Every generation faces a test of its moral imagination. Ours is this: Human trafficking has evolved into a sophisticated digital enterprise while our response remains stubbornly analog. Case in point: Today, we identify only 1% of victims.
Not 10. Not five. One.
Yet the anti-trafficking movement stands divided. Technologists promise artificial intelligence will revolutionize victim identification. Survivors and advocates warn that algorithms can’t comprehend trauma. Meanwhile, traffickers coordinate across continents using encrypted apps, recruit on social media, and move money through digital channels that leave barely a trace.
This asymmetry is deadly.
Modern trafficking thrives in the gaps — between jurisdictions, between agencies, between the moment someone notices something wrong and the moment they act. A hotel worker suspects something’s amiss. A neighbor sees troubling patterns. A teacher worries about a student. These moments of concern often die in uncertainty. People don’t know what they’re seeing. They fear being wrong. They worry about consequences. So they stay silent.
Technology excels at bridging exactly these kinds of gaps. Behavioral analysis helps people understand what they’re observing. Anonymous reporting channels protect those who speak up. Pattern recognition connects dots across jurisdictions that no single person could see. A report in rural Kentucky links with a pattern in urban Atlanta. Information routes to the right authority in minutes rather than days.
The intelligence community learned long ago that the most effective operations combine human assets with technological capabilities. Humans provide context, intuition, and ethical judgment, while technology provides scale, speed, and pattern recognition. Together, they achieve what neither could alone.
This matters for anti-trafficking work. When we encode the expertise of survivors, law enforcement, and service providers into technological tools, we create a kind of collective intelligence. These systems help communities understand and report concerns while maintaining privacy and building prosecutable cases.
Consider the numbers: Over 300 anti-trafficking technology tools exist globally, yet only a handful are designed for community use. This represents a massive missed opportunity. Communities are where trafficking happens — in neighborhoods, businesses, and schools. Accessible tools transform ordinary citizens from helpless bystanders into active participants in protection.
The key is preserving human agency at every step. Survivors must control their own data. Communities must trust that reporting systems protect both reporters and potential victims. Service providers must retain flexibility to respond to each unique situation. Technology should create possibilities, not dictate outcomes.
We’ve seen what happens when tech companies push “solutions” that reduce complex human suffering to data points. The backlash is swift and justified. But we’ve also seen what happens when we cling to analog methods while criminals embrace every digital advantage: that devastating 1% identification rate.
The most promising approaches recognize this reality. They use AI to handle what machines do best: processing vast amounts of data, identifying patterns, and routing information efficiently. This frees humans to focus on what only humans can do: building trust, providing comfort, navigating complexity, and offering hope.
Privacy and consent must be paramount. Federal compliance isn’t just about checking boxes; it’s about encoding our values into the very architecture of our response. When survivors’ dignity and choice are built into systems from the ground up, technology becomes a tool for empowerment rather than exploitation.
The traffickers have already made their choice. They’ve embraced every technological advantage available. Those who fight for freedom must match their sophistication, not by abandoning principles, but by building tools that embody them.
This is the work of our time: creating technology that serves justice, amplifies compassion, and helps communities protect their most vulnerable members. It requires unprecedented collaboration between technologists and advocates, between those who code and those who care.
Some worry about bias in AI systems, and vigilance is warranted. But technological bias can be identified, measured, and systematically addressed. When we build these tools in partnership with survivors and communities, remain transparent about limitations, and are committed to improvement, we create systems that are more fair and effective than what exists now.
WHITE HOUSE TOUTS TRACKING DOWN MORE THAN 10,000 UNACCOMPANIED CHILDREN WHO CROSSED BORDER
The path forward demands we move beyond tired debates about human versus machine. The future of anti-trafficking work is human and machine, working together. It’s about giving communities confidence to speak up and channels to be heard. It’s about creating systems that honor efficiency and empathy and scale response while respecting individual dignity.
Every day that we hesitate, real people pay the price. They deserve better than our debates. They deserve our best thinking, our most sophisticated tools, and our unwavering commitment to innovation and humanity. And when we get this right, that shameful 1% becomes just a memory of what we once tolerated.
Brittany Dunn is cofounder and chief operating officer of Safe House Project. Lior Weinstein is the chief executive officer of CTOx.