Register and join us at 1:00pm PT on August 24!

Call for Contributions

Reality

The world is experiencing a mental health crisis that is in need of immediate attention. In 2017, within the United States alone, an estimated 43 million people (18% of the population) had a mental illness and 9.6 million people experienced thoughts of suicide. About fifty-six percent of such adults did not receive the treatment they needed due to a variety of socio-cultural and economic factors including lack of access to healthcare, a shortage of providers, and a fear of the stigma that may be associated with treatment. Beyond diagnosed mental health conditions, it is estimated that at least 3 out of 5 people have had experiences of mental illness. These statistics hold for global populations as well.

The genesis of mental health conditions is instructive as well. The American Psychiatric Association estimates that 50% of mental illness begins by age 14, and 75% of mental illness begins by age 24. The National Association on Mental Illness in the US tracks suicide as the 3rd biggest cause of death in ages 10-24; 90% of these individuals had an underlying mental illness. These ages are some of the most technologically connected segments of our life span, providing unique opportunities for technological solutions to play a key role in addressing this crisis.

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Responses

Globally, governments, clinical institutions, and technology companies are starting to respond to this escalating crisis. Some examples include: Governments (especially in Europe) starting to establish cabinet level positions for Mental Health, mental health education becoming required in school grades K-12 at a rapidly increasing rate, and partnerships by clinical institutions with communities around general care and prevention. Technology has enabled easier remote access to both active listeners and counselors and psychiatrists through text and video channels.

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RESEARCH

Technical topics & unique opportunities

We are at the dawn of technology supporting good self-care and other-care, especially towards good mental health. The mental health crisis is a huge opportunity for the research, design, and deployment of AI/ML-assisted systems to improve good mental health at scale.

This domain comes with unique challenges. In several mental health scenarios, there isn’t a high degree of agreement between experts on the ground truth of a situation, and culture and its dynamism adds complexity. Datasets can be small or noisy as they capture human expression during periods of desired change. There are often several effective paths forward in any given situation, and not just one “best move”. There is a large cohort of trained providers who would like to use technology well to expand their scale, and to augment their efficacy. There are several other community-centered ecosystems - school, work, religion, others - that play a key role in good mental health and can benefit from technology that leverages their presence. And technology can augment all aspects of fostering good mental health: awareness, assessment, mediation, and maintenance.

This workshop will bring together industrial and academic experts and researchers and field practitioners to elucidate problems, solutions, and paths forward. We invite short papers (anywhere from 2-4 pages + citations) that speak to the topic of designing digitally assisted systems for good mental health. Papers should be submitted here through June 10, 2020. Submissions must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. Accepted papers will be published online, and will not be considered archival. Some topics that your papers might cover include the following (note that this is not a restrictive list!)

  • Requirements for good mental health systems
  • Learnings from digitally assisted mental health systems
  • Dealing with the lack of ground truth
  • Dealing with emotional verbosity in text
  • Supporting human providers over text channels
  • Text and video analysis in support of good mental health
  • Learning over small datasets
  • Predictive models and tools to support good mental health through a variety of channels, from primary care to wellbeing through work to connections with families and communities
  • Building AIs that are aware of, and supportive of the process of improving mental health
  • Deploying cognitive science theories to improve the performance of machine learning
  • Improving cognitive science theories through insights from machine learning systems


Important Dates

June 10, 2020

Workshop paper submissions

July 10, 2020

Workshop paper notifications

August 24, 2020

Workshop date

Accepted Papers

(In order of submission)

Leveraging AI for Psychiatric Research: Natural Language Processing to Assess Loneliness in Older Adults [Video] [Paper]
Varsha Badal, Ellen Lee, Dilip Jeste, Ho-Cheol Kim
Detecting and Explaining Depression in Social Media Text with Machine Learning [Video] [Paper]
Rida Zainab, Rajarathnam Chandramouli
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL [Video] [Paper]
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi, Irina Rish, Jenna Reinen
Profiling Depression in Neutral Reddit Posts: Prediction-Insight Tradeoffs and Mental Health Technology Applications [Video] [Paper]
Molly Ireland, Jonathan Schler, Gilad Gecht, Kate G Niederhoffer
Usable Security for ML Systems in Mental Health: A Framework [Video] [Paper]
Helen Jiang, Erwen Senge

Schedule

The live workshop will be held on August 24 from 1pm to 4pm Pacific Time (UTC-07:00).

The schedule below may evolve.

1:00 - 1:15Greetings & Workshop Introduction, Ajay Chander
1:15 - 1:45Invited talk: Design with Service in Mind, and chat with Chris Wright, NHS Scotland
1:45 - 1:55Connection break
1:55 - 2:15Talk and chat with Ellen Lee and Varsha Badal, on Leveraging AI for Psychiatric Research: Natural Language Processing to Assess Loneliness in Older Adults
2:15 - 2:35Talk and chat with Baihan Lin, on Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL
2:35 - 2:45Connection break
2:45 - 3:05Talk and chat with Molly Ireland and Kate Niederhoffer, on Profiling Depression in Neutral Reddit Posts: Prediction-Insight Tradeoffs and Mental Health Technology Applications
3:05 - 3:25Talk and chat with Helen Jiang, on Usable Security for ML Systems in Mental Health: A Framework
3:25 - 3:35Connection break
3:35 - 3:55Talk and chat with Rida Zainab, on Detecting and Explaining Depression in Social Media Text with Machine Learning
3:55 - 4:15Looking at the Now and the Next: Invited chat with Lily Rahimi, MFT
4:15 - 4:25A View from the Workplace: Invited reflections with Hiroki Hiramatsu, EVP and Head of Global HR, Fujitsu Ltd.
4:25 - 4:30Closing & Community

Organizing Committee

Ajay Chander

Conference Chair, Fujitsu Labs of America

Martha Russell

Stanford University

Anssi Smedlund

Aalto University, Ilmarinen

Program Committee

Rama Akkiraju

IBM Research

Cathrine Dam

Instagram

Senthil Kumar

Capital One

Ajay Chander

Program Chair, Fujitsu Labs of America

Martha Russell

Stanford University

Anssi Smedlund

Aalto University, Ilmarinen