Artificial Intelligence (AI)

Artificial intelligence is changing how we design, decide, and deliver services. But at 1508, we believe the real question is not just what AI can do; it’s how we choose to use it. We explore AI with a responsible mindset, focusing on its human, structural, and environmental implications, and help organizations apply it with intention and awareness of its wider impact.

What do we mean by Artificial Intelligence?

So, when we talk about AI, we don’t mean intelligent robots, general artificial intelligence or science fictiony stuff. Sure that’s also cool, but we talk about systems that uncover structure, predict, personalize, recognize or generate content – using machine learning eg. using large language models.

Why it matters

AI influences people, society, and the planet in ways that go far beyond the technology itself. Understanding these effects helps us see where AI creates value and where it risks reinforcing existing problems.

• Human impact: AI changes how people learn, work, and interact. Even simple tools like recommenders or chatbots can shape what we see, choose, and believe, influencing trust, agency, and behaviour.
  

• Structural impact: Beyond individuals, AI affects how societies function. It can shift power, reinforce inequalities, and deepen our dependence on large-scale infrastructures and corporate control, raising questions of governance and accountability.
  

• Environmental impact: Training and running large models consume massive amounts of energy and water. Every AI service leaves a footprint that must be weighed against the value it creates.

Key Facts and Principles of Responsible AI

It’s easy to get caught up in speed, scale, and innovation, when you work with AI. But what makes AI truly valuable is whether it is used responsibly.

At 1508, we’ve defined a set of Responsible AI principles to guide how we design and apply AI for people and for the planet.

• Make the technology understandable
  Help people grasp what the AI does and why, so they can make informed choices.
  

• Give users the control
  Design for agency and let people stay in charge, not the system.
  

• Avoid manipulation and bias
  Be mindful of how AI influences behaviour and representation, and prevent harm or unfair treatment.
  

• Think small
  Use only the data, power, and model size that’s needed. Bigger isn’t always better.
  

• Choose your partners with care
  Select data centres and partners that prioritise renewable energy and efficient infrastructure, and that actively work to keep resource use low.
  

• Keep monitoring

  Track how models evolve over time to prevent unnecessary growth in size and energy use — and make sure they continue to align with your intentions.

We use the principles as a compass when helping organizations explore, design, and govern AI solutions that they can stand behind – both today and in the futures they want to shape.

How we help organizations apply Responsible AI

We approach AI with curiosity and care. At 1508, we work with both the opportunities and the dilemmas it brings. Our role is to help organizations understand where AI creates real value – for people, for business, and for the world around us and how to work with it responsibly from the very beginning.

• Exploring value and impact: We help teams uncover where AI can make a meaningful difference – and where it might not.
  

• Designing responsibly: We co-create AI products and experiences that build on responsible design principles such as fairness, transparency, and inclusion.
  

• Practical experimentatio: We prototype and test AI use cases so teams can learn what works in practice before scaling.
  

• Building capability: We train and guide teams to use AI tools like ChatGPT or Midjourney in ways that are effective, creative, and ethically aware.
  

• Ongoing reflection: We create space for dialogue inside organizations so both enthusiasm and skepticism can inform how AI becomes part of everyday work.

Glossary

Algorithmic Accountability

The responsibility of organizations to explain and take ownership of decisions made by AI systems.

Bias

Systematic favoritism or discrimination in AI outputs, often arising from imbalanced training data.

Ethics by Design

An approach where ethical reflection and safeguards are embedded directly into the design of AI systems.

Generative AI

AI systems that create new content, from text and images to audio and video.

High-Risk AI

As defined by the EU AI Act, AI systems that significantly affect rights, safety, or critical decisions, requiring strict oversight.

Large Language Model (LLM)

An AI trained on massive text datasets, capable of summarizing, reasoning, and conversation.

Machine Learning (ML)

A branch of AI where systems learn patterns from data and improve performance over time.

Neural Networks

Algorithms inspired by the human brain that underpin many modern AI systems.

Responsible AI

AI designed and deployed with principles about eg. fairness, transparency, sustainability, and accountability in mind.