2022_심화영어독해와작문

A. Listen to the talk and fill in the blanks with the words from the box. If necessary, change the form of the words. Wrap Up input sensitivity norm woman intentional Aspects Details General Introduction AI systems are expected to follow social and be fair and unbiased. Source of Bias Bias is tied to flawed or unrefined data and would likely lead to biased outcomes. Case Study Hiring AI: A U.S. company used employee résumés, which led to bias against . Ethical Use of AI Developers should review data; handling bias requires and openness. Key Message Bias isn’t always , but correcting it helps ensure fair outcomes. B. Read the passage and answer the questions. In employment, AI software processes résumés and analyzes job interviewees’ voice and facial expressions as part of the hiring process. Rather than replacing employees, AI takes on the important technical tasks of their work, like providing routes for package delivery trucks, which potentially frees workers to focus on other responsibilities, making them more productive and, therefore, more valuable to employers. It’s allowing employees to do more, and to do it better. They make fewer errors and can develop their expertise and disseminate it more effectively throughout the organization. Though automation is here to stay, the elimination of entire job categories, like highway toll-takers who were replaced by sensors because of AI’s proliferation, is likely to be rare, according to Fuller. 1. Which statement would the writer most probably agree with? ⓐ AI has not significantly improved accuracy in the workplace. ⓑ AI enhances employee productivity by automating routine tasks. ⓒ Using AI automation makes employees less valuable to companies. 2. How does AI affect employees’ productivity and job security in the hiring process, according to Fuller? 136 I Unit 5