Empathy Should Guide What We Automate

Technology can make our interactions more efficient. Empathy helps us understand which interactions matter.

Empathy has become a recurring theme in my adult English conversation classes.

We might begin by discussing a difficult colleague, a disagreement between friends, or a decision someone doesn’t understand. As the conversation develops, we often discover that the challenge isn’t finding the right English words. It’s understanding another person’s perspective.

These discussions have influenced how I think about automation and artificial intelligence.

I’ve spent much of my professional life helping organizations improve systems, simplify processes, and eliminate unnecessary effort. I believe technology can make people more productive and capable.

But as AI becomes increasingly capable of communicating on our behalf, I’ve been considering a different question.

Are we using technology to strengthen human connection, or are we gradually replacing the interactions that help us understand one another?

Understanding What People Actually Need

Empathy isn’t simply being kind or agreeing with someone. It involves making an effort to understand another person’s experiences, concerns, and perspective, even when they differ from our own.

That understanding can change how we approach a problem.

Consider someone contacting customer support because something has gone wrong.

From an operational perspective, the objective might be straightforward: identify the problem, provide a solution, and resolve the request as efficiently as possible.

An automated system might accomplish all three.

But what if the customer has already tried several times to resolve the issue? What if they’re worried about losing money, missing a deadline, or disappointing someone who depends on them?

The technical problem might be simple. The human experience might not be.

A correct answer doesn’t necessarily address what the person needs.

This doesn’t mean every customer needs to speak with a person. Some would prefer an immediate automated solution. Others need reassurance, an explanation, or someone willing to take responsibility.

Empathy helps us recognize the difference.

Before deciding what to automate, we need to understand what people value about the interaction.

When AI Helps and When It Blurs the Line

AI has made the distinction between human and machine responsibilities less obvious.

We can use it to explain complicated subjects, translate conversations, prepare for meetings, draft thoughtful messages, and practice difficult discussions.

These capabilities can improve human connection.

Someone who struggles to express an idea in English can use AI to organize their thoughts before a meeting. A manager can explore different approaches to delivering difficult feedback. A teacher can identify learning gaps and spend more time helping students develop their capabilities.

In each example, technology supports the person rather than replacing their participation.

But consider what happens when we automate the interaction itself.

Instead of helping a manager prepare for a difficult conversation, we automatically generate and deliver the feedback. Instead of helping someone understand a friend’s concerns, we compose a sympathetic response for them. Instead of helping a teacher recognize a student’s needs, we replace the exchange with personalized instructions.

The results might be accurate, considerate, and useful.

Yet we may have removed an opportunity to understand, reflect, and better understand another person.

Communicating empathy isn’t the same as practicing empathy.

An AI-generated message can express understanding. Whether the sender has developed that understanding is another question.

That distinction matters because empathy isn’t just an outcome. It’s also a capability we develop through experience.

What Conversation Classes Have Taught Me

I see this distinction in my English conversation classes.

Students can use AI to improve grammar, expand vocabulary, prepare responses, and practice speaking. These tools are especially valuable for learners who hesitate because they’re worried about making mistakes.

But meaningful conversation requires something more.

We have to listen, interpret what someone means, and decide how to respond. We sometimes misunderstand. We encounter unfamiliar perspectives. We discover that our assumptions don’t hold up.

A discussion about workplace expectations might become a conversation about fairness. A disagreement about a social issue might reveal different cultural experiences. A question about someone’s decision might help us understand circumstances we hadn’t considered.

These moments aren’t distractions from learning English. They’re part of what makes the learning meaningful.

My goal isn’t simply to help students produce grammatically correct sentences. It’s to help them become more confident and better able to communicate with others.

AI can support that goal through preparation, practice, and feedback. It can even provide a comfortable environment for exploring sensitive subjects.

But if students only practice with systems designed to respond patiently and predictably, they may miss opportunities to navigate the uncertainty of real conversations.

People don’t always respond as we expect. They have their own experiences, emotions, assumptions, and priorities.

Understanding those differences is part of learning to communicate.

Choosing What to Automate

I don’t think the answer is to establish a permanent boundary between humans and machines.

AI will keep developing, and people will find new ways to benefit from it. Technology may even handle some interactions better, especially when privacy, accessibility, consistency, or immediate assistance matters most.

Instead, I think empathy should guide three decisions.

Automate unnecessary effort. When work is repetitive, predictable, and adds little human value, technology can free people to focus elsewhere.

Use AI to develop capability. When technology helps someone prepare, understand, learn, or participate more effectively, it can strengthen their ability to engage with others.

Preserve meaningful human participation. When an interaction involves trust, vulnerability, disagreement, responsibility, or personal growth, consider what might be lost if people no longer participate directly.

These aren’t rigid categories. A situation might benefit from all three.

For example, a manager could automate performance reporting, use AI to identify patterns and prepare questions, and then meet with an employee to understand the circumstances behind the results.

The technology reduces administrative effort. The conversation creates an opportunity for understanding, feedback, and shared responsibility.

Of course, keeping a person involved doesn’t guarantee empathy. A rushed, distracted, or judgmental human response may be less helpful than a thoughtful automated one.

Human participation matters only when we make it meaningful.

That’s why the decision can’t be simply whether a machine can perform a task.

We also need to ask what the people involved might gain or lose.

Making Room for Human Connection

I’ve long believed that automation should eliminate unnecessary effort and help people become more capable.

I’m increasingly convinced that empathy needs to guide how we apply that belief.

We can automate administrative work so teachers have more time to engage with students. We can simplify reporting so managers have more time for meaningful conversations. We can use AI to prepare for difficult discussions instead of avoiding them.

But saving time doesn’t automatically produce better relationships.

We still have to choose how to use the time we’ve gained.

And perhaps that’s the larger challenge.

It’s easy to measure how quickly a system completes a task, how many interactions it handles, or how much money it saves. It’s harder to measure whether people feel understood, whether trust has improved, or whether someone has become more capable of navigating a difficult relationship.

What we can measure easily isn’t necessarily what matters most.

Empathy reminds us that the people affected by our systems aren’t simply users, customers, employees, or students. They’re individuals whose experiences and needs we may not fully understand.

Technology can help us serve them better. It can also create distance when we aren’t paying attention.

The goal shouldn’t be to preserve human involvement simply because it’s human, or to automate something simply because we can.

It should be to make deliberate choices about how technology helps people understand one another, develop their capabilities, and build healthier relationships.

That’s the measure of automation I want to pay more attention to: not just what technology allows us to accomplish, but what it helps us become.