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A guide to Human Centered AI and the balance of human involvement in its design.


What is human centred AI?


HCAI focuses on designing AI systems to amplify rather than replace human interaction by placing the human at the centre of the design, creating a deep understanding of real life users in real world contexts. It promotes the importance of human needs, values and capabilities. By both human and machine working together to develop AI systems, we are seeing a shift from AI systems simply working for us to actually working with us.


Advantages of Human Centered AI:


Improved user experience

  • By designing with human needs and capabilities at the forefront of the AI system, it may well understand users better, giving them enhanced user experience.


Responsibly designed

  • By ensuring questions are asked within the AI design process such as is this fair? Does this affect anyone else? Is there a better, more compassionate response?

  • By humans guiding this question-asking, we see them complement the hard and fast data that most AI systems produce, by adding a touch of moral judgement and empathy.


Gain in trust

  • By ensuring human needs are deeply considered, data from AI systems could be more accurate and reliable, resulting in end users potentially placing more trust in the system.

  • Knowledge is also gained from its users from feedback loops. This human input provides the means to learn where parts of the system could be improved.


Challenges of Human Centered AI:


Whilst Human Centered AI design comes with many advantages, there are also some challenges:


Ethical considerations vs business targets:

A decision made from an AI system that prioritises considerate or fair information might not be the most business critical outcome. This will require many organisations to revisit and discuss collectively what their business priorities are, potentially redefining their measures of success.


Collaboration:

For human centered AI design to be a success, many disciplines need to be involved in its development. Many organisations fall victim to siloed working; teams working in isolation towards a goal that other teams (often in the same building) are working to also. Organisations need to promote the right environments to allow cross departmental team working; to provide a space for stakeholders to come together to edge closer and closer to their common goal, creating a far greater outcome from different expertise and differing view points.


As IBM puts it, “the future of data science is a collaboration between humans and AI systems.”

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