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UID:news239@researchdata.unibas.ch
DTSTAMP;TZID=Europe/Zurich:20260902T143646
DTSTART;TZID=Europe/Zurich:20261201T140000
SUMMARY:Agentic AI in Research: Concepts\, Workflows\, and Critical Use
DESCRIPTION:Agentic artificial intelligence (AI) shows great potential for 
 automating data processing in research contexts and is developing quickly.
 \\r\\nUnlike standard chatbots\, which respond to single prompts\, agentic
  AI systems can plan tasks\, use tools\, retrieve information\, organize d
 ata\, and carry out multi-step workflows with varying degrees of autonomy.
 \\r\\nIn terms of research data management (RDM)\, agentic AI systems can 
 perform tasks such as renaming and organizing files\, completing metadata\
 , identifying gaps and inconsistencies in datasets\, converting formats\, 
 and drafting documentation\, rather than having these tasks done manually.
 \\r\\nThis introductory workshop is designed for data stewards\, network m
 embers\, and researchers who wish to learn how agentic AI can support rese
 arch projects\, RDM and data curation. The workshop will explain the pract
 ical meaning of “agentic”\, where these systems may be useful in resea
 rch\, and the risks they introduce.\\r\\nThe session will include a live d
 emonstration of agentic AI\, followed by the opportunity for hands-on expe
 rimentation in a sandbox environment. Participants will learn how to form
 ulate tasks\, evaluate outputs\, document AI-assisted processes\, and dete
 rmine when not to use agentic AI.\\r\\nBy the end of the session\, partici
 pants will be able to:\\r\\nidentify suitable use cases for agentic AI in 
 research projectsdistinguish between helpful automation and unreliable del
 egationdesign simple workflows with agentic AIassess security risks in res
 earch projects when using agentic AI.\\r\\nThe workshop concludes with a d
 iscussion of how agentic AI and other AI tools can be used effectively and
  securely for research projects at the university and the steps needed to 
 achieve this.\\r\\nLecturer\\r\\nDr. Olga Serbaeva (Open Science\, Univers
 ity Library\, University of Basel)\\r\\nCourse Language: English\\r\\nData
  stewards and other members of the university's RDM Network will be invite
 d to this course by email. Other people who are interested in attending th
 e course are asked to contact the coordinators of the Data Stewardship Pro
 gram (researchdata@unibas.ch [mailto:researchdata@unibas.ch]).
X-ALT-DESC:<p>Agentic artificial intelligence (AI) shows great potential fo
 r automating data processing in research contexts and is developing quickl
 y.</p>\n<p>Unlike standard chatbots\, which respond to single prompts\, ag
 entic AI systems can plan tasks\, use tools\, retrieve information\, organ
 ize data\, and carry out multi-step workflows with varying degrees of auto
 nomy.</p>\n<p>In terms of research data management (RDM)\, agentic AI syst
 ems can perform tasks such as renaming and organizing files\, completing m
 etadata\, identifying gaps and inconsistencies in datasets\, converting fo
 rmats\, and drafting documentation\, rather than having these tasks done m
 anually.</p>\n<p>This introductory workshop is designed for data stewards\
 , network members\, and researchers who wish to learn how agentic AI can s
 upport research projects\, RDM and data curation. The workshop will explai
 n the practical meaning of “agentic”\, where these systems may be usef
 ul in research\, and the risks they introduce.</p>\n<p>The session will in
 clude a live demonstration of agentic AI\, followed by the opportunity for
  hands-on experimentation in a sandbox environment. Participants will lear
 n&nbsp\;how to formulate tasks\, evaluate outputs\, document AI-assisted p
 rocesses\, and determine when not to use agentic AI.</p>\n<p>By the end of
  the session\, participants will be able to:</p>\n<ul><li><span>identify s
 uitable use cases for agentic AI in research projects</span></li><li><span
 >distinguish between helpful automation and unreliable delegation</span></
 li><li><span>design simple workflows with agentic AI</span></li><li><span>
 assess security risks in research projects when using agentic AI.</span></
 li></ul>\n<p>The workshop concludes with a discussion of how agentic AI an
 d other AI tools can be used effectively and securely for research project
 s at the university and the steps needed to achieve this.</p>\n<p><strong>
 Lecturer</strong></p>\n<ul><li><a href="https://daw.philhist.unibas.ch/de/
 personen/olga-serbaeva-saraogi/" title="Olga Serbaeva"><span>Dr. Olga Serb
 aeva</span></a><span> (Open Science\, University Library\, University of B
 asel)</span></li></ul>\n<p><strong>Course Language</strong>: English</p>\n
 <p>Data stewards and other members of the university's RDM Network will be
  invited to this course by email. Other people who are interested in atten
 ding the course are asked to contact the coordinators of the Data Stewards
 hip Program (<a href="mailto:researchdata@unibas.ch" title="researchdata@u
 nibas.ch">researchdata@unibas.ch</a>).</p>
DTEND;TZID=Europe/Zurich:20261201T170000
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