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Resolved Strategies LLC

Data? We don’t have time for data!  A realistic look at law enforcement use of and need for human trafficking data.

• The amount of human trafficking data is overwhelming
• Differences between data, information, and intelligence
• Law enforcement has cultural resistance to change, concerns about data accuracy and applicability, institutional barriers and bureaucratic inertia, and reluctance to utilize data.
• Steps to establishing law enforcement buy-in
• Law enforcement needs accurate data on prevalence, effectiveness, and efficiency that will build public trust.

Breakout Session with Lt. Jake Schauer (Alvin Police Department)

• There are issues of labor trafficking being done by large shell companies for which it is difficult to find the owners and ownership changes quickly.  Need ownership transparency.
• Law enforcement polices and regulations may not change quickly to adhere to new laws, such as changes in relation to child welfare.  Need more rigorous training for law enforcement to understand child welfare laws and for social workers to understand law enforcement policies and procedures.
• Law enforcement needs data for probable cause or exigency.  Need one statewide agency to which all other agencies report and share data.
• U.S. Department of Homeland Security, U.S. Department of State, and U.S. Department of Labor each have significant work related to international law enforcement and human trafficking.
• There is little consistency in law enforcement data collection related to human trafficking.  It depends upon local requirements.  FBI is the only agency required to report to DOJ.  Agencies are not mandated to report their crime statistics to the FBI.

University of California at Irvine 

A participatory approach to case management: Co-creation of effective anti-trafficking programming based on self-identified strengths, needs, and priorities of survivors.

• Need for trauma-informed, participatory approaches to case management
• Existing data ecosystem:  Academic, anti-trafficking organizations, collaborative
• Dimensions of survivors’ well-being, strengths, and vulnerability
• Building collaboration through data

Collaboration through Data (Breakout Session)

• Opportunities are opening for nonprofits to build relationships with researchers at academic institutions
  • Nonprofits are looking to collect in-field base settings data
  • When working with research partners, make sure that you (as the non-profit) are setting them up for success
  • Need academic partners who are advocates in the human trafficking world
• Strategies need to be better aligned to what survivors are needing in the moment.
• Need to be able to articulate data policy/language to the general public.

Moody's Analytics 

Combating forced labor: Innovative data solutions for risk assessment

• Today’s global market demands that businesses ensure their supply chains are free from human rights violations, especially forced labor.
  • Due to the increasing regulatory, commercial, and reputations stakes, it is crucial to identify and address these risks.
  • Firms must manage forced labor risks for compliance purposes while navigating a lack of data visibility and compliance complexities.
• Moody’s and The Rights Lab are levering data and technology to assist businesses in identifying and mitigating the risk of forced labor within their supply chains.
  • By utilizing technology for data collection, they can pinpoint risks in three key areas: industry, geography, and business operations.
  • This process generates an overall risk score for each company, vendor, and client, aiding organizations in managing their risks effectively.
  • The forward-looking risk-based approach provides companies with an automated, scalable, and consistent measure of risk, enhancing data sharing with suppliers.

Human Rights Due Diligence (Breakout Session)

• Moody’s and The Rights Lab leverage data and technology to assist businesses in identifying and mitigating the risk of forced labor within their supply chains
  • Bank Secrecy Act – finding red flags around human trafficking, forced labor, and money laundering
  • Use data to determine high-risk behavior
• High-risk industries: fashion, hospitality, agriculture, janitorial, construction, restaurants, care for persons with disabilities, salons and massage, retail, carnivals, childcare, domestic work, drug distribution
  • Companies can sometimes work on their score, but high-risk industries and locations are hard to change.
• Human rights due diligence is a new term, and people are still figuring out what should go in it.
• Moody’s pulls together data so that companies are safer for workers.

Altus^TM / Engage Together^©

The Data Science and People-Science of Designing Community-based Solutions

• Areas where solutions are needed to eliminate human trafficking:
  • Prevention
  • Identification
  • Exit
  • Restoration
  • Reforms
• Frameworks:  Solutions to human trafficking, solutions to aging out of foster care, community-based, designing, science, people, data
• Lessons learned: Solutions, community-based, designing, science, people, data
• Engage Together^© - Transformational community assessment project

Designing Data-driven Solutions (Breakout Session)

• Lack of available or accessible data:
  • Key problem in every community:  Organizations don’t know each other
  • To catalyze community action without creating unneeded duplicity of effort requires data driven insights to help a community understand how to better work together to meet needs and fill gaps
• Gaps in data:
  • Human trafficking of males
  • Labor trafficking
  • Youth aging out of foster care and justice-involved
  • Standardization of data and siloed data
  • Siloed data
• Potential solutions:
  • Upskill nonprofits on data
  • Anonymize data
  • Find the intersections within data
  • Leverage Machine learning
  • Develop a data dictionary with common language

AnnieCannons

Reclaiming Data to Transform Anti-trafficking Systems

• Introduction to work of AnnieCannons: “We train, prepare, and connect individuals who have experienced human trafficking to sustainable careers in tech.”
• Data governance in anti-trafficking work:  Ownership, deployment, models, creation of new systems
• Resourceful:
  • The right resource, the first time - Using technology to transparently collect/share/secure data, control of own data by those with lived experience
  • A mobile app for survivors
  • A web app for service providers

International Justice Mission

Scaling Survivor Restoration through Data Science

• International Justice Mission’s (IJM) data-informed approach uses Assessment of Survivor Outcomes (ASO) to support Aftercare managers around the world in their care of survivors.
  • Survivor engagement:
    • In community events, health services, and legal proceedings
    • At the point of rescue, at the mid-point of their restoration journey, and at end of their time with our Aftercare program
  • Insights:
    • Optimal time for survivors to be in the Aftercare program
    • Specific indicators in the initial ASO that highlight survivors requiring more support
    • How to optimize delivery of services and train partner organizations

Prevention Now

Can Machine Learning Prevent Human Trafficking? Using Data and Technology to Tailor Policies and Programs Toward Vulnerable Populations in Your Community

• Using data and technology to tailor policies and programs toward vulnerable populations in communities to prevent human trafficking in communities
• A novel machine learning approach to identify local risk factors to guide collaborative, data-oriented prevention programs
• Focused on partnerships, insights from data analysis, and action

University of Texas at Arlington

Law Enforcement’s Response to Child Sex Trafficking:  Fostering Collaborative Response and Implications for North Texas

• Human trafficking is a multifaceted, dynamic issue requiring an inter-disciplinary approach to addressing this egregious crime.
• Recent NIJ-funded study examined law enforcement’s response to child sex trafficking.
  • Research questions:
    • What are the housing needs of children and youth who are impacted by CSEC?
    • What is the availability of these housing options?
    • Has the federal legislation impacted housing options in meaningful ways?
  • Quantitative survey of 3,500 law enforcement agencies, over 100 structured investigator interviews, and 80 in-depth interviews exploring forms of law enforcement and community collaboration in 11 purposefully chosen communities.
  • Results:
    • Temporary housing added a new trauma when survivors had to leave.
    • Survivors have complex needs not addressed through housing alone.
    • Service providers have little time to determine feasibility of housing solutions for survivors.
    • Few housing alternatives for survivors.

Breakout Session

• How do you use community engaged research in your work?
  • Using literature to determine and understand if it is community centered
  • Attending conferences and identifying community organizations that are interested in data
  • Working with specific stakeholders that are driving the solution to better serve the community
  • Conducting a study to better understand the gaps in knowledge
  • Engage with local academic institutions
  • Build a relationship with community partners
• Why would you want to work with researchers and what is the advantage of working with the university?
  • Pair with the university to be rewarded for your time and work
  • Build tangible evidence of your program
  • Universities have unique resources

Street Grace

Measuring the Magnitude and Traits of Local Consumer Demand for Sex Trafficking

• Innovative technology that provides data useful for informing policy and practice designed to reduce sex trafficking
  • Leverages artificial intelligence to engage individuals responding to online ads for the commercial sexual exploitation of minors
  • Provided free of cost to law enforcement agencies
  • Deployment quickly provides measures of the scope and traits of local consumer-level demand for the sex trafficking of children within any defined jurisdiction

Breakout Session

• All data sets are imperfect and have flaws - think about different kinds of data and how we can use it
• Think about:
  • What you want to accomplish before seeking data
  • Who you are trying to convince:  Law enforcement, legislators, health officials, funders, others
  • Who are the targets of the desired change:  Traffickers, buyers, others
  • What is monetary and time cost

BCFS Common Thread

Harm Reduction through Data to CSEY Survivors

• Harm reduction with data can be achieved by setting up documentation software with data points aimed at gathering quantitative data that tells a story.
• Ability to quickly track and pull reports showing:
  • How engaged, connected, the needs of, and felt safety of our survivors.
  • How well the implemented intervention strategies are working.
• Multiple datapoints reduce the need for long narratives written by advocates which can harm our survivors if subpoenaed and not written with safe documentation.
• Using these techniques prevents survivors from having to retell their stories and re-live their trauma.

New Friends New Life

• City of Dallas’ Human Trafficking Dashboard
  • Tells a story that can inspire action and change lives
  • Data against human trafficking:  Shining a light, revolutionizing investigations, hope restored, support in action, breaking barriers, inclusive support
• Primary Participants:
  • City of Dallas’ Data Team
  • Dallas Police Department
  • New Friends New Life
  • Traffick911
  • Bob’s House of Hope / Ranch Hands Rescue

Gallaudet University

Human Trafficking and Disabilities

• Models of disability:  Medical, social, human rights
• For those who are deaf or hard of hearing (DHH)
• Risk factors for DHH population
• Methods of prevention
• Accommodations to reduce vulnerability and create access
• Data collection approaches
• Deaf and hard of hearing resources

Alvin Police Department

Breakout Session with Doug Gilmer, Ph.D. (Resolved Strategies LLC)

• There are issues of labor trafficking being done by large shell companies for which it is difficult to find the owners and ownership changes quickly.  Need ownership transparency.
• Law enforcement polices and regulations may not change quickly to adhere to new laws, such as changes in relation to child welfare.  Need more rigorous training for law enforcement to understand child welfare laws and for social workers to understand law enforcement policies and procedures.
• Law enforcement needs data for probable cause or exigency.  Need one statewide agency to which all other agencies report and share data.
• U.S. Department of Homeland Security, U.S. Department of State, and U.S. Department of Labor each have significant work related to international law enforcement and human trafficking.
• There is little consistency in law enforcement data collection related to human trafficking.  It depends upon local requirements.  FBI is the only agency required to report to DOJ.  Agencies are not mandated to report their crime statistics to the FBI.

Fortenberry Firm PLLC

• Represents human trafficking survivors against hotels
• Collaboration of data
• Identify the issue and scope of trafficking
• Using research and data to show the impact of what’s going on
• Criminal prosecutions
• Key data makes a difference (i.e. police reports, etc.)
• Evidence of “benefit” to accused
• Open records/FOIA
• Online hotel reviews
• Sex advertisements
• Hotel industry standards
• U.S. State Department
• McCain Institution
• Civil verdicts and published settlements
• Can sue outside of Texas because there is a federal mandate

Eagle Venture Fund

• Eagle Venture Fund - An impact venture fund that only invests in for profit tech companies that have a positive impact on Economic Opportunities, Healthcare Access, and Combatting Trafficking and produce investment returns for investors
• While most impact investment funds focus on Donated Impact – the impact from donating a portion of the profit which reduces investor’s returns, Eagle’s focus is on Direct impact – impact from delivering the product or service that creates the impact which increases investor’s returns. With Eagle’s model of investing, the more impact, the more revenue, and the higher the investor returns.
• Eagle Freedom Fund is one of Eagle’s funds that only invests in for-profit companies that combat human trafficking
• Market Analysis: the counter HT technology market is poised for rapid expansion and growth because of the increased awareness, increased regulations, and increased litigation and court cases. Market growth will also be fueled by the unprecedented emergence of AI-powered tools, geospatial tracking tools, visual processing technology, and victim support tools

Cloudflare / ÕýÆ·À¶µ¼º½ University

Technology That Helps: Using Multimodal AI to Help Combat Human Trafficking

• Traditional human trafficking data tools focus on single modalities not multiple, so there is fragmented evidence. Investigators need tools for cross-modal insight.
• Challenge has been accessing data and aggregating data.
• Multimodal AI integrates data from multiple sources and formats (text, video, images, audio)
• Considerations include what data can be accessed, size of data, and memory

ES Counseling and Consulting

Mental Health Data in Trafficked Populations: Patterns and Implications

• Many different needs of survivors
• Time-limited program/services; specific criteria; lack of funding and training; failure to understand complexity; treatment approaches don’t address developmental trauma
• Compounding trauma: Developmental Trauma + commercial sexual exploitation and trafficking + trauma surrounding the trafficking experience
• Restoration of victims:
  • Need period of stabilization before diving into therapy.
  • Making sure there is a feeling of safety and autonomy and consistency.
  • More survivor-led programs
  • Relational advocacy program
  • Empower survivors to advocate for themselves