Thisprojectwas developedaspartof Parson’sSpring2024 ExternalEngagement Studio.
We’dliketothankour professor,Jennifer Rittner,ourpartnersat TheMayor’sOffice, AndreaHamiltonand EvaWong,fortheir supportandguidance. WethankJohnBuckley forshapingthedesign briefandforhis thoughtfulengagement withourstudio community.
We’dthankDr.Victoria Wilkins,Dr.Ennio Ammendola, JenVanderMeer,and ourinterviewand workshopparticipants.
AnexplanationofhowWatershedties intocurrentframeworksforcommunity building
Asitemap&mockupsoftheproposed solution,withanexplanationofthe featuresavailabletokeystakeholders
Anoverviewofmajorchallengesto implementation,andourstepsto mitigatethem
Atimelineoftheproject’sactionplan through2039
Alistofresourcesthatguidedour researchandworkingprocessthis semester
Briefbiographiesaboutthemembers ofthisstudioteam
How does verbal and visual language shape interpersonal as well as societal conversations, dialogue and ultimately, narratives?
Through our research of over 200 signals, we found that heightened exposure to doom-scrolling leads to the generation of neurotoxic noise, fostering addictive tendencies.
Transforming addiction triggers into detoxification signals We need to reinterpret and reframe verbal and visual language not only as a cause of addiction but also as a barometer of the wellbeing of our youth, a compass directing us towards detoxification by cultivating healthier cognitive environments.
gIn a world where the digital landscape is as pervasive as the physical, ensuring the health and safety of our online communities becomes increasingly important. Just as public safety departments diligently monitor water sources for pathogens to safeguard public health, we face the challenge of identifying and mitigating harmful content on social media platforms.
Leveraging advancements in AI technology, our proposal introduces the Wellbeing Quality Index (WQI), mirroring the Water Quality Index, to proactively trace pathogenic rhetoric online as a predictor for self- or community harm.
By systematically analyzing social media content, our solution aims to provide real-time insights into the emotional well-being of individuals and communities. By quantifying the quality of online discourse, the WQI offers a key value proposition in fostering safer and healthier digital environments, ultimately promoting collective well-being in our interconnected world.
As we envision the landscape of well-being for young adults in 2039, it's evident that the evolution of language and online discourse will play a pivotal role in shaping their experiences The solution we propose, the Wellbeing Quality Index (WQI), is poised to revolutionize how we approach online interactions and community well-being
In a future where online discourse continues to evolve rapidly, the WQI serves as a beacon of accountability, providing real-time insights into the emotional impact of digital interactions, and bringing in human experts to design meaningful interventions as issues arise.
We recognize the significant privacy challenges inherent in developing an AI model that analyzes all public social media content in NYC, particularly when deployed by the government. Safeguarding user privacy remains at the forefront of this project, and we're committed to addressing these concerns proactively. Our approach includes stringent measures to ensure user anonymity, as well as initiatives to encourage community-wide participation through participatory collage workshops
Watershed is a tool that harnesses AI to trace pathogenic rhetoric online as a predictor of self or community harm, fostering safer and healthier digital environments. This data allows the city government to generae faster, more effective, and timely interventions through AI-driven budget allocations and expert recommendations.
Watershed aims to achieve the following:
Foster safer digital environments by using AI as a predictor
Improve and analyze existing programs to enhance community’s wellbeing
Assess existing verbal and visual digital signals as wellbeing indicators
Streamline government agency communication or interactions through one platform
Our system equips various mayoral agencies with tailored tools to enhance community health and engagement The Mayor's Office of Technology and Innovation oversees the deployment and management of system settings. Meanwhile, the Mayor's Office of Community Mental Health utilizes the dashboard to gauge health metrics across neighborhoods, identifying areas for intervention and community engagement initiatives.
The NYC Department of Youth and Community Development could leverage the platform to facilitate youth development and community development initiatives. Additionally, the Mayor's Office of Special Projects and Community Events could utilize Watershed to drive impactful community events and initiatives. Our project operates as a clearinghouse, promoting inter-agency collaboration by facilitating communication and coordination between agencies, leading to a stronger sense of wellbeing in communities and decreasing the amount of redundancy in current projects
1 DataCollection
TheAItooldetectsearly indicatorsofmentalhealth issuesthroughverbaland visuallanguagescanson socialmedia.
2
PassingaThreshold
Onceasignalpassesa threshold,anautomatic alertissenttorelevant expertswhoassessand validatedatacollection findings.
3
AlertingExperts
Expertsassistinleveraging existingneighborhood interventionsand identifyinggapswithin them.Prioritizationof fundingallocationsare alsogeneratedbyAI.
4 Resolution
Interventionsare appropriately implemented,alongwith progresstracking.
In our hypothetical scenario, the AI tool diligently collects data from all major social media platforms, including verbal and visual language scans, to detect early indicators of mental health issues.
As the tool sifts through the vast volume of social media posts, it identifies a specific trend a surge in posts concerning loneliness among young adults in Brooklyn. Once this signal surpasses a threshold of 0 007% among the 13-26 age demographic (meaning 100-300 posts on this topic within a 24 hour period), an automatic alert is triggered, prompting the system to notify relevant experts.
In this scenario, a youth engagement specialist is flagged as an expert, drawing on their specialized knowledge in addressing mental health challenges associated with youth loneliness. Upon receiving the alert and validating incoming data points, the specialist immediately springs into action, collaborating with a local community organization to plan a book club event aimed at fostering social connections and combating loneliness.
Throughout this process, the AI system continues to play a crucial role by generating prioritized recommendations for funding allocations, ensuring that interventions are appropriately implemented and progress is effectively tracked.
Thisisaquicksitemap,showingthewaysausercannavigateWatershed
starthere
LOG-IN
DISCLAIMERPAGE
three(3)viewoptions
HOME OCMH/CITY OFFICIAL
CITYOVERVIEW
NEIGHBORHOOD ANALYSIS
CURRENTPROGRAM ANALYSIS
LOCALEVENTSIN WELLBEING
LOCAL INTERVENTIONS
STANDARDACCESS DATAHOMEPAGE
STANDARDACCESS ALERTGENERATION
STANDARDACCESS EXPERTDATABASE
ADMINACCESS MEDIAPOSTANALYSIS
ADMINACCESS THRESHOLDSETTINGS
SIGNALREVIEW
INTERVENTION PLANNER
AnoverviewoftheWatershedinterfaceforsomeoneworkingintheTechnologyoffice,who wouldtakeresponsibilityformanaginganddevelopingthemodel
The first screenshot shows the social media post database, which aggregates data from various platforms and scrapes posts in realtime. Each post is analyzed and tagged based on its content, underlying emotional sentiment, and geographical region. This database serves as the foundation for the AI model, enabling accurate predictions and insights into community well-being trends
Users with standard access, distinct from admin access, are limited in their visibility of the social media data. While administrators have comprehensive access to the entire database, including detailed posts and analyses, standard users have restricted access. This tiered system ensures data security and privacy, allowing only authorized personnel to view sensitive information.
The threshold percentage for detecting concerning signals in NYC social media posts, focusing on young people aged 13-26, is set between 0.005% to 0.01%. This translates to monitoring approximately 125 to 250 posts per day at the lower end and 250 to 500 posts per day at the higher end, considering an average daily post volume of 25,000 to 50,000 from this demographic. Adjustments to the threshold percentage depend on factors like desired sensitivity, social media activity volume, and available resources for review and intervention
The platform provides city tech workers with the capability to define specific thresholds for different topics or themes of concern. Using a user-friendly interface, they can access a panel where they can configure thresholds based on parameters such as the number of posts, frequency, or sentiment analysis scores. By writing functions within the platform, these thresholds can be customized to align with the city's priorities and the sensitivity desired for detecting relevant signals. This flexibility allows for tailored alert triggering based on the specific objectives and concerns of the city, ensuring that potential issues are promptly identified and addressed
Continues to Inform the AI Model
Subject matter experts play a key role in the refinement of the AI model, as they review triggered alerts and assess the severity and potential impact on well-being by examining contextual factors and language nuances in social media posts. Through classification and analysis, experts categorize content into thematic areas, such as body image issues or mental health struggles, facilitating effective intervention prioritization
Additionally, data annotation enriches the understanding of underlying issues, contributing to algorithm refinement aimed at improving the accuracy of detecting wellbeing concerns. Regular performance evaluation ensures the system's reliability, with iterative improvements based on expert feedback and evaluation results ensuring ongoing enhancement and effectiveness in supporting well-being monitoring efforts.
AnoverviewoftheWatershedinterfaceforthoseworkingintheOCMH,orforcityofficialsin chargeofmonitoringneighborhoods’wellbeing
The City Official view first shows heat map focused on the wellbeing in the city, with an emphasis on those areas requiring more attention or intervention. This gives a general overview of the locations that require more focus. Below it, a marquee displays the general wellbeing for each neighborhood. Once clicked, this leads to the Per Neighborhood Analysis.
The dashboard also includes a quick snapshot of highlighted signals or trends happening in the neighborhoods
The City Official view allows city officials, mainly from the OCMH, to have a quick glimpse of the overall and neighborhood wellbeing. While equipped with Watershed (AI), assessments, analyses, and improvements can also be made.
One of the features showcase the current events in each borough These are highlighted events that focus on wellbeing When an event is “processed,” local officials in the specific neighborhood are then notified of such event, which invites for promotion.
One of the main focuses of the City Official view in Watershed zones in on the Per Neighborhood Analyses, where city officials get a Watershed report of any particular neighborhood in New York City. Each analysis looks into the existing or current trends or signals in the area, a quick AI analysis of the location, suggested local wellbeing interventions, and a status of the neighborhood.
from the OCMH Watershed is a program dedicated to improving existing programs as well. These pages show reports of each existing government program, seeing whether or not the program is efficient, or doing well. The AI model also suggests potential improvements or insights, which can be used for future adjustments or budget planning.
AnoverviewoftheWatershedinterfaceforsubjectmatterexpertsandcommunityorganizations, whodesigninterventionsbasedonsignalsraisedbytheAImodel
Experts are required to adhere to a privacy disclaimer, acknowledging their responsibility in safeguarding the confidentiality and integrity of individuals' data. This measure underscores the commitment to protecting sensitive information and upholding privacy standards throughout the review process, thereby fostering trust and confidence among users and stakeholders.
These screens display signals awaiting the experts' response, providing a centralized hub for managing interventions and tracking progress Here, experts can view a comprehensive list of flagged signals that require their attention, allowing for efficient prioritization and timely review.
The intervention tracker enables experts to monitor the status of ongoing interventions, track follow-up actions, and ensure continuity in addressing identified concerns.
Additionally, the running chronicle offers a real-time log of the experts' latest analyses and assessments, serving as a valuable resource for tracking trends, identifying patterns, and informing decision-making processes.
Subject matter experts meticulously analyze flagged signals originating from various social media platforms such as Facebook, Instagram, TikTok, and more. They delve into the context and content of each flagged signal, leveraging their expertise to discern potential implications for affected communities. By understanding how the flagged content may impact well-being, experts can devise tailored interventions aimed at uplifting these communities.
The intervention planner serves as a pivotal tool for subject matter experts, facilitating the strategic coordination of interventions to address flagged signals. Central to this process is the identification of suitable community organizations and stakeholders for collaboration, ensuring that interventions are intricately tailored to local dynamics and needs Experts leverage their nuanced understanding of community contexts to forge meaningful partnerships and design interventions that resonate with residents. Additionally, the planner enables experts to explore potential funding avenues, providing insights into resources that could bolster intervention efforts and maximize their impact on community well-being.
1 DataHandlingand Privacy
Howmightweusedatafor socialgoodwhilestill protectingindividual privacy?
2 AIAccuracy improvement
Howmightwecapturethe expressionsofhuman mentalstatesthatAIalone cannotfullymeasure?
3 PublicAcceptanceand Trust
Howmightweovercome resistancetoAIemotion analysisand collaborativelyintegrate thissolutionintosociety?
Employing strong encryption techniques to secure user data both during transmission and storage.
When handling sensitive data such as mental health information, it is of utmost importance that privacy is fully protected and citizens' rights are safeguarded.
To alleviate privacy concerns, Watershed will implement four key safety measures.
Ensuring that users are informed about the data collection process and providing clear options for consent.
Conducting regular audits of data handling practices to ensure compliance with privacy regulations and identify any potential vulnerabilities.
Integrating privacy considerations into the design and development of the AI system from the outset, rather than as an afterthought.
How might we grasp the nuanced intricacies of human emotions that elude the grasp of AI alone, and thereby enhance the precision of AI models?
Furthermore, what measures might we undertake to assuage the resistance towards having emotions analyzed by AI, fostering citizen acceptance of this technology? We propose a unified approach to address these pivotal inquiries: engaging in dialogue to explore how citizens articulate their emotional experiences through visual and verbal modes of expression.
ng their collages. Reduces stigma around discussing mental health.
Collaborative AI Model Growth
Input artifact-emotion connections into AI to grow the model with citizen input. Co-creation fosters AI acceptance and enables citizen opt-in. Provides a dialogue platform between citizens and officials
Create user-friendly UI/UX mockups & dashboards for decision-makers
Establish multistakeholder taskforce for oversight
Engage public through workshops
2029
Integrate emotional scoring system with municipal data systems
Establish data security, anonymization & storage protocols
Establish citizen advisory board for regular input & guidance
2039
Integrate AI-driven emotional scoring into decision-making process
Foster ongoing public engagement, transparency & regular updates
Amnesty International “New York Is in Danger of Becoming a Total Surveillance City ” Amnesty International, August 16, 2021. https://www.amnesty.org/en/latest/news/2021/06/scale-new-york-police-facial-recognition-revealed/.
Chancellor, Stevie, and Munmun De Choudhury. “Methods in Predictive Techniques for Mental Health Status on Social Media: A Critical Review ” Nature News, March 24, 2020 https://www nature com/articles/s41746-020-0233-7
CISA CISA roadmap for artificial intelligence Accessed April 23, 2024 https://www cisa gov/sites/default/files/202311/2023-2024 CISA-Roadmap-for-AI 508c.pdf.
Díaz, Ángel. “New York City Police Department Surveillance Technology.” Brennan Center for Justice. Accessed April 23, 2024 https://www brennancenter org/our-work/research-reports/new-york-city-police-department-surveillancetechnology?ref=blog salesforceairesearch com
Gaind, Bharat, Varun Syal, and Sneha Padgalwar “Emotion Detection and Analysis on Social Media ” arXiv org, June 12, 2019. https://arxiv.org/abs/1901.08458.
Metzler, Hannah, Max Pellert, and David Garcia. “Using Social Media Data to Capture Emotions before and during COVID-19 ” The World Happiness Report Accessed April 23, 2024 https://worldhappiness report/ed/2022/usingsocial-media-data-to-capture-emotions-before-and-during-covid-19/.
Ny State Senate. “Ny State Senate Bill 2023-S7695A.” NYSenate.gov. Accessed April 23, 2024. https://www nysenate gov/legislation/bills/2023/S7695/amendment/A
NYPD “Technology ” Technology - NYPD Accessed April 23, 2024 https://www nyc gov/site/nypd/about/aboutnypd/equipment-tech/technology.page.
Office of Information Technology Services “Cybersecurity ” Office of Information Technology Services Accessed April 23, 2024 https://its ny gov/cybersecurity
Srispens, StateScoop. “NYPD Scrutinized for Not Complying with Surveillance Tech Disclosure Law.” StateScoop, December 22, 2023 https://statescoop com/nypd-surveillance-technology-disclosure-law/
Surveillance Technology Oversight Project, Inc “Zooming in on NYPD Data Sharing ” S T O P - The Surveillance Technology Oversight Project. Accessed April 23, 2024. https://www.stopspying.org/zooming-in-nypd.
WELLBEING ECONOMY ALLIANCE. Wellbeing economy policy design guide. Accessed April 23, 2024. https://wellbeingeconomy org/wp-content/uploads/Wellbeing-Economy-Policy-Design-Guide Mar17 FINAL pdf
IsaMerialesisastrategic designandmanagement studentandindustrial designerwithexperience incivilserviceandworking increativeindustriesinthe Philippines.Sheis passionateaboutbuilding storiesthroughdesign.
TomoMorikawa isa strategicdesignand managementstudentwith experienceasabusiness developerandservice designerinthepublic sector.Sheispassionate aboutfindingthesweet spotwherebusiness, design,andtechnology intersect,whileprovidinga structuredapproachto navigatingambiguity.
XeniaJankovichisa strategicdesignand managementstudentwith previousbackgroundsin thesocialsciencesand businessadministration. Sheispassionatein combiningbothfieldswith designinordertofind uniqueinflectionpoints forcreativeproblem solvinginordertobest driveimpactful innovationsforward.
NsisongUdosenisa strategicdesignand managementstudent,and aUXconsultant.Sheis alwaysexcitedtotalk abouthowstorytellingand interactiveexperiences contributetocommunitybuilding,historical understanding,and speculativethinkingfor equitablefutures.