4.2: Kasia Chmielinski

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Project Lead and Co-Founder, Data Nutrition Project¹²⁶ www.linkedin.com/in/kchmielinski/

Although the impulse is to believe in the objectivity of the machine, we need to remember that algorithms were built by people. When a human judge makes a decision, it is within our right to respectfully disagree. We understand that people are not infallible and we leverage frameworks like the appeals process to address what we feel are injustices. We should consider algorithmically-determined judgements in the same exact manner; if we blindly accept algorithmically-determined decisions, we are giving up the very important right to appeal and investigate what could be injustices on the part of the algorithm. The algorithm is only reflecting what it has been taught to believe, and often by a very homogenous group of people. Thus, the ability to appeal, alongside the importance of diversifying the pool of people who are building algorithms, can move us along a path towards better artificial intelligence.

References

Hilary Ross and Nicole West Bassoff (29 November 2018), “The ‘Dataset Nutrition Label Project’ tackles dataset health and standards,” Medium, https://medium.com/berkman-klein-cen...s-658dc162dfbb

Contributors and Attributions

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