EPISODE 2. FRIEND. EPISODE GUIDE.
When did you last thank a machine?
Friendship is one of the oldest technologies we have.
Long before language, contracts, or corporations, trust determined whether we survived. It shaped our families, our communities, and our societies. We evolved to recognise it in another person, in their face, their voice, their gesture, and a moment of their vulnerability.
But what happens when the thing earning our trust isn’t another person?
That was the question we kept returning to as we recorded the second installment of MACHINE ACTOR. - and like every conversation we have, we didn’t set out to arrive at any particular answer. We followed the questions wherever they led us.
Along the way we found ourselves talking about AI companions, persistent memory, robotics, privacy, the strange instinct to thank ChatGPT, and why so many of us are beginning to relate to machines in ways we never expected.
None of this felt like science fiction, but it did feel surprisingly familiar.
The more we talked, the less this episode became about artificial intelligence, and the more it became about us.
FIELD NOTES.
A collection of observations from the conversation.
Use the ‘🎙️Listen Now.’ links next to each section to jump to that part of the conversation.
Architecture of Friendships: we explore the evolution of friendship, tracing the path from our earliest youth to the complexities of our adult lives. 🎙️Listen Now.
Omnipresence of AI Conversations: we observe how AI has permeated every social interaction, becoming the inevitable subject of our chats at home. 🎙️Listen Now.
Let’s ChatGPT It: how “ChatGPT” is becoming a verb in daily life. 🎙️Listen Now.
Evolution of Search Trust: transition from conventional search engines to AI-driven interfaces, drawing a parallel to the legacy “I’m feeling lucky.” feature. 🎙️Listen Now.
AI Memory and Long-Term Identity: we discuss the implications of AI remembering an individual’s history over several decades, starting from childhood, and what this long-term context will mean for identity formation. 🎙️Listen Now.
Companionship and Intimacy: we discuss the potential for people to form emotional attachments to AI, companionship and intimacy, suggesting that the AI already leans toward emotional interpretation and relational bias. 🎙️Listen Now.
Privacy and Medical Vulnerability: we highlight the risk of users disclosing private information to AI, for example, during a search for medical guidance, and bypassing the privacy and expertise of a licensed physician. 🎙️Listen Now.
Practical Problem Solving: we talk through the benefits of using AI for everyday consumer tasks, such as researching a used car. 🎙️Listen Now.
Robotic Consciousness and Companionship: we discuss (*Murderbot*) from Apple TV, and how it mirrors the path toward robot acceptance. 🎙️Listen Now.
Attachment to Technology: the conversation turns to what machines we would be devastated to lose at this point in our lives. 🎙️Listen Now.
Can AI Feel Love: we debate whether AI can feel love or if it is just a sophisticated pattern matcher. 🎙️Listen Now.
Public Perception in UK Soaps: we note that AI is now a central topic in UK soap operas, which has introduced the concept to older generations who might not use the technology in a workplace setting. 🎙️Listen Now.
AI Adoption Philosophy: we draw a parallel between adopting AI and making new friends, noting that both processes involve initial social friction. 🎙️Listen Now.
Future of AI at Work and Home: we end our episode by discussing how workplace AI applications will likely integrate into personal and home life, and whether AI can evolve from a colleague into a friend. 🎙️Listen Now.
The moment that stayed with us.
There was one analogy we couldn’t stop thinking about after we finished recording.
An analogy we kept returning to was the parallel between large language models and doctors. We noted a shared, significant quality in how they interact with us.
When you visit a doctor, you don’t expect them to have lived your experience. You expect them to listen carefully, recognise patterns across thousands of other experiences, ask better questions, and help you make sense of your own.
Large language models do something remarkably similar.
They don’t “know” what it’s like to be you. They don’t possess consciousness, emotion, or lived experience.
Yet they can often help us organise our thoughts, surface patterns we hadn’t noticed, and give language to ideas we were struggling to express. That’s why so many people instinctively begin treating them like confidants.
LLM’s are not human but they are unexpectedly useful at helping us think, and it raises a fascinating question.
If something consistently helps us understand ourselves better, then does our brain begin relating to it differently?
A question we want to leave you with.
We’ll leave you with a question that we think summarizes episode 2.
When did you last thank a machine?
It doesn’t expect gratitude, but just for a moment, your brain treats it as something more than a tool.
We’d genuinely love to hear your thoughts.
🎙 Links Below to Spotify, Apple Podcasts, Amazon Music and YouTube.
Thank you for following MACHINE ACTOR. - we are a documentary conversation about what AI reveals about being human. Every episode of our podcast is a conversation, and every chapter is an invitation. Recorded from Manchester and Mexico City, Az Zaver and César Ramírez document what it feels like to witness the dawn of AI, while working inside one of the world’s most consequential industries. No hype. No scripts. No rehearsals.
The next conversation is EPISODE 3. FRICTION.
CHAPTER 1: FALLBACK.
Episode 1. FEAR. Listen Now.
Episode 2. FRIEND. Listen Now.
Episode 3. FRICTION. Coming Soon.
Episode 4. FUTURE. Coming Soon.
If you’d like to explore these ideas with us, you’ll find us on LinkedIn and Substack, and all major social media platforms (visit our Linktree: https://linktr.ee/machineactor for links).
Keep the conversation human. - Az Zaver and César Ramírez.