The concept of “big data” has been the subject of considerable hype and speculation in recent years. So much so that the dominant technologies and technical practices that generate big data — data analytics, algorithms and machine learning — are now commonly described as “artificial intelligence” instead. As a result, Ian Bogost argues, there has been “an explosion of supposed-AI in media, industry and technology.” Despite emerging punctures in the big data and AI hype bubbles, it remains hard to dispute that digitally produced, collected and analysed forms of data have been vested with certain powers
I started a list of critical questions for big data in education earlier this week. This is a big topic, raising lots of big questions and serious topics and problems for further debate and discussion. Here, I focus on questions about big data ownership, divides, algorithmic accountability, issues about voice and literacy, and, finally, ethical implications and challenges of big data in education. Who “owns” educational big data? The sociologist Evelyn Ruppert has asked, “who owns big data?” noting that numerous people, technologies, practices and actions are involved in how data is shaped, made and captured.
What do robots eat? Contemporary digital data analytics systems feed on a diet of data produced through human activity. Through this feeding, robotic machines receive the informational nutrition required for their own development: to become smarter, more aware of their environment, more responsive and adaptive in their interactions with people. By eating human data, robots are learning. Feeding Societies The claim that we now live in a consumer society has become commonplace in academic research. People have become voracious consumers, but also, through their participation in social media environments, present themselves as desirable commodities for the