Artificial intelligence is frequently used as an umbrella term for a broad range of potential uses of computer algorithms to accomplish a cognitive task in a relatively short time-frame. In the more specific context of the information community, “smart systems” may be expected to do everything from the handling of a routine voice request to phrase extraction from the literature for data discovery and re-use to image assessment. The possibilities are intriguing, but there are hesitations as well. It’s very easy to replicate existing social biases. There are discussions over the ethical uses of artificial intelligence.
How might intelligent infrastructure support the work of the information community? Librarians are considering whether a virtual assistant might be able to aid in providing research support. Seen from an adjacent space -- apart from the work of academic researchers -- content and platform providers are considering how the use of algorithms, data and analytics may serve to enhance smart services for users. This 90-minute webinar will offer a glimpse into the practical application of artificial intelligence in support of research workflow and outputs.
Confirmed speakers: Bohyun Kim, Chief Technology Officer and Associate Professor, University of Rhode Island Libraries; Michael Upshall, Head of Sales and Business Development, UNSILO; Michael Hemenway, Chief Information Officer, Iliff School of Theology;
AI & Us: Are We Intelligent Machines?
Recent developments in artificial intelligence (AI) is generating much discussion about what intelligent machines will be capable of in the near future. Many organizations and businesses are enthusiastically looking at ways to apply AI to automate more work and reduce their business costs, while the public is raising many concerns regarding privacy, surveillance, deep fakes, biases, job displacement, and so on. This presentation will provide an overview of (i) what today’s AI can do and (ii) how AI works under the hood. It will also invite the attendees to reflect on two issues: (i) how learning and research may change in the new era of AI and data-ism and (ii) whether we are simply one type of data-processing system as the emerging data-ism claims, in which data is thought to be of the utmost value.
AI and the Publishing Workflow
AI presents both opportunities and challenges for publishers. Because of its topicality, AI generates rather wild responses, ranging from frantic enthusiasm to fears it will cause us all to lose our jobs. To try to make some sense of AI in the publishing environment, this presentation outlines some of the types of AI that can be useful today, and identifies some use cases within the academic publishing workflow. Finally, there are some suggestions for the role of the information community in implementing and evaluating AI tools.
Libraries cultivating TRUST-based AI
At ai.iliff, we are working to build a TRUST-based AI ecosystem. Libraries, as places for the collaborative cultivation of information capacities, can provide a critical apparatus for facilitating this TRUST-based ecosystem. Information professionals have a long history of championing cross-disciplinary collaboration, careful attention to data sets, and a deep commitment to user experience and rights. These values are essential if we are to build an AI ecosystem based on Transparency, Responsibility, User Centeredness, and Sustainability Together. We will look at managing data bias as an example of how these values play an important role in the development of AI.