• "Metrics are à la mode. Once it was plain old bibliometrics, now we have scientometrics, informetrics, webometrics, cybermetrics, digimetrics, tagometrics. Neologisms abound. The widespread availability of Web log files affords unprecedented opportunity for assessing the visibility, productivity, and performance of individual scholars, research groups, institutions, and nation states…
• Of course, information science has long been concerned with the quantitative analysis of scholarly communication and publishing behaviors. Latterly, however, there has been a renaissance of sorts and we are witnessing spectacular growth in the volume and variety of bibliometric research and experimentation, not just within information science but also in other disciplines.
• As I observed some years ago, there 'will soon be a critical mass of Web-based digital objects and usage statistics on which to model scholars' communication behaviors - publishing, posting, blogging, scanning, reading, downloading, glossing, linking, citing, recommending, acknowledging - and with which to track their scholarly influence and impact, broadly conceived and broadly felt' (Cronin, 2005, p. 196). What, then, are the implications of these developments?..."
The excerpts above are from the Introduction to Volume 44 (2010) of the Annual Review of Information Science and Technology (ARIST). The Introduction was by SLIS Dean Blaise Cronin - the editor of ARIST. SLIS faculty member Debora Shaw is the associate editor of ARIST, and SLIS faculty member Hamid Ekbia contributed a chapter titled "Fifty Years of Research in Artificial Intelligence" (see excerpt below.)
ARIST is published by the American Society of Information Science and Technology and Information Today.
Artificial Intelligence has come of age. The year MMVI marked the fiftieth anniversary of the Dartmouth Conference, where the term Artificial Intelligence was accepted as the official label of a new discipline that seemed to hold great promise in the pursuit of understanding the human mind. AI, as the nascent discipline came to be known in public and academic discourse, has accomplished a lot during this period, breaking new grounds and providing deep insights into our minds, our technologies, and the relationship between them. But AI has also failed tremendously, making false promises and often manifesting a kind of unbridled enthusiasm that is emblematic of Hollywood-style pecuniary projects. This review seeks to capture both of these aspects: AI's successes, accomplishments, and contributions to science, technology, and intellectual inquiry, on one hand, and its failures, fallacies, and shortcomings, on the other.
Posted October 29, 2009