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SUMMARY:Language models as temporary training wheels to improve mental hea
 lth - Tim Althoff\, Univeristy of Washington
DTSTART:20241119T160000Z
DTEND:20241119T170000Z
UID:TALK219091@talks.cam.ac.uk
CONTACT:Cecilia Mascolo
DESCRIPTION:Abstract: Access to mental health care falls short of meeting 
 the significant need. More than one billion individuals are affected by me
 ntal health conditions\, with the majority not receiving the necessary tre
 atment.\n\nIn this talk\, I will describe how human-AI collaboration\, cri
 tically enabled by language models\, can improve access to and quality of 
 mental health support. Language models have the potential to act as tempor
 ary training wheels providing immediate support and guidance to help indiv
 iduals develop essential mental health skills. This approach emphasizes th
 e importance of using these tools as initial aids rather than long-term cr
 utches. By offering structured assistance\, practice\, and feedback\, lang
 uage models can help individuals and professionals learn skills\, such as 
 cognitive reframing\, emotional regulation\, and conflict resolution. Howe
 ver\, the ultimate goal is for individuals to gradually transition away fr
 om dependence on these models\, fostering sustained skill development and 
 long-term well-being. This talk will describe how language models can be d
 eveloped towards these aims and evaluate their effectiveness across multip
 le randomized trials and real-world deployments with over 150\,000 partici
 pants.\n\nLearn to challenge unhelpful thinking with your personal AI assi
 stant at https://bit.ly/changing-thoughts\n\n\n\nBio: Tim Althoff is an as
 sociate professor in the Allen School of Computer Science & Engineering at
  the University of Washington. Tim’s research seeks to better understand
  and empower people through data and computation. His AI research has dire
 ctly improved mental health services utilized by over ten million people a
 nd informed federal policy. Tim holds a Ph.D. degree from the Computer Sci
 ence Department at Stanford University. His work has received various awar
 ds including WWW\, 2x ICWSM\, ACL\, UbiComp\, and IMIA Best Paper Awards\,
  the SIGKDD Dissertation Award 2019\, and an NSF CAREER Award. Tim's resea
 rch has been covered internationally by news outlets including BBC\, CNN\,
  The Economist\, The Wall Street Journal\, and The New York Times.
LOCATION:Online
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