2022_심화영어독해와작문

frictionless discriminate subjectivity surveillance safeguard indispensable favoritism disparate marginalized Find words which mean: • the influence of personal beliefs or feelings, rather than facts: • extremely important and necessary: • (of a person, group, or concept) treated as insignificant: Opinions Q4 What did Michael Sandel say are the disadvantages of algorithmic decision- making? Q5 Write about the conflicting opinions of Fuller and Sandel on the ethical issues of AI. Not everyone sees blue skies on the horizon, however. Many worry whether the coming age of AI will bring new, faster, and frictionless ways to discriminate against certain groups and divide society. “Part of the appeal of algorithmic decision-making is that it seems to offer an objective way of overcoming human subjectivity, bias, and prejudice,” said Michael Sandel, a political philosophy professor at Harvard University Law School. “But we are discovering that many of the algorithms that decide who should get parole, for example, or who should be presented with employment opportunities or housing replicate the biases that already exist in our society.” AI presents three major areas of ethical concern for society: privacy and surveillance, bias and discrimination, and, perhaps the deepest, most difficult philosophical question of the era, the role of human judgment. “Debates about privacy safeguards and how to overcome bias in algorithmic decision-making in sentencing, parole, and employment practices are by now familiar,” said Sandel, referring to the conscious and unconscious prejudices of program developers, as well as those built into the datasets used to train the software. “But we’ve not yet wrapped our minds around the hardest question: Can smart machines outthink us, or are certain elements of human judgment indispensable in deciding some of the most important things in life?” Panic over AI suddenly injecting bias into everyday life on a large scale is overstated, says Fuller. He argues that the business world and the workplace, which are full of human decision-making, have always involved “all sorts” of biases that prevent people from making deals or landing contracts and jobs. When adjusted carefully and deployed thoughtfully, résumé-screening software allows a wider pool of applicants to be considered than could be done otherwise and should minimize the potential for favoritism that comes with human gatekeepers. Sandel disagrees. “AI not only replicates human biases, but also confers on these biases a kind of scientific credibility. It makes it seem that these predictions and judgments have an objective status,” he said. In the world of lending, algorithm-driven decisions do have a potential “dark side,” said Karen Mills, the former head of the U.S. Small Business Administration. As machines learn from datasets they’re fed, chances are “pretty high” they may replicate many of the banking industry’s past failings that resulted in the systematic disparate treatment of African Americans and other marginalized consumers. “If we’re not thoughtful and careful, we’re going to end up with institutional discrimination again,” she said. Possible Risks of AI Ethical Issues 5 10 15 20 25 30 35 120 I Unit 5