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AI-by-Design: What to Remember

•3 min read•By Ioannis Zempekakis
AI by DesignTakeawaysLeadershipStrategyPart 5

AI-by-Design: What to Remember

Part 5 (final) of the AI-by-Design series. Start from Part 1.

After years of working with AI teams, building frameworks, and learning from both successes and failures, here are the 7 key takeaways from AI-by-Design.

1. Start with Customer Needs

Define the problem before working on the solution. Otherwise, you might end up building a solution that nobody wants to use.

2. Combine Service Design with Data Science

It will make your products and services more effective, liked by your customers, and ethical. The intersection is where the real magic happens.

3. Educate Each Other About the Basics, but Don't Switch Jobs

Interdisciplinary collaboration within an AI innovation team can greatly benefit the project outcome. Allow everyone to gain a fundamental understanding of both design and technology.

You do not need to be a data scientist to work with AI, nor do you need to be a designer to take a human-centric approach to innovation.

4. Make a Conscious AI Decision

Not every project can and should involve AI. Before committing, assess the difficulty, costs, and ethical side of it. Sometimes the best decision is to not use AI.

5. Design for Trust

Design for transparency, explainability and unbiasedness. This builds trust with your users and improves the customer experience. Without trust, even the best AI solution will fail.

6. It Takes Time, So Start Today

It takes time to mature into an AI-by-Design organisation and to have a fully operational dataset. Begin now to pave the way for future AI projects. Even if you can't apply the full process, just start and explore.

7. Bring the Team Together to Prepare for the Future

Data science and design don't naturally work together, so we need a helping hand to start collaborating. Even if you don't have a current AI project, start the preparation now. You will most likely need it.

Becoming an AI organisation demands focusing on solving the right problem, designing data solutions with feedback loops and explainability, and continuous iteration to get better.

The Full Series

  1. Introduction to AI-by-Design
  2. Why Do We Need AI-by-Design?
  3. The 6-Step Framework
  4. The Framework in Practice: Real Cases from OLX
  5. What to Remember (you are here)

Get in Touch

Do you believe we can make the world better by combining AI and design? I'd love to have a conversation.