Choosing Connection Over Convenience: 3 Things I’m NOT Using AI For
Artificial intelligence is changing the way we work, learn, and interact—but that doesn’t mean it’s the best tool for every task. As a social worker and educator, I’ve spent a lot of time exploring how AI can support practice, streamline workflows, and enhance learning. But just as I wouldn’t replace a home-cooked meal with takeout every night, there are areas where I deliberately choose not to use AI.
While AI offers incredible efficiency, social work is fundamentally about human connection, emotional intelligence, and ethical decision-making—things no algorithm can replicate. That’s why I’m making intentional choices about where to integrate AI and where to step back. Here are three areas where I’m not relying on AI.
1. Human-to-Human Connection
Building trust with clients, students, and colleagues requires authentic presence, active listening, and empathy—qualities that AI, no matter how advanced, cannot replicate. Whether it’s guiding an MSW student through a difficult field placement experience or engaging in thoughtful discussions with DSW students about leadership and social justice, these moments demand the kind of nuanced human engagement that AI simply cannot provide.
AI can help summarize conversations or analyze data trends, but it cannot replace the depth of a real-time, compassionate interaction. In social work, we don’t just hear words—we listen for meaning, context, and emotion. These moments require connection over convenience.
2. Creative and Ethical Decision-Making
Social work practice involves complex ethical considerations, cultural nuances, and professional judgment. While AI can assist in organizing case notes or generating reports, it should never be the sole decision-maker in ethical dilemmas.
Take, for example, a case involving a child welfare report or a crisis intervention plan. AI might offer templates or suggested responses, but it cannot assess cultural context, lived experience, or systemic inequities with the insight that a trained social worker can. In these moments, I lean on critical thinking, professional consultation, and lived experience—not AI-generated solutions.
3. Teaching and Mentoring MSW & DSW Students
Teaching at the MSW and DSW levels is not just about delivering content—it’s about fostering critical thinking, ethical reflection, and leadership development. While AI can assist with grading, summarizing articles, or even generating discussion prompts, it cannot replace the relational aspect of learning.
When I engage with MSW students on their field experiences or mentor DSW students developing their research, I rely on personal reflection, shared experiences, and professional wisdom—not AI-generated feedback. Learning in social work is about more than knowledge transfer; it’s about guidance and critical engagement with complex issues.
The Bottom Line: AI as a Tool, Not a Replacement
AI is a powerful tool, but it’s just that—a tool. It can support practice, increase efficiency, and enhance learning, but it should not replace the core of what makes social work meaningful: human connection, ethical decision-making, and relational growth.
As social workers and educators, we must make intentional choices about when to lean on AI and when to lean into our human strengths. It’s not about rejecting AI—it’s about using it responsibly and recognizing when only a human touch will do.
What about you? What are some things you choose not to use AI for in your work? I’d love to hear your thoughts!
The content in this blog was created with the assistance of Artificial Intelligence (AI) and reviewed and edited by Dr. Marina Badillo-Diaz to ensure accuracy, relevance, and integrity. Dr. Badillo-Diaz's expertise and insightful oversight have been incorporated to ensure the content in this blog meets the standards of professional social work practice.