Dinner meets Data

James Mairs • July 16, 2025

From Devilled Eggs to Data: What a 7-Course Meal Taught Me About Global Cuisine 

Over the weekend, I hosted two Eden Smith Directors and their wives for a dinner party. It was a night of great company, conversation - and seven courses of food inspired by French classics. 

Behind every carefully plated dish is a story - not just of flavour, but of history, culture, and, yes, even data.... so here are my reflections, with a data twist

The Menu: 

Canapés: 

  • Paprika-Dusted Devilled Eggs 
  • Mini Smashed Pea & Mint Tortillas 
  • Tomato & Onion Bruschetta with Sweet Balsamic Glaze 

Amuse Bouche: 

  • Mushroom Soup with Crispy Pancetta & Balsamic Mushrooms 

Starter: 

  • Petit Tartiflette with Cornichon Salad 

Salad: 

  • Warm Beetroot, Sweet Potato & Apple Salad with Roquefort Mousse 

Main: 

  • Sous Vide Fillet Steak with Mustard-Infused Mash, Honey-Roasted Carrot, Caramelised Shallots & Edamame 
  • Finished with Bone Broth & Red Wine Jus 

Dessert: 

  • Raspberry & White Chocolate Semifreddo with Raspberry Coulis 

Palate Cleanser: 

  • Lime-Infused Mango with Raspberry Sorbet & Mint 



At first glance, this is the stuff of my culinary dreams. But zoom out just slightly, and you realise: this menu is also a mirror. It reflects a centuries-long evolution of how we eat, why we eat the way we do, and how food is an ever-evolving cultural code. 


Naturally, I did a little research (and yes, pulled some data)… Let’s tuck in! 

The Psychology of Courses: Why We Love to Sequence 

Why do we enjoy meals served in courses? The answer goes deeper than "it's fancy." 

The concept of multi-course dining dates back to Ancient Rome, where feasts began with a gustatio (appetiser), moved through mains, and ended with secundae mensae (dessert). But it was the 18th-century French who codified the structure into what we now know as the "tasting menu" or table d’hôte - a fixed, chef-curated journey of flavours. 


Each course serves a purpose: to awaken, surprise, satisfy, cleanse, and close. It’s not just a meal - it’s a data-informed experience designed to guide the diner’s palate through peaks and valleys of taste, texture, and temperature. 


Tiny Bites, Big Data: The Canapé and Amuse-Bouche 

Even the smallest dishes carry history. 

  • Canapé comes from the French word for “sofa,” describing how a topping sits atop a base - like a person on a couch. 
  • Amuse-bouche, or “mouth amuser,” emerged in the 20th century as a way for chefs to show off a flash of creativity before the main show. 


In both cases, you’re looking at micro-expressions of culinary identity. Think of them as the “elevator pitch” of a chef’s worldview - one bite, one idea, one statement. 

Global Palates: What the Data Says 

One of my guests requested a South East Asian-themed menu next time. So, I compared popular dishes across Western and Eastern cuisines to explore flavour preferences and cultural differences. 

The results are probably not very surprising … and probably hasn’t changed since the 80’s! 

Western Cuisine 

- Starters  🍅 Soup of the Day (35%) 🥖 Pâté with Toast (30%) 🥗 Smoked Salmon Salad (25%) 

- Mains🐟 Fish & Chips (45%) 🍗 Roast Chicken (40%) 🥩 Beef Wellington (30%) 

- Desserts🍮 Sticky Toffee Pudding (50%) 🍰 Cheesecake (40%) 🍫 Chocolate Brownie (35%) 

Eastern Cuisine 

- Starters  🥟 Spring Rolls (40%) 🥟 Dumplings (35%) 🥙 Samosas (30%) 

- Mains  🍣 Sushi/Sashimi (50%) 🧺 Dim Sum (45%) 🍛 Butter Chicken (40%) 

- Desserts  🍡 Mochi (45%) 🍯 Gulab Jamun (40%) 🥭 Mango Sticky Rice (35%) 

 

This isn’t just about taste - it’s about climate, culture, and consumption habits. Western dishes lean towards cream, meat, and dairy. Eastern menus favour rice, spices, fermentation, and balance between hot and cold, soft and crunchy. 


What’s next on the menu? 

Menus evolve. But they’re also a canvas for cultural storytelling - and the data underneath tells us who we are, where we’ve been, and what we value. 

The next dinner party menu will have a South East Asian twist. Think lemongrass instead of shallots, tamarind instead of balsamic, pandan leaf instead of vanilla. 


Final Bite 

Whether you’re a data scientist, home cook, or curious diner, food is one of the richest datasets around

So next time you’re plating up dinner, ask yourself: 
  • What story is this dish telling? 
  • What journey is it taking you on? 
  • And what kind of data - cultural, emotional, nutritional - is being served? 

Because a great meal doesn’t just feed the stomach. It feeds the mind. 

Until then, keep eating curiously and thinking analytically. 


By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
Woman and man touching hands, digital data flowing between them, with digital head projections.
By Eden Smith December 3, 2025
Discover why teams resist AI and how leaders can drive real buy-in using behavioural science, transparency, and human-centred adoption strategies.
People in office meeting with person on screen via video call.
By Eden Smith December 2, 2025
Discover why Data Translators, hybrid talent blending business, data, and communication, are becoming essential as organisations move beyond pure tech roles.
Show More