Guest Post — Your Next Reader Is a Machine, and We Are Ready
Machine readers replacing human readers can sound like a threat. Today’s post argues that our community is well prepared to face these challenges and seize the opportunities.
AI Will Lead Us to Need More Garbage-subtraction.
Generative AI wants to make information cheap, but will people want to read it? Are we ready for more productive writers?
Patterns In and Across Aggregated Data — Is "Anonymous" Collaborative Filtering Really Safe?
New research demonstrates that there’s a decent likelihood that your data exhaust can be used to find out sensitive things about you.
Reconsidering the Abstract — Are the Unintended Consequences Mounting?
The abstract is an element of scientific papers we take for granted. Is that a good idea in a networked information environment gravitating to usage-based measures?
Cups, Buckets, Pools, and Puddles: When the Flood of Papers Won’t Abate, Which Do You Choose?
When most papers submitted ultimately get published, and in an age driven by pooled philosophies and practices, are we already participating in a “filter failure” of immense proportions?
Is OUP’s “Anti-Google” Just a Half-Million Words of Filter Failure?
The OUP has launched Oxford Bibliographies Online, hoping to filter major fields down to a high-quality, peer-reviewed reference kick-start. But does a wordy filter actually filter in the networked world?
How Networked Information Changes the Filter Metaphor for Journals
Image via Wikipedia I think by the end of this post, you won’t think of your editorial filter in quite the way you did when you woke up this morning. The metaphor of a filter has informed our thinking about […]