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Organisational Management for AI – Five Key Principles

Artificial Intelligence is a science that mimics human intelligence and other phenomena that exist in nature, such as evolution. Plenty of concepts that work out for humans are therefore directly applicable to algorithms. Concepts that work out for organisations of humans are relevant for organisations of algorithms. Therefore, when recruiting your team of AI workers, think carefully how you want to organise them and how they should complement each other. Below we describe five key principles to consider when building a team of AI brains.


1. Decide who is in charge

We won’t go into a never-ending discussion of centralised versus decentralised control. One thing is however clear: things tend to fall between the chairs when there is no clear responsible person AI.


2. Make sure the team members complement each other

We all know about the benefits of diversity and inclusion in teams of people. Different opinions and approaches are great in brainstorming sessions and the same goes for AI brains. Just like people, different algorithms complement each other and find better solutions faster.


3. Make sure the team members don’t have communication problems

When several brains work together, they better make sure to have access to the latest information. When a colleague sees a piece of new data, finds out a piece of new information, or comes to a new conclusion, it needs to be communicated instantly to other colleagues working on the same problem. In the AI world we call it common state space, and a mechanism of tackling data updates is linked data. In addition, communication problem can arise when AI brains do not talk the same language (can be solved through adaptors) or do not have the same background (can be solved through semantic mapping of concepts).


4. Healthy competition never hurts

Let two AI colleagues compete in solving the same problem. It will consume some extra resources but will bring multiple benefits: redundancy, opportunity of doing federated learning, and finding out what algorithm gives you the best results.


5. Know your heroes

Rewards are important, also in the world of AI brains. It’s the main thing behind reinforcement learning, while training your algorithm, but also among different algorithms – keep track of your best machine learning models for each specific purpose, so that you know whom to turn to in the future.

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