Bias in Algorithm
First, we need to define an algorithm, “an algorithm is just the specific set of steps needed to perform some type of computation.” This can be applied to anything and not just science-related. One thing that I learned that stuck out to me was that the first rule of algorithms is that they are just opinions hidden in codes. Our biases and assumptions are all put into code, and this can be conscious or unconscious. What surprised me was that many people feel that biases cannot be present in AI, but in fact, they are sometimes as biased as humans. One major thing that I took away was how we fight the biases within our AI. Joy Buolamwini talked about how we need to create more inclusive code and employ inclusive coding practices. She also said that who codes matters how we code matters, and why we code matters. AI can spread bias on a large scale at lightning speed so we need to make sure that it isn’t biased or harmful. I feel that my thinking has changed about the AI around me and taking into consideration our naturally biased society.
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Buolamwini, J. (n.d.). How I’m fighting bias in algorithms. Joy Buolamwini: How I’m fighting bias in algorithms | TED Talk. Retrieved May 17, 2022, from https://www.ted.com/talks/joy_buolamwini_how_i_m_fighting_bias_in_algorithms
Hauser, R. (n.d.). Can we protect AI from our biases? Robin Hauser: Can we protect AI from our biases? | TED Talk. Retrieved May 17, 2022, from https://www.ted.com/talks/robin_hauser_can_we_protect_ai_from_our_biases
O’Neil, C. (n.d.). The era of blind faith in big data must end. Cathy O’Neil: The era of blind faith in big data must end | TED Talk. Retrieved May 17, 2022, from https://www.ted.com/talks/cathy_o_neil_the_era_of_blind_faith_in_big_data_must_end
Algorithmic Inequality-Chapter 7
