Seeing Beyond the Algorithm | Jenna Hammoud | TEDxYouth@JeffersonStreet

AI Bias and its Impact - AI systems learn and repeat biases and inequalities present in the world due to being trained on biased data [5] - AI bias can lead to exclusion, such as in hiring processes where AI tools favor certain demographics over others [7][8][10][11] - Lack of representation in AI training data can result in systems that do not accurately recognize or serve all users [15][20] The Importance of Awareness and Critical Thinking - Awareness and AI literacy are crucial for challenging biased AI systems and promoting change [6][23] - Questioning AI responses and outcomes can help break the cycle of reinforcing existing biases [6][18] - Individuals have the power to shape the future of AI by being informed, curious, and unafraid to challenge the systems around them [24] Examples of AI Bias and Exclusion - An AI hiring tool favored men due to being trained on 10 years of resumes primarily from men [7][9] - Facial recognition systems have difficulty accurately detecting darker-skinned and female faces [20] - Voice recognition systems may not be trained to recognize higher-pitched voices, excluding women [15] Call to Action - Individuals should understand the biases rooted within technology to question and challenge outcomes [18] - Promoting ethical and equitable AI systems requires collective effort and awareness [22] - The goal is to lead AI and the world towards a future that is fair, inclusive, and human-centered [25]