Avoiding Social Bias in AI Systems - Troy T. Taylor

!mpact
2 min readJan 15, 2021

--

As we move deeper and deeper towards our reliance on AI and Machine Learning to make decisions on our behalf, it is crucial that these tools are not built with the capacity to be infected with the pitfalls of human bias.

At the onset of their development, AI are like children in the sense that they are born innocent of bias but later taught bias through their environment and training. If their basic education is filled with bias, no matter how unconscious it may be, as these systems develop and become independent of their human creators these biases will remain. This partiality could expand and infect their decision-making processes.

There will come a point when we will not question the AI system’s decisions nor will we be able to intervene in the results. As a consequence, the real-world risk of bias exists. If we are not vigilant and fail to create specific governance policies and procedures, these systems could potentially introduce unwanted biases that will limit the promises of a diverse, equitable, and inclusive world.

Should corporate governance include DE&I in the world of AI and Machine Learning? Isn’t it a question of sustainability? How Machine Learning is influencing Diversity & Inclusion by Pierre Debois is a must read!

Sign up to discover human stories that deepen your understanding of the world.

Free

Distraction-free reading. No ads.

Organize your knowledge with lists and highlights.

Tell your story. Find your audience.

Membership

Read member-only stories

Support writers you read most

Earn money for your writing

Listen to audio narrations

Read offline with the Medium app

--

--

!mpact
!mpact

Written by !mpact

!mpact Magazine is a platform where people with a vision can share their ideas and insights.

No responses yet

Write a response