Publishing & Technology: And for an Additional Fee, We’ll Build a Machine to Read it for You as Well
Brian Tibbetts is a literary agent with MacGregor Literary. Every Wednesday, Brian posts about trends in the publishing industry and developments in technology that impact the industry. You can find him on Twitter @BRIANRTIBBETTS
This week in Publishing & Technology we’ll be talking machine learning, curated content, and discoverability. This week in Digital Book World Yasmine Askari reported on the launch of Canadian company Intellogo and their machine-learning based software’s potential applications in the publishing industry. According to the article, the new software will use machine learning to help publishers compare manuscript submissions with their current and back catalogs as well as using consumers read lists to custom tailor offerings by reader preference.
As anyone who has struggled to find good comps for a potential project can attest, this might be a fantastic new tool for editors in evaluating potential projects. Then again, it might be another step toward the automation of already tenuous positions. Regardless, it’s sure to help further maximize profitability forecasting, erroneous or otherwise.
What seems far more chilling is the idea that machine learning can use algorithms to mine our preferences and customize what we see as available for purchase. Discoverability is the core of successful book marketing. Using machine learning, tweaked as it will inevitably be to showcase content that is most likely to drive sales, will inevitably narrow the titles presented to readers rather than expanding it. And, If this argument seems a little too familiar, refresh yourself with another look at Mike Shatzkin’s oft referred to post Do ebook consumers love bestsellers, or does it just look that way? In which he argues that commerce (as expressed through a variety of factors) and not consumer preference, is the primary driving force behind the continuing success of best sellers, in terms of discoverability.