Talk summary / 6:46 min
Mapping the Landscape of AI and Research
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In this video
- 0:02 How AI in research has changed
- 0:58 Assisted discovery
- 1:53 AI as Tool Maker
- 2:42 An agent can find the form
- 3:31 Take a literature review
- 4:19 A small research project today
- 5:10 Everything saved on his drive
- 6:01 Each may need £2,000–3,000 a year
Dominik Lukeš maps how AI in research has changed. When ChatGPT arrived in 2023 the concern was that AI would write or edit papers; by 2026 AI makes independent discoveries and runs full research workflows, much of it true only in the last ten to twelve months. Autonomous discovery gets the headlines but is still the exception, so the lecture concentrates on assisted discovery. He shows what a desktop agent did for a literature review and for a weekend project cataloguing his old community radio recordings, and what this means for research projects, journals and supervision.
You'll come away with
- Three roles of AI, oracle, tool maker and tool user, and why people have moved from chatbots to desktop agents.
- How the agent loop runs through a harness, a model and your computer, and that it can run for minutes, hours, even days.
- Two worked cases: searching Elicit through its API and importing tagged papers into Zotero, and a published radio archive that the agent estimated at three to six hundred hours of work.
- What changes for research: who is on the team, what aims are realistic and what it costs, plus journals overwhelmed with submissions and supervisors who do not know how to supervise new methods.
Narration uses a synthetic voice. This video is an AI-assisted summary of the recorded lecture.