapidly transcribe some audio as well as humans do.

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Facebook is willing to pay users for just recording audio for voice recognition 

Facebook has announced it will pay select users who agree to record their voice to improve its speech recognition technology. According to The Verge, the social networking giant company will pay select users to record snippets of audio through a new programme called "Pronunciations" in its Viewpoints market research app. If you qualify to be part of the programme, you'll be able to record the phrase "Hey Portal," followed by the first name of a friend from your friends" list.

"You'll be able to do this with the names of up to 10 friends, and you have to record each statement twice," the report said on Thursday.

The Facebook announcement comes at a time when several tech companies like Apple, Microsoft, Amazon and Google have paused their audio transcription programmes after reports emerged that third-party contractors were listening to audio recordings.

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The 7 malignant myths of machine learning

The biggest obstacle to unleashing the power of enterprise artificial intelligence (AI) and machine learning (ML) isn’t a lack of data scientists – it’s a lack of leaders who understand ML.

Tech titans, industrial giants, and startups alike are falling over themselves to hire leaders with the business acumen and ML know-how to spot the most valuable opportunities and guide projects from inception to business value.  Unfortunately, we are in the midst of a pandemic of ML misconceptions and illiteracy.

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Impact of AI and ML on data management

Businesses are turning to artificial intelligence and machine learning to help to create effective data management systems. While the implementation is challenging, the outcome can be autonomous, self-managing databases.

Businesses are turning to artificial intelligence and machine learning to help to create effective data management systems. While the implementation is challenging, the outcome can be autonomous, self-managing databases. Walt Kristick explains how.
Data management is vital for modern businesses, covering the process of collecting, storing, organizing and maintaining the data created and collected by an organization. Due to the complexity, some organizations are turning to new technology as part of their digital transformation initiatives. The increase use of artificial intelligence and machine learning with data management processes will require a reassessment of infrastructure and for companies to select the write types of systems and to get to grips with process reengineering.

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The Future Of Customer Service Isn't As Simple As AI Or Human

Automation and artificial intelligence are transforming the customer service industry and raising difficult questions about the role that humans will play in the workplace of the future. For years, pundits have been largely relegated to one of two camps: mass unemployment predictors and budget-minded capitalists (paywall). But recently, more and more thought leaders have shifted into a third camp, which argues that the future of customer service and business in general will be rooted in AI-human collaboration.

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Choosing Between Rule-Based Bots And AI Bots

Until a decade ago, the only option people had to reach out to a company was to call or email their customer service team. Now, companies offer a chat team to provide better round-the-clock customer service. According to a Facebook-commissioned study by Nielsen, 56% of people would prefer to message rather than call customer service, and that’s where bots come into play.

Bots are revolutionizing the way companies interact with their customers. A decade ago, bots were considered a passing tech fad. However, that debate has been put to rest now as major companies like Amazon, Microsoft, Facebook and others have started deploying bots in almost every area of their business.

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